From 9ace76832d413c1ba2384fceebdbe77ded4be15f Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Tue, 8 Sep 2020 20:36:28 +0200 Subject: [PATCH 01/40] Add gititnore and codeowners --- .gitignore | 101 +++++++++++++++++++++++++++++++++++++++++++++++++++++ CODEOWNERS | 37 ++++++++++++++++++++ 2 files changed, 138 insertions(+) create mode 100644 .gitignore create mode 100644 CODEOWNERS diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..66482ec --- /dev/null +++ b/.gitignore @@ -0,0 +1,101 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +env/ +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib64/ +parts/ +sdist/ +var/ +*.egg-info/ +.installed.cfg +*.egg + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*,cover +.hypothesis/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# IPython Notebook +.ipynb_checkpoints + +# pyenv +.python-version + +# celery beat schedule file +celerybeat-schedule + +# dotenv +.env + +# virtualenv +.venv/ +venv/ +ENV/ + +# Spyder project settings +.spyderproject + +# IDEs +.idea/ +.vscode/ + +# Rope project settings +.ropeproject + +# mypy +.mypy_cache/ + +# pytest +.pytest_cache/ + +# data diff --git a/CODEOWNERS b/CODEOWNERS new file mode 100644 index 0000000..816ce1c --- /dev/null +++ b/CODEOWNERS @@ -0,0 +1,37 @@ +# This is a comment. +# Each line is a file pattern followed by one or more owners. + +# These owners will be the default owners for everything in +# the repo. Unless a later match takes precedence, +# @global-owner1 and @global-owner2 will be requested for +# review when someone opens a pull request. +* @CharlyEmpereurmot + +# Order is important; the last matching pattern takes the most +# precedence. When someone opens a pull request that only +# modifies JS files, only @js-owner and not the global +# owner(s) will be requested for a review. +*.py @CharlyEmpereurmot @giovannidoni + +# You can also use email addresses if you prefer. They'll be +# used to look up users just like we do for commit author +# emails. +# *.go docs@example.com + +# In this example, @doctocat owns any files in the build/logs +# directory at the root of the repository and any of its +# subdirectories. +# /build/logs/ @doctocat + +# The `docs/*` pattern will match files like +# `docs/getting-started.md` but not further nested files like +# `docs/build-app/troubleshooting.md`. +# docs/* docs@example.com + +# In this example, @octocat owns any file in an apps directory +# anywhere in your repository. +# apps/ @octocat + +# In this example, @doctocat owns any file in the `/docs` +# directory in the root of your repository. +# /docs/ @doctocat \ No newline at end of file From 9ee096e72a392fad7bd6fa3d6e335f386162ebff Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Tue, 8 Sep 2020 21:37:44 +0200 Subject: [PATCH 02/40] reorder import --- swarmcg/analyze_optimization.py | 44 +++++++++++---------- swarmcg/evaluate_model.py | 19 ++++----- swarmcg/optimize_model.py | 12 +++--- swarmcg/shared/__init__.py | 0 swarmcg/swarmCG.py | 70 +++++++-------------------------- 5 files changed, 50 insertions(+), 95 deletions(-) create mode 100644 swarmcg/shared/__init__.py diff --git a/swarmcg/analyze_optimization.py b/swarmcg/analyze_optimization.py index 2083889..5dc9488 100644 --- a/swarmcg/analyze_optimization.py +++ b/swarmcg/analyze_optimization.py @@ -1,16 +1,18 @@ -import warnings - # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings +import warnings warnings.filterwarnings("ignore") -import matplotlib.pyplot as plt -from matplotlib.ticker import MaxNLocator -import numpy as np -# from pylab import polyfit import os, sys from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS from shlex import quote as cmd_quote + +import matplotlib.pyplot as plt +from matplotlib.ticker import MaxNLocator +import numpy as np + from . import config from . import swarmCG as scg +from shared.utils import forward_fill + warnings.resetwarnings() @@ -96,7 +98,7 @@ def main(): try: used_dihedrals = iter_indep_scores[:,0] for i in range(1, iter_indep_scores.shape[1]): - scg.forward_fill(iter_indep_scores[:,i], config.sim_crash_EMD_indep_score) + forward_fill(iter_indep_scores[:,i], config.sim_crash_EMD_indep_score) except IndexError: sys.exit(config.header_error+'The optimization recap file seems empty, please wait for your optimization process to start or check for errors during execution') @@ -283,22 +285,22 @@ def main(): # display indicator when simulation(s) crashed for any reason -- check for None gyr_cg to identify a simulation as crashed crashes_ids = np.where(all_gyr_cg == None)[0]+1 - scg.forward_fill(all_eval_scores, None) - scg.forward_fill(all_fit_score_total, None) - scg.forward_fill(all_fit_score_constraints_bonds, None) - scg.forward_fill(all_fit_score_angles, None) - scg.forward_fill(all_fit_score_dihedrals, None) - scg.forward_fill(all_gyr_aa_mapped, None) - scg.forward_fill(all_gyr_aa_mapped_std, None) + forward_fill(all_eval_scores, None) + forward_fill(all_fit_score_total, None) + forward_fill(all_fit_score_constraints_bonds, None) + forward_fill(all_fit_score_angles, None) + forward_fill(all_fit_score_dihedrals, None) + forward_fill(all_gyr_aa_mapped, None) + forward_fill(all_gyr_aa_mapped_std, None) # all_gyr_cg = np.where(all_gyr_cg == None, 0, all_gyr_cg) - scg.forward_fill(all_gyr_cg, None) - scg.forward_fill(all_gyr_cg_std, None) - scg.forward_fill(all_sasa_aa_mapped, None) - scg.forward_fill(all_sasa_aa_mapped_std, None) + forward_fill(all_gyr_cg, None) + forward_fill(all_gyr_cg_std, None) + forward_fill(all_sasa_aa_mapped, None) + forward_fill(all_sasa_aa_mapped_std, None) # all_sasa_cg = np.where(all_sasa_cg == None, 0, all_sasa_cg) - # scg.forward_fill(all_sasa_cg, 0) - scg.forward_fill(all_sasa_cg, None) - scg.forward_fill(all_sasa_cg_std, None) + # forward_fill(all_sasa_cg, 0) + forward_fill(all_sasa_cg, None) + forward_fill(all_sasa_cg_std, None) for i in range(len(all_gyr_aa_mapped)): all_gyr_aa_mapped[i] += all_gyr_aa_mapped_offset diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index a70f388..3cbddae 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -1,22 +1,17 @@ -import warnings - # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings +import warnings warnings.filterwarnings("ignore") -import os, re, sys +import os, sys +from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS from shlex import quote as cmd_quote + import matplotlib -matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation -import matplotlib.pyplot as plt -from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS -# import argcomplete # arguments completion currently disabled because it's one more library to install -from random import randint -import numpy as np -import scipy.stats -from pyemd import emd -import MDAnalysis as mda + from . import config from . import swarmCG as scg + warnings.resetwarnings() +matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation def main(): diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 8605a43..a950915 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -1,17 +1,17 @@ -import warnings - # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings +import warnings warnings.filterwarnings("ignore") -import os, sys, re, shutil, subprocess, time, copy, contextlib +import os, sys, shutil, subprocess, time, copy, contextlib from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS from shlex import quote as cmd_quote +from datetime import datetime + from fstpso import FuzzyPSO import numpy as np -from datetime import datetime -from scipy.optimize import curve_fit -import MDAnalysis as mda + from . import config from . import swarmCG as scg + warnings.resetwarnings() diff --git a/swarmcg/shared/__init__.py b/swarmcg/shared/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index c57764b..b435304 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -1,24 +1,25 @@ -from pyemd import emd -import sys, re, random, os, shutil, subprocess, signal, time, contextlib, warnings, textwrap +# some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings +import warnings +warnings.filterwarnings("ignore") +import collections + +import (sys, re, random, os, shutil, subprocess, signal, time, contextlib, + warnings, textwrap, collections) +from datetime import datetime # matplotlib new version has some problems with incorrectly uninstalled files at version upgrade and display a lot of warnings # also some numpy version have this ufunc warning at import -warnings.filterwarnings("ignore") import numpy as np import matplotlib -matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation import matplotlib.pyplot as plt +from pyemd import emd + from scipy.spatial.distance import cdist -from scipy.cluster.hierarchy import linkage, fcluster -from scipy.spatial.distance import squareform from scipy.optimize import curve_fit -from scipy.signal import lfiltic, lfilter -from itertools import compress -# import networkx as nx -import MDAnalysis as mda -import collections -from datetime import datetime + from . import config + +matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation warnings.resetwarnings() # TODO: When provided trajectory file does NOT contain PBC infos (box position and size for each frame, which are present in XTC format for example), we want to stil accept the provided trajectory format (if accepted by MDAnalysis) but we automatically disable the handling of PBC by the code @@ -54,49 +55,6 @@ def header_package(module_line): '''+config.sep_close+'\n' -def forward_fill(arr, cond_value): - - # out = np.empty(len(arr)) - valid_val = None - for i in range(len(arr)): - if arr[i] != cond_value: - # out[i] = arr[i] - valid_val = arr[i] - else: - j = i - while valid_val == None and j < len(arr): - j += 1 - try: - if arr[j] != cond_value: - valid_val = arr[j] - break - except IndexError: - sys.exit(config.header_error+'Unexpected read of the optimization results, please check that your simulations have not all been crashing') - if valid_val != None: - # out[i] = valid_val - arr[i] = valid_val - else: - sys.exit('All simulations crashed, nothing to display\nPlease check the setup and settings of your optimization run') - # return out - return - - -# simple moving average -def sma(interval, window_size): - window = np.ones(int(window_size))/float(window_size) - return np.convolve(interval, window, 'same') - - -# exponential moving average -def ewma(a, alpha, windowSize): - wghts = (1-alpha)**np.arange(windowSize) - wghts /= wghts.sum() - out = np.full(len(a), np.nan) - # out[windowSize-1:] = np.convolve(a, wghts, 'valid') - out = np.convolve(a, wghts, 'same') - return out - - # cast object as string, enclose by parentheses and return a string -- for arguments display in help def par_wrap(string): return '('+str(string)+')' @@ -115,7 +73,7 @@ def set_MDA_backend(ns): ns.mda_backend = 'serial' return - + # draw random float between given range and apply rounding to given digit def draw_float(low, high, dg_rnd): From 3432f4d1e374ef0511ec051c00b545029dcd0629 Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Tue, 8 Sep 2020 21:39:43 +0200 Subject: [PATCH 03/40] Add new files --- swarmcg/shared/exceptions.py | 3 +++ swarmcg/shared/utils.py | 51 ++++++++++++++++++++++++++++++++++++ 2 files changed, 54 insertions(+) create mode 100644 swarmcg/shared/exceptions.py create mode 100644 swarmcg/shared/utils.py diff --git a/swarmcg/shared/exceptions.py b/swarmcg/shared/exceptions.py new file mode 100644 index 0000000..385c687 --- /dev/null +++ b/swarmcg/shared/exceptions.py @@ -0,0 +1,3 @@ +header_error = "\n-- ! ERROR ! --\n" +header_warning = "\n-- ! WARNING ! --\n" +header_gmx_error = "\n GMX ERROR MSG\n'+sep+'\n\n" \ No newline at end of file diff --git a/swarmcg/shared/utils.py b/swarmcg/shared/utils.py new file mode 100644 index 0000000..17a4474 --- /dev/null +++ b/swarmcg/shared/utils.py @@ -0,0 +1,51 @@ +import sys + +import numpy as np + +import exceptions + + +def forward_fill(arr, cond_value): + + # out = np.empty(len(arr)) + valid_val = None + for i in range(len(arr)): + if arr[i] != cond_value: + # out[i] = arr[i] + valid_val = arr[i] + else: + j = i + while valid_val is None and j < len(arr): + j += 1 + try: + if arr[j] != cond_value: + valid_val = arr[j] + break + except IndexError as e: + msg = """{} Unexpected read of the optimization results, + please check that your simulations have not all been crashing + """.format(exceptions.header_error) + sys.exit(msg) + + if valid_val is not None: + # out[i] = valid_val + arr[i] = valid_val + else: + msg = """All simulations crashed, nothing to display. + Please check the setup and settings of your optimization run + """ + sys.exit(msg) + +# simple moving average +def sma(interval, window_size): + window = np.ones(int(window_size)) / float(window_size) + return np.convolve(interval, window, 'same') + +# exponential moving average +def ewma(a, alpha, windowSize): + wghts = (1 - alpha) ** np.arange(windowSize) + wghts /= wghts.sum() + out = np.full(len(a), np.nan) + # out[windowSize-1:] = np.convolve(a, wghts, 'valid') + out = np.convolve(a, wghts, 'same') + return out \ No newline at end of file From 8cc7396cc727deb47c4db68d72026164fd153635 Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Wed, 9 Sep 2020 11:56:47 +0200 Subject: [PATCH 04/40] Add tests and env --- environment.yml | 24 ++++++++++++++++++++++++ swarmcg/shared/utils.py | 26 ++++++++++++++------------ tests/shared/test_utils.py | 29 +++++++++++++++++++++++++++++ 3 files changed, 67 insertions(+), 12 deletions(-) create mode 100644 environment.yml create mode 100644 tests/shared/test_utils.py diff --git a/environment.yml b/environment.yml new file mode 100644 index 0000000..728e713 --- /dev/null +++ b/environment.yml @@ -0,0 +1,24 @@ +name: swarmcg +channels: + - conda-forge +dependencies: + - cycler=0.10.0 + - dscribe=0.4.0 # 0.3.5 available for linux + - matplotlib=3.2.0 # 3.2.1 available + - mdanalysis>=1.0.0 + - mypy=0.770 + - numpy=1.19.1 + - pandas=1.0.1 + - pip + - pybind11=2.4.3 # 2.5.0 available + - pyemd=0.5.1 + - pylint=2.4.4 + - pytest=5.4.1 + - pytest-runner=5.2 + - python=3.7.6 + - scikit-learn=0.22.2.post1 + - scipy=1.4.1 + - setuptools + - wheel + - pip: + - fst-pso diff --git a/swarmcg/shared/utils.py b/swarmcg/shared/utils.py index 17a4474..ce43308 100644 --- a/swarmcg/shared/utils.py +++ b/swarmcg/shared/utils.py @@ -2,7 +2,7 @@ import numpy as np -import exceptions +from . import exceptions def forward_fill(arr, cond_value): @@ -36,16 +36,18 @@ def forward_fill(arr, cond_value): """ sys.exit(msg) -# simple moving average -def sma(interval, window_size): - window = np.ones(int(window_size)) / float(window_size) - return np.convolve(interval, window, 'same') -# exponential moving average -def ewma(a, alpha, windowSize): +def sma(x, window_size): + """ + Implement simple moving average with convolution operator. + """ + return ewma(x, 1, window_size) + + +def ewma(x, alpha, windowSize): + """ + Implement expontential moving average with convolution operator. + """ wghts = (1 - alpha) ** np.arange(windowSize) - wghts /= wghts.sum() - out = np.full(len(a), np.nan) - # out[windowSize-1:] = np.convolve(a, wghts, 'valid') - out = np.convolve(a, wghts, 'same') - return out \ No newline at end of file + wghts = wghts / wghts.sum() + return np.convolve(x, wghts, 'same') \ No newline at end of file diff --git a/tests/shared/test_utils.py b/tests/shared/test_utils.py new file mode 100644 index 0000000..ed39193 --- /dev/null +++ b/tests/shared/test_utils.py @@ -0,0 +1,29 @@ +import numpy as np +from numpy.testing import assert_almost_equal + +from swarmcg.shared import utils + + +def test_sma(): + # given: + x = np.arange(10) + + # when: + window_size = 5 + result = utils.sma(x, window_size) + + # then: + expected = np.array([2, 3, 4, 5, 6, 7, 8, 9, 0, 0], dtype=float) + assert_almost_equal(result, expected) + +def test_ema(): + # given: + x = np.arange(10) + + # when: + window_size = 5 + result = utils.ewma(x, 1, window_size) + + # then: + expected = np.array([2, 3, 4, 5, 6, 7, 8, 9, 0, 0], dtype=float) + assert_almost_equal(result, expected) \ No newline at end of file From 12c0a8af1a335a139ba1e1272339e8f5af866381 Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Wed, 9 Sep 2020 12:12:38 +0200 Subject: [PATCH 05/40] Add other test --- swarmcg/shared/utils.py | 2 ++ swarmcg/swarmCG.py | 5 +++-- tests/shared/test_utils.py | 17 ++++++++++++++++- 3 files changed, 21 insertions(+), 3 deletions(-) diff --git a/swarmcg/shared/utils.py b/swarmcg/shared/utils.py index ce43308..bfb380e 100644 --- a/swarmcg/shared/utils.py +++ b/swarmcg/shared/utils.py @@ -36,6 +36,8 @@ def forward_fill(arr, cond_value): """ sys.exit(msg) + return arr + def sma(x, window_size): """ diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index b435304..f5ef5be 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -18,6 +18,7 @@ from scipy.optimize import curve_fit from . import config +from .shared import utils matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation warnings.resetwarnings() @@ -1481,7 +1482,7 @@ def perform_BI(ns): nb_passes = 3 alpha = 0.55 for _ in range(nb_passes): - hist_geoms_modif = ewma(hist_geoms_modif, alpha, int(config.bi_nb_bins/10)) + hist_geoms_modif = utils.ewma(hist_geoms_modif, alpha, int(config.bi_nb_bins/10)) y = -config.kB * ns.temp * np.log(hist_geoms_modif + 1) x = np.linspace(bi_xrange[0], bi_xrange[1], config.bi_nb_bins, endpoint=True) @@ -1498,7 +1499,7 @@ def perform_BI(ns): nb_passes = 5 for _ in range(nb_passes): - deriv = sma(deriv, int(config.bi_nb_bins/5)) + deriv = utils.sma(deriv, int(config.bi_nb_bins/5)) deriv *= np.sqrt(y/min(y)) deriv = 1/deriv diff --git a/tests/shared/test_utils.py b/tests/shared/test_utils.py index ed39193..94e235d 100644 --- a/tests/shared/test_utils.py +++ b/tests/shared/test_utils.py @@ -4,6 +4,20 @@ from swarmcg.shared import utils +# TODO: add test on failure but needs dedicated exceptions rather and sys.exit +def test_forward_fill(): + # given: + x = [1, 2, 10, 4, None, None, 10, 10] + + # when: + cond_value = None + result = utils.forward_fill(x, cond_value) + + # then: + expected = [1, 2, 10, 4, 4, 4, 10, 10] + assert result == expected + + def test_sma(): # given: x = np.arange(10) @@ -26,4 +40,5 @@ def test_ema(): # then: expected = np.array([2, 3, 4, 5, 6, 7, 8, 9, 0, 0], dtype=float) - assert_almost_equal(result, expected) \ No newline at end of file + assert_almost_equal(result, expected) + From cf38d612cc9148d6923f6c4e5233ebb878ed604f Mon Sep 17 00:00:00 2001 From: giovannidoni <9051577+giovannidoni@users.noreply.github.com> Date: Thu, 10 Sep 2020 12:09:22 +0200 Subject: [PATCH 06/40] Cleanup03 (#5) * Create styling module * Use f strings * Use indent size 4 * Return objects after forward fill * Remove folder --- setup.py | 4 +- swarmcg/__init__.py | 1 + swarmcg/analyze_optimization.py | 147 ++-- swarmcg/config.py | 10 - swarmcg/evaluate_model.py | 242 +++--- swarmcg/optimize_model.py | 1334 ++++++++++++++++--------------- swarmcg/shared/styling.py | 142 ++++ swarmcg/swarmCG.py | 152 ++-- 8 files changed, 1130 insertions(+), 902 deletions(-) create mode 100644 swarmcg/shared/styling.py diff --git a/setup.py b/setup.py index 1d85fd6..5176a00 100644 --- a/setup.py +++ b/setup.py @@ -1,11 +1,13 @@ from setuptools import setup, find_packages +import swarmcg + with open('README.md') as readme_file: README = readme_file.read() setup( name='swarm-cg', - version='v1.1.2', + version=swarmcg.__version__, description='Tools for automatic parametrization of bonded terms in coarse-grained molecular models, with respect to an all-atom trajectory', author='Charly Empereur-mot', author_email='charly.empereur@gmail.com', diff --git a/swarmcg/__init__.py b/swarmcg/__init__.py index e69de29..218644a 100644 --- a/swarmcg/__init__.py +++ b/swarmcg/__init__.py @@ -0,0 +1 @@ +__version__ = 'v1.1.2' \ No newline at end of file diff --git a/swarmcg/analyze_optimization.py b/swarmcg/analyze_optimization.py index 5dc9488..fee2066 100644 --- a/swarmcg/analyze_optimization.py +++ b/swarmcg/analyze_optimization.py @@ -1,5 +1,8 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings + +import swarmcg.shared.styling + warnings.filterwarnings("ignore") import os, sys from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS @@ -9,14 +12,14 @@ from matplotlib.ticker import MaxNLocator import numpy as np -from . import config -from . import swarmCG as scg -from shared.utils import forward_fill +from swarmcg import config +from swarmcg.shared.styling import ANALYSE_DESCR +from swarmcg.shared.utils import forward_fill warnings.resetwarnings() -def main(): +def main(ns): # TODO: print some text to tell user if opti run finished or not -- then we can only look at the results files, not the running processes on the machine @@ -32,61 +35,6 @@ def main(): plt.rcParams['axes.axisbelow'] = True - print(scg.header_package(' Module: Optimization run analysis\n')) - - args_parser = ArgumentParser(description='''\ -This module produces a visual summary (big plot) of an optimization procedure started with -module 'scg_optimize' to refine the bonded terms of a coarse-grained (CG) molecular model. -It works whether the optimization is ongoing or finished. The plot will be produced in the -directory provided via argument -opti_dir. - -Top row displays bonded terms score (global and breakdown) together with radius of gyration -(Rg) and solvent accessible surface area (SASA) estimations. We call these estimations because -they are calculated on short simulations used during optimization (time depends on parameters -used for optimization), therefore one should always run a long simulation at the end of the -optimizaton process, from which one can calculate the real Rg and SASA values for your model. - -Other rows display bond, angle and dihedral parameters tested together with their independant -score (distance from the AA distributions using EMD/Wasserstein). This allows to diagnose -issues, notably related to the topology defined in the ITP file, for example if the score -cannot go down for a specific group of bonds, angles or dihedrals. The optimization procedure -is in principle robust, as demonstrated in the paper, however problems can arise from the CG -representation used (e.g. if topology is too restrictive or incorrectly defined) and non-bonded -parameters (e.g. strong intra-molecular attractions that would not allow the molecule to adopt -extended conformations). -''', formatter_class=lambda prog: RawTextHelpFormatter(prog, width=135, max_help_position=52), add_help=False, usage=SUPPRESS) - - args_header = config.sep_close+'\n| ARGUMENTS |\n'+config.sep_close - # bullet = '❭' - # bullet = '★' - # bullet = '|' - bullet = ' ' - - required_args = args_parser.add_argument_group(args_header+'\n\n'+bullet+'INPUT/OUTPUT') - required_args.add_argument('-opti_dir', dest='opti_dirname', help='Directory created by module \'scg_optimize\' that contains all files\ngenerated during the optimization procedure', type=str, metavar='') - required_args.add_argument('-o', dest='plot_filename', help='Filename for the output plot, produced in directory -opti_dir.\nExtension/format can be one of: eps, pdf, pgf, png, ps, raw, rgba,\nsvg, svgz', type=str, default='opti_summary.png', metavar=' (opti_summary.png)') - - optional_args = args_parser.add_argument_group(bullet+'OTHERS') - optional_args.add_argument('-plot_scale', dest='plot_scale', help='Scale factor of the plot', type=float, default=1.0, metavar=' (1.0)') - optional_args.add_argument('-h', '--help', help='Show this help message and exit', action='help') - - # display help if script was called without arguments - if len(sys.argv) == 1: - args_parser.print_help() - sys.exit() - - # arguments handling, display command line if help or no arguments provided - # argcomplete.autocomplete(parser) - ns = args_parser.parse_args() - input_cmdline = ' '.join(map(cmd_quote, sys.argv)) - print('Working directory:', os.getcwd()) - print('Command line:', input_cmdline) - print() - print(config.sep_close) - print('| SUMMARIZING OPTIMIZATION PROCEDURE |') - print(config.sep_close) - print() - # parameters read_offset = 15 # nb of trailing fields that have static lengths in the recap file (i.e. NOT dependent on number of bonds, angles, etc.) min_nb_cols = 9 # to be sure we have enough columns for opti process plots, even if number of bonds/angles/dihedrals is less than this @@ -98,9 +46,10 @@ def main(): try: used_dihedrals = iter_indep_scores[:,0] for i in range(1, iter_indep_scores.shape[1]): - forward_fill(iter_indep_scores[:,i], config.sim_crash_EMD_indep_score) + iter_indep_scores[:,i] = forward_fill(iter_indep_scores[:,i], config.sim_crash_EMD_indep_score) except IndexError: - sys.exit(config.header_error+'The optimization recap file seems empty, please wait for your optimization process to start or check for errors during execution') + sys.exit( + swarmcg.shared.styling.header_error + 'The optimization recap file seems empty, please wait for your optimization process to start or check for errors during execution') # process files and plot with open(ns.opti_dirname+'/'+config.opti_perf_recap_file, 'r') as fp: @@ -285,22 +234,22 @@ def main(): # display indicator when simulation(s) crashed for any reason -- check for None gyr_cg to identify a simulation as crashed crashes_ids = np.where(all_gyr_cg == None)[0]+1 - forward_fill(all_eval_scores, None) - forward_fill(all_fit_score_total, None) - forward_fill(all_fit_score_constraints_bonds, None) - forward_fill(all_fit_score_angles, None) - forward_fill(all_fit_score_dihedrals, None) - forward_fill(all_gyr_aa_mapped, None) - forward_fill(all_gyr_aa_mapped_std, None) + all_eval_scores = forward_fill(all_eval_scores, None) + all_fit_score_total = forward_fill(all_fit_score_total, None) + all_fit_score_constraints_bonds = forward_fill(all_fit_score_constraints_bonds, None) + all_fit_score_angles = forward_fill(all_fit_score_angles, None) + all_fit_score_dihedrals = forward_fill(all_fit_score_dihedrals, None) + all_gyr_aa_mapped = forward_fill(all_gyr_aa_mapped, None) + all_gyr_aa_mapped_std = forward_fill(all_gyr_aa_mapped_std, None) # all_gyr_cg = np.where(all_gyr_cg == None, 0, all_gyr_cg) - forward_fill(all_gyr_cg, None) - forward_fill(all_gyr_cg_std, None) - forward_fill(all_sasa_aa_mapped, None) - forward_fill(all_sasa_aa_mapped_std, None) + all_gyr_cg = forward_fill(all_gyr_cg, None) + all_gyr_cg_std = forward_fill(all_gyr_cg_std, None) + all_sasa_aa_mapped = forward_fill(all_sasa_aa_mapped, None) + all_sasa_aa_mapped_std = forward_fill(all_sasa_aa_mapped_std, None) # all_sasa_cg = np.where(all_sasa_cg == None, 0, all_sasa_cg) - # forward_fill(all_sasa_cg, 0) - forward_fill(all_sasa_cg, None) - forward_fill(all_sasa_cg_std, None) + # all_sasa_cg = forward_fill(all_sasa_cg, 0) + all_sasa_cg = forward_fill(all_sasa_cg, None) + all_sasa_cg_std = forward_fill(all_sasa_cg_std, None) for i in range(len(all_gyr_aa_mapped)): all_gyr_aa_mapped[i] += all_gyr_aa_mapped_offset @@ -658,6 +607,54 @@ def main(): print('Wrote visual optimization summary file at location:\n ', os.path.normpath(ns.opti_dirname+'/'+ns.plot_filename)) print() +if __name__ == '__main__': + + print(swarmcg.shared.styling.header_package( + ' Module: Optimization run analysis\n')) + + formatter = lambda prog: RawTextHelpFormatter(prog, width=135, max_help_position=52) + args_parser = ArgumentParser( + description=ANALYSE_DESCR, + formatter_class=formatter, + add_help=False, + usage=SUPPRESS + ) + + args_header = swarmcg.shared.styling.sep_close + '\n| ARGUMENTS |\n' + swarmcg.shared.styling.sep_close + bullet = ' ' + + required_args = args_parser.add_argument_group(args_header + '\n\n' + bullet + 'INPUT/OUTPUT') + required_args.add_argument('-opti_dir', dest='opti_dirname', + help='Directory created by module \'scg_optimize\' that contains all files\ngenerated during the optimization procedure', + type=str, metavar='') + required_args.add_argument('-o', dest='plot_filename', + help='Filename for the output plot, produced in directory -opti_dir.\nExtension/format can be one of: eps, pdf, pgf, png, ps, raw, rgba,\nsvg, svgz', + type=str, default='opti_summary.png', + metavar=' (opti_summary.png)') + + optional_args = args_parser.add_argument_group(bullet + 'OTHERS') + optional_args.add_argument('-plot_scale', dest='plot_scale', help='Scale factor of the plot', + type=float, default=1.0, metavar=' (1.0)') + optional_args.add_argument('-h', '--help', help='Show this help message and exit', + action='help') + + # display help if script was called without arguments + if len(sys.argv) == 1: + args_parser.print_help() + sys.exit() + + # arguments handling, display command line if help or no arguments provided + ns = args_parser.parse_args() + input_cmdline = ' '.join(map(cmd_quote, sys.argv)) + print('Working directory:', os.getcwd()) + print('Command line:', input_cmdline) + print() + print(swarmcg.shared.styling.sep_close) + print( + '| SUMMARIZING OPTIMIZATION PROCEDURE |') + print(swarmcg.shared.styling.sep_close) + print() + main(ns) diff --git a/swarmcg/config.py b/swarmcg/config.py index 5ee6555..91c5233 100644 --- a/swarmcg/config.py +++ b/swarmcg/config.py @@ -1,5 +1,4 @@ # general stuff -module_version = '1.1.2' github_url = 'http://github.com/GMPavanLab/SwarmCG' gmx_path = 'gmx' @@ -115,15 +114,6 @@ ref_distrib_plots = 'reference_AA_distributions.png' best_distrib_plots = 'optimized_CG_model_distributions.png' -# stdout display formatting -sep = '----------------------------------------------------------------------' -sep_close = '+---------------------------------------------------------------------------------------------+' -# header_warning = '\n========================= /!\\ WARNING /!\\ ==========================\n' -header_warning = '\n-- ! WARNING ! --\n' -# header_error = '\n========================== /!\\ ERROR /!\\ ===========================\n' -header_error = '\n-- ! ERROR ! --\n' -header_gmx_error = sep+'\n GMX ERROR MSG\n'+sep+'\n\n' - diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index 3cbddae..8584e81 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -1,5 +1,8 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings + +import swarmcg.shared.styling + warnings.filterwarnings("ignore") import os, sys from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS @@ -7,8 +10,9 @@ import matplotlib -from . import config -from . import swarmCG as scg +from swarmcg import swarmCG as scg +from swarmcg import config +from swarmcg.shared.styling import EVALUATE_DESCR warnings.resetwarnings() matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation @@ -21,101 +25,6 @@ def main(): # TODO: make it possible to feed a delta for Rg in case the model has scaling ? - # command for tests - # ./evaluate_model.py -aa_tpr ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.tpr -aa_traj ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.xtc -cg_map ../DATA_MDL/Mono_B/MOB_atom_mapping/atomistic/MOB_mapping.ndx -cg_itp MOB_HUMAN_SIM/Mono_B.itp -cg_tpr MOB_HUMAN_SIM/cg_solvated.tpr -cg_traj MOB_HUMAN_SIM/cg_solvated.xtc - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.tpr -aa_traj ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.xtc -cg_map ../DATA_MDL/Mono_B/MOB_atom_mapping/atomistic/MOB_mapping.ndx -cg_itp MOB_HUMAN_SIM/Mono_B.itp - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/fake_for_test.tpr -aa_traj ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/ATOM_TRAJ.xtc -cg_map ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/index_bta.ndx -cg_itp BTA_HUMAN_SIM/bta_P3.itp -cg_tpr BTA_HUMAN_SIM/cg_solvated.tpr -cg_traj BTA_HUMAN_SIM/cg_solvated.xtc - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/POPC/AA/topol.tpr -aa_traj ../DATA_MDL/POPC/AA/traj.trr -cg_map ../DATA_MDL/POPC/CG/mapping.ndx -cg_itp POPC_CG_SIM/martini_v2.0_POPC_02.itp -cg_tpr POPC_CG_SIM/cg_solvated.tpr -cg_traj POPC_CG_SIM/cg_solvated.xtc - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/B3T/AA/topol.tpr -aa_traj ../DATA_MDL/B3T/AA/traj_atom.xtc -cg_map ../DATA_MDL/B3T/CG/MAPPING.ndx -cg_itp ../DATA_MDL/B3T/CG/MARTINI/B3T_CG.itp -cg_tpr B3T_HUMAN_SIM/produced.tpr -cg_traj B3T_HUMAN_SIM/produced.xtc - - - print(scg.header_package(' Module: Model bonded terms assessment\n')) - - args_parser = ArgumentParser(description='''\ -This module enables quick evaluation of the fit of bond, angle and dihedral distributions between -a CG model trajectory and a reference AA model trajectory of an identical molecule, in a single -comprehensive figure. The figure's rows display bond, angle and dihedral distributions for groups -present in your system according to the ITP file. - -Arguments allows to specify scaling of the AA bonds used as reference to optimize the CG model. -An image displaying all AA reference distributions will be created at the very beginning of the -optimization process. You can check it to make sure scaling is conform to your expectations. - -The CG model preliminary ITP file follows the standard ITP format, with one subtlety. The file -can include groups of bonds, angles and dihedrals that will be considered identical. Their -distributions will be averaged within groups. This is important to obtain reliable results for -symmetrical molecules. Groups can be formed using empty line(s) or comment(s), like this: - - [ angles ] - - ; i j k funct angle force.c. - ; grp 1 - 5 6 10 1 150 40 - 9 8 11 1 150 40 - ; grp 2 - 1 6 10 2 120 0 ; NOTE: either comment(s) or empty line(s) - 4 8 11 2 120 0 ; separate groups of bonds/ang/dihe. - -The AA trajectory is mapped on-the-fly using file from argument -cg_map, which uses gromacs NDX -file format. Periodic boundary conditions are handled internally if the input trajectories -contain box dimensions.''', formatter_class=lambda prog: RawTextHelpFormatter(prog, width=135, max_help_position=52), add_help=False, usage=SUPPRESS) - - all_args_header = config.sep_close+'\n| REQUIRED/OPTIONAL ARGUMENTS |\n'+config.sep_close - # bullet = '❭' - # bullet = '★' - # bullet = '|' - bullet = ' ' - - required_args = args_parser.add_argument_group(all_args_header+'\n\n'+bullet+'MODELS FILES') - required_args.add_argument('-aa_tpr', dest='aa_tpr_filename', help=config.help_aa_tpr, type=str, default=config.metavar_aa_tpr, metavar=' '+scg.par_wrap(config.metavar_aa_tpr)) - required_args.add_argument('-aa_traj', dest='aa_traj_filename', help=config.help_aa_traj, type=str, default=config.metavar_aa_traj, metavar=' '+scg.par_wrap(config.metavar_aa_traj)) - required_args.add_argument('-cg_map', dest='cg_map_filename', help=config.help_cg_map, type=str, default=config.metavar_cg_map, metavar=' '+scg.par_wrap(config.metavar_cg_map)) - required_args.add_argument('-cg_itp', dest='cg_itp_filename', help='ITP file of the CG model to evaluate', type=str, default=config.metavar_cg_itp, metavar=' '+scg.par_wrap(config.metavar_cg_itp)) - required_args.add_argument('-cg_tpr', dest='cg_tpr_filename', help='TPR file of your CG simulation (omit for solo AA inspection)', type=str, default=config.metavar_cg_tpr, metavar=' '+scg.par_wrap(config.metavar_cg_tpr)) - required_args.add_argument('-cg_traj', dest='cg_traj_filename', help='XTC file of your CG trajectory (omit for solo AA inspection)', type=str, default=config.metavar_cg_traj, metavar=' '+scg.par_wrap(config.metavar_cg_traj)) - # required_args.add_argument('-figmolname', dest='figmolname', help='TODO REMOVE', type=str, required=True) # TODO: remove, this was just for figures - - optional_args = args_parser.add_argument_group(bullet+'CG MODEL SCALING') - # optional_args.add_argument('-nb_threads', dest='nb_threads', help='number of threads to use', type=int, default=1, metavar='1') # TODO: does NOT work properly -- modif MDAnalysis code with OpenMP num_threads(n) in the pragma - optional_args.add_argument('-bonds_scaling', dest='bonds_scaling', help=config.help_bonds_scaling, type=float, default=config.bonds_scaling, metavar=' '+scg.par_wrap(config.bonds_scaling)) - optional_args.add_argument('-bonds_scaling_str', dest='bonds_scaling_str', help=config.help_bonds_scaling_str, type=str, default=config.bonds_scaling_str, metavar='') - optional_args.add_argument('-min_bonds_length', dest='min_bonds_length', help=config.help_min_bonds_length, type=float, default=config.min_bonds_length, metavar=' '+scg.par_wrap(config.min_bonds_length)) - optional_args.add_argument('-b2a_score_fact', dest='bonds2angles_scoring_factor', help=config.help_bonds2angles_scoring_factor, type=float, default=config.bonds2angles_scoring_factor, metavar=' '+scg.par_wrap(config.bonds2angles_scoring_factor)) - # ONLY FOR PAPER FIGURES - # optional_args.add_argument('-datamol', dest='datamol', help='Save bonded score and Rg values for each frame across simulation', type=str, default='MOL_EXEC_MODE') - - graphical_args = args_parser.add_argument_group(bullet+'FIGURE DISPLAY') - graphical_args.add_argument('-mismatch_ordering', dest='mismatch_order', help='Enables ordering of bonds/angles/dihedrals by mismatch score\nbetween pairwise AA-mapped/CG distributions (can help diagnosis)', default=False, action='store_true') - graphical_args.add_argument('-bw_constraints', dest='bw_constraints', help=config.help_bw_constraints, type=float, default=config.bw_constraints, metavar=' '+scg.par_wrap(config.bw_constraints)) - graphical_args.add_argument('-bw_bonds', dest='bw_bonds', help=config.help_bw_bonds, type=float, default=config.bw_bonds, metavar=' '+scg.par_wrap(config.bw_bonds)) - graphical_args.add_argument('-bw_angles', dest='bw_angles', help=config.help_bw_angles, type=float, default=config.bw_angles, metavar=' '+scg.par_wrap(config.bw_angles)) - graphical_args.add_argument('-bw_dihedrals', dest='bw_dihedrals', help=config.help_bw_dihedrals, type=float, default=config.bw_dihedrals, metavar=' '+scg.par_wrap(config.bw_dihedrals)) - graphical_args.add_argument('-disable_x_scaling', dest='row_x_scaling', help='Disable auto-scaling of X axis across each row of the plot', default=True, action='store_false') - graphical_args.add_argument('-disable_y_scaling', dest='row_y_scaling', help='Disable auto-scaling of Y axis across each row of the plot', default=True, action='store_false') - graphical_args.add_argument('-bonds_max_range', dest='bonded_max_range', help=config.help_bonds_max_range, type=float, default=config.bonds_max_range, metavar=' '+scg.par_wrap(config.bonds_max_range)) - graphical_args.add_argument('-ncols', dest='ncols_max', help='Max. nb of columns displayed in figure', type=int, default=0, metavar='') # TODO: make this a line return in plot instead of ignoring groups - - optional_args2 = args_parser.add_argument_group(bullet+'OTHERS') - optional_args2.add_argument('-o', dest='plot_filename', help='Filename for the output plot (extension/format can be one of:\neps, pdf, pgf, png, ps, raw, rgba, svg, svgz)', type=str, default='distributions.png', metavar='distributions.png') - optional_args2.add_argument('-h', '--help', action='help', help='Show this help message and exit') - optional_args2.add_argument('-v', '--verbose', dest='verbose', help=config.help_verbose, action='store_true', default=False) - - # display help if script was called without arguments - if len(sys.argv) == 1: - args_parser.print_help() - sys.exit() - - # arguments handling, display command line if help or no arguments provided - # argcomplete.autocomplete(parser) - ns = args_parser.parse_args() - input_cmdline = ' '.join(map(cmd_quote, sys.argv)) - print('Working directory:', os.getcwd()) - print('Command line:', input_cmdline) - ns.molname_in = None # TODO: arguments that exist only in the scope of optimization (useless for manual model evaluation) -- but this could be modified to be allowed to evaluate models in mixed membranes, averaging distribs for given molecule name only ns.gyr_aa_mapped, ns.gyr_aa_mapped_std = None, None # ns.sasa_aa_mapped, ns.sasa_aa_mapped_std = None, None @@ -126,24 +35,28 @@ def main(): # TODO: add missing checks -- if some are missing # TODO: factorize all checks and put them in global lib if not os.path.isfile(ns.aa_tpr_filename): - sys.exit(config.header_error+'Cannot find coordinate file of the atomistic simulation\n(GRO, PDB, or other trajectory formats supported by MDAnalysis)') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot find coordinate file of the atomistic simulation\n(GRO, PDB, or other trajectory formats supported by MDAnalysis)') if not os.path.isfile(ns.aa_traj_filename): - sys.exit(config.header_error+'Cannot find trajectory file of the atomistic simulation\n(XTC, TRR, or other trajectory formats supported by MDAnalysis)') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot find trajectory file of the atomistic simulation\n(XTC, TRR, or other trajectory formats supported by MDAnalysis)') if not os.path.isfile(ns.cg_map_filename): - sys.exit(config.header_error+'Cannot find CG beads mapping file (NDX-like file format)') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot find CG beads mapping file (NDX-like file format)') if not os.path.isfile(ns.cg_itp_filename): - sys.exit(config.header_error+'Cannot find ITP file of the CG model') + sys.exit(swarmcg.shared.styling.header_error + 'Cannot find ITP file of the CG model') # check bonds scaling arguments conflicts if (ns.bonds_scaling != config.bonds_scaling and ns.min_bonds_length != config.min_bonds_length) or (ns.bonds_scaling != config.bonds_scaling and ns.bonds_scaling_str != config.bonds_scaling_str) or (ns.min_bonds_length != config.min_bonds_length and ns.bonds_scaling_str != config.bonds_scaling_str): - sys.exit(config.header_error+'Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length can be provided\nPlease check your parameters') + sys.exit( + swarmcg.shared.styling.header_error + 'Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length can be provided\nPlease check your parameters') # if ns.bonds_scaling < 1: # sys.exit(config.header_error+'Bonds scaling factor is inferior to 1, please check your parameters') print() - print(config.sep_close) + print(swarmcg.shared.styling.sep_close) print('| PRE-PROCESSING |') - print(config.sep_close) + print(swarmcg.shared.styling.sep_close) print() # display parameters for function compare_models @@ -173,6 +86,127 @@ def main(): scg.compare_models(ns, manual_mode=True, calc_sasa=False) +if __name__ == '__main__': + + # command for tests + # ./evaluate_model.py -aa_tpr ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.tpr -aa_traj ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.xtc -cg_map ../DATA_MDL/Mono_B/MOB_atom_mapping/atomistic/MOB_mapping.ndx -cg_itp MOB_HUMAN_SIM/Mono_B.itp -cg_tpr MOB_HUMAN_SIM/cg_solvated.tpr -cg_traj MOB_HUMAN_SIM/cg_solvated.xtc + + # ./evaluate_model.py -aa_tpr ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.tpr -aa_traj ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.xtc -cg_map ../DATA_MDL/Mono_B/MOB_atom_mapping/atomistic/MOB_mapping.ndx -cg_itp MOB_HUMAN_SIM/Mono_B.itp + + # ./evaluate_model.py -aa_tpr ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/fake_for_test.tpr -aa_traj ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/ATOM_TRAJ.xtc -cg_map ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/index_bta.ndx -cg_itp BTA_HUMAN_SIM/bta_P3.itp -cg_tpr BTA_HUMAN_SIM/cg_solvated.tpr -cg_traj BTA_HUMAN_SIM/cg_solvated.xtc + + # ./evaluate_model.py -aa_tpr ../DATA_MDL/POPC/AA/topol.tpr -aa_traj ../DATA_MDL/POPC/AA/traj.trr -cg_map ../DATA_MDL/POPC/CG/mapping.ndx -cg_itp POPC_CG_SIM/martini_v2.0_POPC_02.itp -cg_tpr POPC_CG_SIM/cg_solvated.tpr -cg_traj POPC_CG_SIM/cg_solvated.xtc + + # ./evaluate_model.py -aa_tpr ../DATA_MDL/B3T/AA/topol.tpr -aa_traj ../DATA_MDL/B3T/AA/traj_atom.xtc -cg_map ../DATA_MDL/B3T/CG/MAPPING.ndx -cg_itp ../DATA_MDL/B3T/CG/MARTINI/B3T_CG.itp -cg_tpr B3T_HUMAN_SIM/produced.tpr -cg_traj B3T_HUMAN_SIM/produced.xtc + + print(swarmcg.shared.styling.header_package( + ' Module: Model bonded terms assessment\n')) + + formatter = lambda prog: RawTextHelpFormatter(prog, width=135, max_help_position=52) + args_parser = ArgumentParser( + description=EVALUATE_DESCR, + formatter_class=formatter, + add_help=False, + usage=SUPPRESS + ) + + all_args_header = swarmcg.shared.styling.sep_close + '\n| REQUIRED/OPTIONAL ARGUMENTS |\n' + swarmcg.shared.styling.sep_close + bullet = ' ' + + required_args = args_parser.add_argument_group( + all_args_header + '\n\n' + bullet + 'MODELS FILES') + required_args.add_argument('-aa_tpr', dest='aa_tpr_filename', help=config.help_aa_tpr, type=str, + default=config.metavar_aa_tpr, + metavar=' ' + scg.par_wrap(config.metavar_aa_tpr)) + required_args.add_argument('-aa_traj', dest='aa_traj_filename', help=config.help_aa_traj, + type=str, default=config.metavar_aa_traj, + metavar=' ' + scg.par_wrap(config.metavar_aa_traj)) + required_args.add_argument('-cg_map', dest='cg_map_filename', help=config.help_cg_map, type=str, + default=config.metavar_cg_map, + metavar=' ' + scg.par_wrap(config.metavar_cg_map)) + required_args.add_argument('-cg_itp', dest='cg_itp_filename', + help='ITP file of the CG model to evaluate', type=str, + default=config.metavar_cg_itp, + metavar=' ' + scg.par_wrap(config.metavar_cg_itp)) + required_args.add_argument('-cg_tpr', dest='cg_tpr_filename', + help='TPR file of your CG simulation (omit for solo AA inspection)', + type=str, default=config.metavar_cg_tpr, + metavar=' ' + scg.par_wrap(config.metavar_cg_tpr)) + required_args.add_argument('-cg_traj', dest='cg_traj_filename', + help='XTC file of your CG trajectory (omit for solo AA inspection)', + type=str, default=config.metavar_cg_traj, + metavar=' ' + scg.par_wrap(config.metavar_cg_traj)) + # required_args.add_argument('-figmolname', dest='figmolname', help='TODO REMOVE', type=str, required=True) # TODO: remove, this was just for figures + + optional_args = args_parser.add_argument_group(bullet + 'CG MODEL SCALING') + # optional_args.add_argument('-nb_threads', dest='nb_threads', help='number of threads to use', type=int, default=1, metavar='1') # TODO: does NOT work properly -- modif MDAnalysis code with OpenMP num_threads(n) in the pragma + optional_args.add_argument('-bonds_scaling', dest='bonds_scaling', + help=config.help_bonds_scaling, type=float, + default=config.bonds_scaling, + metavar=' ' + scg.par_wrap(config.bonds_scaling)) + optional_args.add_argument('-bonds_scaling_str', dest='bonds_scaling_str', + help=config.help_bonds_scaling_str, type=str, + default=config.bonds_scaling_str, metavar='') + optional_args.add_argument('-min_bonds_length', dest='min_bonds_length', + help=config.help_min_bonds_length, type=float, + default=config.min_bonds_length, + metavar=' ' + scg.par_wrap(config.min_bonds_length)) + optional_args.add_argument('-b2a_score_fact', dest='bonds2angles_scoring_factor', + help=config.help_bonds2angles_scoring_factor, type=float, + default=config.bonds2angles_scoring_factor, + metavar=' ' + scg.par_wrap(config.bonds2angles_scoring_factor)) + # ONLY FOR PAPER FIGURES + # optional_args.add_argument('-datamol', dest='datamol', help='Save bonded score and Rg values for each frame across simulation', type=str, default='MOL_EXEC_MODE') + graphical_args = args_parser.add_argument_group(bullet + 'FIGURE DISPLAY') + graphical_args.add_argument('-mismatch_ordering', dest='mismatch_order', + help='Enables ordering of bonds/angles/dihedrals by mismatch score\nbetween pairwise AA-mapped/CG distributions (can help diagnosis)', + default=False, action='store_true') + graphical_args.add_argument('-bw_constraints', dest='bw_constraints', + help=config.help_bw_constraints, type=float, + default=config.bw_constraints, + metavar=' ' + scg.par_wrap(config.bw_constraints)) + graphical_args.add_argument('-bw_bonds', dest='bw_bonds', help=config.help_bw_bonds, type=float, + default=config.bw_bonds, + metavar=' ' + scg.par_wrap(config.bw_bonds)) + graphical_args.add_argument('-bw_angles', dest='bw_angles', help=config.help_bw_angles, + type=float, default=config.bw_angles, + metavar=' ' + scg.par_wrap(config.bw_angles)) + graphical_args.add_argument('-bw_dihedrals', dest='bw_dihedrals', help=config.help_bw_dihedrals, + type=float, default=config.bw_dihedrals, + metavar=' ' + scg.par_wrap(config.bw_dihedrals)) + graphical_args.add_argument('-disable_x_scaling', dest='row_x_scaling', + help='Disable auto-scaling of X axis across each row of the plot', + default=True, action='store_false') + graphical_args.add_argument('-disable_y_scaling', dest='row_y_scaling', + help='Disable auto-scaling of Y axis across each row of the plot', + default=True, action='store_false') + graphical_args.add_argument('-bonds_max_range', dest='bonded_max_range', + help=config.help_bonds_max_range, type=float, + default=config.bonds_max_range, + metavar=' ' + scg.par_wrap(config.bonds_max_range)) + graphical_args.add_argument('-ncols', dest='ncols_max', + help='Max. nb of columns displayed in figure', type=int, default=0, + metavar='') # TODO: make this a line return in plot instead of ignoring groups + + optional_args2 = args_parser.add_argument_group(bullet + 'OTHERS') + optional_args2.add_argument('-o', dest='plot_filename', + help='Filename for the output plot (extension/format can be one of:\neps, pdf, pgf, png, ps, raw, rgba, svg, svgz)', + type=str, default='distributions.png', metavar='distributions.png') + optional_args2.add_argument('-h', '--help', action='help', + help='Show this help message and exit') + optional_args2.add_argument('-v', '--verbose', dest='verbose', help=config.help_verbose, + action='store_true', default=False) + # display help if script was called without arguments + if len(sys.argv) == 1: + args_parser.print_help() + sys.exit() + + # arguments handling, display command line if help or no arguments provided + ns = args_parser.parse_args() + input_cmdline = ' '.join(map(cmd_quote, sys.argv)) + print('Working directory:', os.getcwd()) + print('Command line:', input_cmdline) + main(ns) \ No newline at end of file diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index a950915..d3943af 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -1,5 +1,8 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings + +import swarmcg.shared.styling + warnings.filterwarnings("ignore") import os, sys, shutil, subprocess, time, copy, contextlib from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS @@ -9,657 +12,714 @@ from fstpso import FuzzyPSO import numpy as np -from . import config -from . import swarmCG as scg +from swarmcg import config +from swarmcg import swarmCG as scg +from swarmcg.shared.styling import OPTIMISE_DESCR warnings.resetwarnings() def main(): - from numpy import VisibleDeprecationWarning - warnings.filterwarnings("ignore", category=VisibleDeprecationWarning) # filter MDAnalysis + numpy deprecation stuff that is annoying + from numpy import VisibleDeprecationWarning + warnings.filterwarnings("ignore", category=VisibleDeprecationWarning) # filter MDAnalysis + numpy deprecation stuff that is annoying - # TODO: allow to feed a JSON file or DICT-like string for which bonds group to rescale for AA - # TODO: allow to feed a JSON file for cycles of optimization ?? this is more optional but useful for big stuff possibly - # TODO: if using SASA through GMX SASA, ensure vdwradii.dat contains the MARTINI radii - # TODO: give a warning when users specify a bond scaling without specifying an Rg offset !!! - - # TODO: AT OPTI CYCLE 2, FIND ANGLES THAT ARE TOO STEEP (CG) AND WHEN GENERATING THE NEW GUESSES, PUT 10-30-50-70% OF THE CURRENT BEST FORCE CONSTANT IN SEVERAL PARTICLES !!!!!!!!! - - # NOTE: gmx trjconv and sasa may produce bugs when using TPR produced with gromacs v5, only current solution seems to be implementing the SASA calculation using MDTraj - - - ##################################### - # ARGUMENTS HANDLING / HELP DISPLAY # - ##################################### - - print(scg.header_package(' Module: CG model optimization\n')) - - args_parser = ArgumentParser(description='''\ -This module automatically optimizes the bonded parameters of a CG model to best match the bonds, -angles and dihedrals distributions of a reference AA model. Different sets of bonded parameters -are explored via swarm optimization (FST-PSO) and iterative CG simulations. Bonded parameters are -evaluated for the matching they produce between AA and CG distributions via a scoring function -relying on the Earth Movers' Distance (EMD/Wasserstein). The process is designed to execute in -4-24h on a standard desktop machine, according to hardware, molecule size and simulations setup. - -This module has 2 optimization modes: - - (1) TUNE BOTH BONDS LENGTHS, ANGLES/DIHEDRALS VALUES AND THEIR FORCE CONSTANTS. First uses - Boltzmann Inversion to estimate bonds lengths, angles/dihedrals values and their force - constants, then runs optimization to best fit the reference AA-mapped distributions. - - (2) TUNE ONLY FORCE CONSTANTS FOR ANGLES/DIHEDRALS VALUES AND ALL PARAMETERS FOR BONDS. - Equilibrium values of angles/dihedrals provided in the preliminary CG ITP model are - conserved while optimization best fits reference AA-mapped distributions. - -Independently of parameters, the expected input is: - - (1) Atomistic trajectory of the molecule (gromacs binary TPR + trajectory files XTC TRR) - (2) Mapping file, atoms to CG beads (gromacs NDX format) - (3) CG model ITP file to be optimized (group identical bonds/angles/dihedrals, see below) - (4) CG simulation files (initial configuration GRO + system TOP + MDP files) - -You can prepare a directory using default input filenames, then provide only argument -in_dir. -If -in_dir is provided, all filenames provided as arguments will also be searched for within -this directory. Demonstration data are available at '''+config.github_url+'''. - -Arguments allows to specify scaling of the AA bonds used as reference to optimize the CG model. -An image displaying all AA reference distributions will be created at the very beginning of the -optimization process. You can check it to make sure scaling is conform to your expectations. - -The CG model preliminary ITP file follows the standard ITP format, with one subtlety. The file -can include groups of bonds, angles and dihedrals that will be considered identical. Their -distributions will be averaged within groups. This is important to obtain reliable results for -symmetrical molecules. Groups can be formed using empty line(s) or comment(s), like this: - - [ angles ] - - ; i j k funct angle force.c. - ; grp 1 - 5 6 10 1 150 40 ; NOTE 1: force constants can be set to 0 - 9 8 11 1 150 40 ; in the prelim. model to optimize - ; grp 2 - 1 6 10 2 120 0 ; NOTE 2: either comment(s) or empty line(s) - 4 8 11 2 120 0 ; separate groups of bonds/ang/dihe. - -The AA trajectory is mapped on-the-fly using file from argument -cg_map, which uses gromacs NDX -file format. Periodic boundary conditions are handled internally if the input AA trajectory -contains box dimensions.''', formatter_class=lambda prog: RawTextHelpFormatter(prog, width=135, max_help_position=52), add_help=False, usage=SUPPRESS) - - # TODO: handle trajectories for which no box informations are provided - # TODO: explain what is modified in the MDP - # TODO: explain module analyze_opti_moves.py can be used to monitor optimization at any point of the process - # TODO: end the help message by a new frame with examples from the demo data - - req_args_header = config.sep_close+'\n| REQUIRED ARGUMENTS |\n'+config.sep_close - opt_args_header = config.sep_close+'\n| OPTIONAL ARGUMENTS |\n'+config.sep_close - # bullet = '❭' - # bullet = '★' - # bullet = '|' - bullet = ' ' - - optional_args0 = args_parser.add_argument_group(req_args_header+'\n\n'+bullet+'EXECUTION MODE') - optional_args0.add_argument('-exec_mode', dest='exec_mode', help='MODE 1: Tune both bonds lengths, angles/dihedrals values\n and their force constants\nMODE 2: Like MODE 1 but angles/dihedrals values in the prelim.\n CG model ITP are conserved during optimization\nMODE 3: Like MODE 1 but only dihedrals values in the prelim.\n CG model ITP are conserved during optimization', type=int, default=1, metavar=' (1)') - - required_args = args_parser.add_argument_group(bullet+'REFERENCE AA MODEL') - required_args.add_argument('-aa_tpr', dest='aa_tpr_filename', help=config.help_aa_tpr, type=str, default=config.metavar_aa_tpr, metavar=' '+scg.par_wrap(config.metavar_aa_tpr)) - required_args.add_argument('-aa_traj', dest='aa_traj_filename', help=config.help_aa_traj, type=str, default=config.metavar_aa_traj, metavar=' '+scg.par_wrap(config.metavar_aa_traj)) - required_args.add_argument('-cg_map', dest='cg_map_filename', help=config.help_cg_map, type=str, default=config.metavar_cg_map, metavar=' '+scg.par_wrap(config.metavar_cg_map)) - - sim_filenames_args = args_parser.add_argument_group(bullet+'CG MODEL OPTIMIZATION') - sim_filenames_args.add_argument('-cg_itp', dest='cg_itp_filename', help='ITP file of the CG model to optimize', type=str, default=config.metavar_cg_itp, metavar=' '+scg.par_wrap(config.metavar_cg_itp)) - sim_filenames_args.add_argument('-cg_gro', dest='gro_input_filename', help='Starting GRO file used for iterative simulation\nWill be minimized and relaxed before each MD run', type=str, default='start_conf.gro', metavar=' (start_conf.gro)') - sim_filenames_args.add_argument('-cg_top', dest='top_input_filename', help='TOP file used for iterative simulation', type=str, default='system.top', metavar=' (system.top)') - sim_filenames_args.add_argument('-cg_mdp_mini', dest='mdp_minimization_filename', help='MDP file used for minimization runs', type=str, default='mini.mdp', metavar=' (mini.mdp)') - sim_filenames_args.add_argument('-cg_mdp_equi', dest='mdp_equi_filename', help='MDP file used for equilibration runs', type=str, default='equi.mdp', metavar=' (equi.mdp)') - sim_filenames_args.add_argument('-cg_mdp_md', dest='mdp_md_filename', help='MDP file used for the MD runs analyzed for optimization', type=str, default='md.mdp', metavar=' (md.mdp)') - - optional_args4 = args_parser.add_argument_group(opt_args_header+'\n\n'+bullet+'FILES HANDLING') - optional_args4.add_argument('-in_dir', dest='input_folder', help='Additional prefix path used to find argument-provided files\nIf ambiguous, files found without prefix are preferred', type=str, default='.', metavar='') - optional_args4.add_argument('-out_dir', dest='output_folder', help='Directory where to store all outputs of this program\nDefault -out_dir is named after timestamp', type=str, default='', metavar='') - - optional_args1 = args_parser.add_argument_group(bullet+'GROMACS SETTINGS') - optional_args1.add_argument('-gmx', dest='gmx_path', help=config.help_gmx_path, type=str, default=config.gmx_path, metavar=' '+scg.par_wrap(config.gmx_path)) - optional_args1.add_argument('-nt', dest='nb_threads', help='Number of threads to use, forwarded to gmx mdrun -nt', type=int, default=0, metavar=' (0)') - optional_args1.add_argument('-gpu_id', dest='gpu_id', help='String (use quotes) space-separated list of GPU device IDs', type=str, default='', metavar='') - optional_args1.add_argument('-gmx_args_str', dest='gmx_args_str', help='String (use quotes) of arguments to forward to gmx mdrun\nIf provided, arguments -nt and -gpu_id are ignored', type=str, default='', metavar='') - optional_args1.add_argument('-mini_maxwarn', dest='mini_maxwarn', help='Max. number of warnings to ignore, forwarded to gmx\ngrompp -maxwarn at each minimization step', type=int, default=1, metavar=' (1)') - optional_args1.add_argument('-sim_kill_delay', dest='sim_kill_delay', help='Time (s) after which to kill a simulation that has not been\nwriting into its log file, in case a simulation gets stuck', type=int, default=60, metavar=' (60)') - - optional_args2 = args_parser.add_argument_group(bullet+'CG MODEL SCALING') - optional_args2.add_argument('-aa_rg_offset', dest='aa_rg_offset', help='Radius of gyration offset (nm) to be applied to AA data\naccording to your potential bonds rescaling (for display only)', type=float, default=0.00, metavar=' '+scg.par_wrap('0.00')) - optional_args2.add_argument('-bonds_scaling', dest='bonds_scaling', help=config.help_bonds_scaling, type=float, default=config.bonds_scaling, metavar=' '+scg.par_wrap(config.bonds_scaling)) - optional_args2.add_argument('-bonds_scaling_str', dest='bonds_scaling_str', help=config.help_bonds_scaling_str, type=str, default=config.bonds_scaling_str, metavar='') - optional_args2.add_argument('-min_bonds_length', dest='min_bonds_length', help=config.help_min_bonds_length, type=float, default=config.min_bonds_length, metavar=' '+scg.par_wrap(config.min_bonds_length)) - - optional_args5 = args_parser.add_argument_group(bullet+'CG MODEL SCORING') - optional_args5.add_argument('-cg_time_short', dest='sim_duration_short', help='Simulation time (ns) of the MD runs analyzed for optimization\nIn opti. cycles 1 and 2, this will modify MDP file for the MD runs', type=float, default=10, metavar=' (10)') - optional_args5.add_argument('-cg_time_long', dest='sim_duration_long', help='Simulation time (ns) of the MD runs analyzed for optimization\nIn opti. cycle 3, this will modify MDP file for the MD runs', type=float, default=25, metavar=' (25)') - optional_args5.add_argument('-b2a_score_fact', dest='bonds2angles_scoring_factor', help=config.help_bonds2angles_scoring_factor, type=float, default=config.bonds2angles_scoring_factor, metavar=' '+scg.par_wrap(config.bonds2angles_scoring_factor)) - optional_args5.add_argument('-bw_constraints', dest='bw_constraints', help=config.help_bw_constraints, type=float, default=config.bw_constraints, metavar=' '+scg.par_wrap(config.bw_constraints)) - optional_args5.add_argument('-bw_bonds', dest='bw_bonds', help=config.help_bw_bonds, type=float, default=config.bw_bonds, metavar=' '+scg.par_wrap(config.bw_bonds)) - optional_args5.add_argument('-bw_angles', dest='bw_angles', help=config.help_bw_angles, type=float, default=config.bw_angles, metavar=' '+scg.par_wrap(config.bw_angles)) - optional_args5.add_argument('-bw_dihedrals', dest='bw_dihedrals', help=config.help_bw_dihedrals, type=float, default=config.bw_dihedrals, metavar=' '+scg.par_wrap(config.bw_dihedrals)) - optional_args5.add_argument('-bonds_max_range', dest='bonded_max_range', help=config.help_bonds_max_range, type=float, default=config.bonds_max_range, metavar=' '+scg.par_wrap(config.bonds_max_range)) - - optional_args6 = args_parser.add_argument_group(bullet+'CG MODEL FORCE CONSTANTS') - optional_args6.add_argument('-max_fct_bonds_f1', dest='default_max_fct_bonds_opti', help=config.help_max_fct_bonds, type=float, default=config.default_max_fct_bonds_opti, metavar=' '+scg.par_wrap(config.default_max_fct_bonds_opti)) - optional_args6.add_argument('-max_fct_angles_f1', dest='default_max_fct_angles_opti_f1', help=config.help_max_fct_angles_f1, type=float, default=config.default_max_fct_angles_opti_f1, metavar=' '+scg.par_wrap(config.default_max_fct_angles_opti_f1)) - optional_args6.add_argument('-max_fct_angles_f2', dest='default_max_fct_angles_opti_f2', help=config.help_max_fct_angles_f2, type=float, default=config.default_max_fct_angles_opti_f2, metavar=' '+scg.par_wrap(config.default_max_fct_angles_opti_f2)) - optional_args6.add_argument('-max_fct_dihedrals_f149', dest='default_abs_range_fct_dihedrals_opti_func_with_mult', help=config.help_max_fct_dihedrals_with_mult, type=float, default=config.default_abs_range_fct_dihedrals_opti_func_with_mult, metavar=''+scg.par_wrap(config.default_abs_range_fct_dihedrals_opti_func_with_mult)) - optional_args6.add_argument('-max_fct_dihedrals_f2', dest='default_max_fct_dihedrals_opti_func_without_mult', help=config.help_max_fct_dihedrals_without_mult, type=float, default=config.default_max_fct_dihedrals_opti_func_without_mult, metavar=''+scg.par_wrap(config.default_max_fct_dihedrals_opti_func_without_mult)) - - optional_args3 = args_parser.add_argument_group(bullet+'OTHERS') - optional_args3.add_argument('-temp', dest='temp', help='Temperature used to perform Boltzmann inversion (K)', type=float, default=config.sim_temperature, metavar=' '+scg.par_wrap(config.sim_temperature)) - optional_args3.add_argument('-keep_all_sims', dest='keep_all_sims', help='Store all gmx files for all simulations, may use disk space', action='store_true', default=False) - optional_args3.add_argument('-h', '--help', help='Show this help message and exit', action='help') - optional_args3.add_argument('-v', '--verbose', dest='verbose', help=config.help_verbose, action='store_true', default=False) - - # display help if script was called without arguments - if len(sys.argv) == 1: - args_parser.print_help() - sys.exit() - - # arguments handling, display command line if help or no arguments provided - # argcomplete.autocomplete(parser) - ns = args_parser.parse_args() - input_cmdline = ' '.join(map(cmd_quote, sys.argv)) - ns.exec_folder = time.strftime("MODEL_OPTI__STARTED_%d-%m-%Y_%Hh%Mm%Ss") # default folder name for all files of this optimization run, in case none is provided - if ns.output_folder != '': - ns.exec_folder = ns.output_folder - print('Working directory:', os.getcwd()) - print('Command line:', input_cmdline) - print('Results directory:', ns.exec_folder) - - # namespace variables not directly linked to arguments for plotting or for global package interpretation - ns.mismatch_order = False - ns.row_x_scaling = True - ns.row_y_scaling = True - ns.ncols_max = 0 # 0 to display all - # ns.atom_only = False - ns.molname_in = None # if None the first found using TPR atom ordering will be used - ns.process_alive_time_sleep = 10 # nb of seconds between process alive check cycles - ns.process_alive_nb_cycles_dead = int(ns.sim_kill_delay / ns.process_alive_time_sleep) # nb of cycles without .log file bytes size changes to determine that the MD run is stuck - ns.bonds_rescaling_performed = False # for user information display - - # get basenames for simulation files - ns.cg_itp_basename = os.path.basename(ns.cg_itp_filename) - ns.gro_input_basename = os.path.basename(ns.gro_input_filename) - ns.top_input_basename = os.path.basename(ns.top_input_filename) - ns.mdp_minimization_basename = os.path.basename(ns.mdp_minimization_filename) - ns.mdp_equi_basename = os.path.basename(ns.mdp_equi_filename) - ns.mdp_md_basename = os.path.basename(ns.mdp_md_filename) - - - #################### - # ARGUMENTS CHECKS # - #################### - - print() - print() - print(config.sep_close) - print('| PRE-PROCESSING AND CONTROLS |') - print(config.sep_close) - # print() - - # TODO: check that at least 10-20% of the simulations of the 1st swarm iteration finished properly, otherwise lower all energies or tell the user he is not writting into the log file regularly enough - # TODO: test this program with ITP files that contain all the different dihedral functions, angles functions, constraints etc - # TODO: find some fuzzy logic to determine number of swarm iterations + take some large margin to ensure it will optimize correctly - - # avoid overwriting an output directory of a previous optimization run - if os.path.isfile(ns.exec_folder) or os.path.isdir(ns.exec_folder): - sys.exit(config.header_error+'Provided output folder already exists, please delete existing folder manually or provide another folder name.') - - # check if we can find files at user-provided location(s) - arg_entries = vars(ns) # dict view of the arguments namespace - user_provided_filenames = ['aa_tpr_filename', 'aa_traj_filename', 'cg_map_filename', 'cg_itp_filename', 'gro_input_filename', 'top_input_filename', 'mdp_minimization_filename', 'mdp_equi_filename', 'mdp_md_filename'] - args_names = ['aa_tpr', 'aa_traj', 'cg_map', 'cg_itp', 'cg_sim_gro', 'cg_sim_top', 'cg_sim_mdp_mini', 'cg_sim_mdp_equi', 'cg_sim_mdp_md'] - - for i in range(len(user_provided_filenames)): - arg_entry = user_provided_filenames[i] - if not os.path.isfile(arg_entries[arg_entry]): - data_folder_path = ns.input_folder+'/'+arg_entries[arg_entry] - if ns.input_folder != '.' and os.path.isfile(data_folder_path): - arg_entries[arg_entry] = data_folder_path - else: - if ns.input_folder == '': - data_folder_path = arg_entries[arg_entry] - sys.exit(config.header_error+'Cannot find file for argument -'+args_names[i]+' (expected at location: '+data_folder_path+')') - - # check that gromacs alias is correct - with open(os.devnull, 'w') as devnull: - try: - subprocess.call(ns.gmx_path, stdout=devnull, stderr=devnull) - except OSError: - sys.exit(config.header_error+'Cannot find GROMACS using alias \''+ns.gmx_path+'\', please provide the right GROMACS alias or path') - - # check that ITP filename for the model to optimize is indeed included in the TOP file of the simulation directory - # then find all TOP includes for copying files for simulations at each iteration - top_includes_filenames = [] - with open(ns.top_input_filename, 'r') as fp: - all_top_lines = fp.read() - if ns.cg_itp_basename not in all_top_lines: - sys.exit(config.header_error+'The CG ITP model filename you provided is not included in your TOP file') - - top_lines = all_top_lines.split('\n') - top_lines = [top_line.strip().split(';')[0] for top_line in top_lines] # split for comments - for top_line in top_lines: - if top_line.startswith('#include'): - top_include = top_line.split()[1].replace('"', '').replace("'", '') # remove potential single and double quotes - top_includes_filenames.append(top_include) - # TODO: VERIFY THE PRESENCE OF ALLLLLLLLL TOP FILES, NOT ONLY THE CG MODEL'S + # TODO: allow to feed a JSON file or DICT-like string for which bonds group to rescale for AA + # TODO: allow to feed a JSON file for cycles of optimization ?? this is more optional but useful for big stuff possibly + # TODO: if using SASA through GMX SASA, ensure vdwradii.dat contains the MARTINI radii + # TODO: give a warning when users specify a bond scaling without specifying an Rg offset !!! - # check gmx arguments conflicts - if ns.gmx_args_str != '' and (ns.nb_threads != 0 or ns.gpu_id != ''): - print(config.header_warning+'Argument -gmx_args_str is provided together with one of arguments: -nb_threads, -gpu_id\nOnly argument -gmx_args_str will be used during this execution') - - # check bonds scaling arguments conflicts - if (ns.bonds_scaling != config.bonds_scaling and ns.min_bonds_length != config.min_bonds_length) or (ns.bonds_scaling != config.bonds_scaling and ns.bonds_scaling_str != config.bonds_scaling_str) or (ns.min_bonds_length != config.min_bonds_length and ns.bonds_scaling_str != config.bonds_scaling_str): - sys.exit(config.header_error+'Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length can be provided\nPlease check your parameters') - # if ns.bonds_scaling < 1: - # sys.exit(config.header_error+'Bonds scaling factor is inferior to 1, please check your parameters') - - - ################## - # INITIALIZATION # - ################## - - scg.set_MDA_backend(ns) - ns.mda_backend = 'serial' # clusters execution - - # directory to write all files for current execution of optimizations routines - os.mkdir(ns.exec_folder) - os.mkdir(ns.exec_folder+'/.internal') - os.mkdir(ns.exec_folder+'/'+config.distrib_plots_all_evals_dirname) - os.mkdir(ns.exec_folder+'/'+config.log_files_all_evals_dirname) - if ns.keep_all_sims: - os.mkdir(ns.exec_folder+'/'+config.sim_files_all_evals_dirname) - - # prepare a directory to be copied at each iteration of the optimization, to run the new simulation - os.mkdir(ns.exec_folder+'/'+config.input_sim_files_dirname) - user_provided_sim_files = ['cg_itp_filename', 'gro_input_filename', 'top_input_filename', 'mdp_minimization_filename', 'mdp_equi_filename', 'mdp_md_filename'] - - for sim_file in user_provided_sim_files: - shutil.copy(arg_entries[sim_file], ns.exec_folder+'/'+config.input_sim_files_dirname) - - # get all TOP file includes copied into input simulation directory - top_include_dirbase = os.path.dirname(arg_entries['top_input_filename']) - for top_include in top_includes_filenames: - # shutil.copy(top_include_dirbase+'/'+top_include, ns.exec_folder+'/'+config.input_sim_files_dirname) # PROBLEM LUCA - # shutil.copy(ns.input_folder+'/'+top_include_dirbase+'/'+top_include, ns.exec_folder+'/'+config.input_sim_files_dirname) # PROBLEM WITH PIP - - # print(ns.input_folder, top_include_dirbase, top_include) - shutil.copy(ns.input_folder+'/'+top_include, ns.exec_folder+'/'+config.input_sim_files_dirname) - - # modify the TOP file to adapt includes paths - with open(ns.exec_folder+'/'+config.input_sim_files_dirname+'/'+ns.top_input_basename, 'r') as fp: - all_top_lines = fp.read().split('\n') - with open(ns.exec_folder+'/'+config.input_sim_files_dirname+'/'+ns.top_input_basename, 'w+') as fp: - nb_includes = 0 - for i in range(len(all_top_lines)): - if all_top_lines[i].startswith('#include'): - all_top_lines[i] = '#include "'+os.path.basename(top_includes_filenames[nb_includes])+'"' - nb_includes += 1 - fp.writelines('\n'.join(all_top_lines)) - - ns.nb_eval = 0 # global count of evaluation steps - ns.start_opti_ts = datetime.now().timestamp() - ns.total_eval_time, ns.total_gmx_time, ns.total_model_eval_time = 0, 0, 0 - - scg.create_bins_and_dist_matrices(ns) # bins for EMD calculations - scg.read_ndx_atoms2beads(ns) # read mapping, get atoms accurences in beads - scg.get_atoms_weights_in_beads(ns) # get weights of atoms within beads - - print() - - # read starting CG ITP file - with open(ns.cg_itp_filename, 'r') as fp: - itp_lines = fp.read().split('\n') - itp_lines = [itp_line.strip() for itp_line in itp_lines] - scg.read_cg_itp_file(ns, itp_lines) # loads ITP object that contains our reference atomistic data -- won't ever be modified during execution - - # touch results files to be appended to later - with open(ns.exec_folder+'/'+config.opti_perf_recap_file, 'w') as fp: - # TODO: print that file has been generated with Swarm-CG etc -- do this for basically all files - # TODO: add some info on the opti cycles ?? - fp.write('# nb constraints: '+str(ns.nb_constraints)+'\n') - fp.write('# nb bonds: '+str(ns.nb_bonds)+'\n') - fp.write('# nb angles: '+str(ns.nb_angles)+'\n') - fp.write('# nb dihedrals: '+str(ns.nb_dihedrals)+'\n') - fp.write('#\n') - fp.write('# opti_cycle nb_eval fit_score_all fit_score_cstrs_bonds fit_score_angles fit_score_dihedrals eval_score Rg_AA_mapped Rg_CG parameters_set eval_time current_total_time\n') - with open(ns.exec_folder+'/'+config.opti_pairwise_distances_file, 'w'): - pass - - # process specific bonds scaling string, if provided - ns.bonds_scaling_specific = None - if ns.bonds_scaling_str != config.bonds_scaling_str: - sp_str = ns.bonds_scaling_str.split() - if len(sp_str) % 2 != 0: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nPlease check your parameters, or help for an example') - ns.bonds_scaling_specific = dict() - i = 0 - try: - while i < len(sp_str): - geom_id = sp_str[i][1:] - if sp_str[i][0].upper() == 'C': - if int(geom_id) > ns.nb_constraints: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA constraint group id exceeds the number of constraints groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') - if not 'C'+geom_id in ns.bonds_scaling_specific: - if float(sp_str[i+1]) < 0: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') - ns.bonds_scaling_specific['C'+geom_id] = float(sp_str[i+1]) - else: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA constraint group id is provided multiple times (id: '+str(geom_id)+')\nPlease check your parameters, or help for an example') - elif sp_str[i][0].upper() == 'B': - if int(geom_id) > ns.nb_bonds: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA bond group id exceeds the number of bonds groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') - if not 'B'+geom_id in ns.bonds_scaling_specific: - if float(sp_str[i+1]) < 0: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') - ns.bonds_scaling_specific['B'+geom_id] = float(sp_str[i+1]) - else: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA bond group id is provided multiple times (id: '+str(geom_id)+')\nPlease check your parameters, or help for an example') - i += 2 - except ValueError: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nPlease check your parameters, or help for an example') - - # read atom mapped trajectory + find domains boundaries for values ranges (NOT the force constants, for which it is config/user defined already) - print() - scg.read_aa_traj(ns) - scg.load_aa_data(ns) - scg.make_aa_traj_whole_for_selected_mols(ns) - - print('\nCalculating bonds, angles and dihedrals distributions for reference AA-mapped model') - - # for each CG bead, create atom groups for trajectory geoms calculation using mass and atom weights across beads - scg.get_beads_MDA_atomgroups(ns) - - ns.gyr_aa_mapped, ns.gyr_aa_mapped_std = None, None # will be computed one single time with model evaluation script - ns.sasa_aa_mapped, ns.sasa_aa_mapped_std = None, None # will be computed one single time with model evaluation script - - ns.domains_val = {'constraint': [], 'bond': [], 'angle': [], 'dihedral': []} - ns.data_BI = {'bond': [], 'angle': [], 'dihedral': []} # store hists for BI, std and possibly some other stats - - # create all ref atom histograms to be used for pairwise distributions comparisons + find average geoms values as first guesses (without BI at this point) - # get ref atom hists + find very first distances guesses for constraints groups - for grp_constraint in range(ns.nb_constraints): - - constraint_avg, constraint_hist, constraint_values = scg.get_AA_bonds_distrib(ns, beads_ids=ns.cg_itp['constraint'][grp_constraint]['beads'], grp_type='constraint group', grp_nb=grp_constraint) - # if ns.exec_mode == 1: - ns.cg_itp['constraint'][grp_constraint]['value'] = constraint_avg - ns.cg_itp['constraint'][grp_constraint]['avg'] = constraint_avg - ns.cg_itp['constraint'][grp_constraint]['hist'] = constraint_hist - - ns.domains_val['constraint'].append([round(np.min(constraint_values), 3), round(np.max(constraint_values), 3)]) - - # get ref atom hists + find very first distances and force constants guesses for bonds groups - for grp_bond in range(ns.nb_bonds): - - bond_avg, bond_hist, bond_values = scg.get_AA_bonds_distrib(ns, beads_ids=ns.cg_itp['bond'][grp_bond]['beads'], grp_type='bond group', grp_nb=grp_bond) - # if ns.exec_mode == 1: - ns.cg_itp['bond'][grp_bond]['value'] = bond_avg - ns.cg_itp['bond'][grp_bond]['avg'] = bond_avg - ns.cg_itp['bond'][grp_bond]['hist'] = bond_hist - - xmin, xmax = min(np.inf, ns.bins_bonds[np.min(np.nonzero(bond_hist))]), max(-np.inf, ns.bins_bonds[np.max(np.nonzero(bond_hist))+1]) - xmin, xmax = xmin-ns.bw_bonds, xmax+ns.bw_bonds - ns.data_BI['bond'].append([np.histogram(bond_values, range=(xmin, xmax), bins=config.bi_nb_bins)[0], np.std(bond_values), np.mean(bond_values), (xmin, xmax)]) - - ns.domains_val['bond'].append([round(np.min(bond_values), 3), round(np.max(bond_values), 3)]) # boundaries of force constats during optimization - - # get ref atom hists + find very first values and force constants guesses for angles groups - for grp_angle in range(ns.nb_angles): - - angle_avg, angle_hist, angle_values_deg, angle_values_rad = scg.get_AA_angles_distrib(ns, beads_ids=ns.cg_itp['angle'][grp_angle]['beads']) - if ns.exec_mode == 1 or ns.exec_mode == 3: - ns.cg_itp['angle'][grp_angle]['value'] = angle_avg - ns.cg_itp['angle'][grp_angle]['avg'] = angle_avg - ns.cg_itp['angle'][grp_angle]['hist'] = angle_hist - - xmin, xmax = min(np.inf, ns.bins_angles[np.min(np.nonzero(angle_hist))]), max(-np.inf, ns.bins_angles[np.max(np.nonzero(angle_hist))+1]) - xmin, xmax = xmin+ns.bw_angles/2, xmax-ns.bw_angles/2 - ns.data_BI['angle'].append([np.histogram(angle_values_rad, range=(np.deg2rad(xmin), np.deg2rad(xmax)), bins=config.bi_nb_bins)[0], np.std(angle_values_rad), (xmin, xmax)]) - - ns.domains_val['angle'].append([round(np.min(angle_values_deg), 2), round(np.max(angle_values_deg), 2)]) # boundaries of force constats during optimization - - # get ref atom hists + find very first values and force constants guesses for dihedrals groups - for grp_dihedral in range(ns.nb_dihedrals): - - dihedral_avg, dihedral_hist, dihedral_values_deg, dihedral_values_rad = scg.get_AA_dihedrals_distrib(ns, beads_ids=ns.cg_itp['dihedral'][grp_dihedral]['beads']) - if ns.exec_mode == 1: # the angle value for dihedral will be calculated from the BI fit, because for dihedrals it makes no sense to use the average - ns.cg_itp['dihedral'][grp_dihedral]['value'] = dihedral_avg - ns.cg_itp['dihedral'][grp_dihedral]['avg'] = dihedral_avg - ns.cg_itp['dihedral'][grp_dihedral]['hist'] = dihedral_hist - - xmin, xmax = -180, 180 - ns.data_BI['dihedral'].append([np.histogram(dihedral_values_rad, range=(np.deg2rad(xmin), np.deg2rad(xmax)), bins=2*config.bi_nb_bins)[0], np.std(dihedral_values_rad), np.mean(dihedral_values_rad), (xmin, xmax)]) - - ns.domains_val['dihedral'].append([round(np.min(dihedral_values_deg), 2), round(np.max(dihedral_values_deg), 2)]) # boundaries of force constats during optimization - - if not ns.bonds_rescaling_performed: - print(' No bonds rescaling performed') - - # output png with all the reference distributions, so the user can check - ns.atom_only = True - ns.plot_filename = ns.exec_folder+'/'+config.ref_distrib_plots - with open(os.devnull, 'w') as devnull: - with contextlib.redirect_stdout(devnull): - scg.compare_models(ns, manual_mode=False) - print() - print('Plotted reference AA-mapped distributions (used as target during optimization) at location:\n ', ns.exec_folder+'/'+config.ref_distrib_plots) - ns.atom_only = False - - - ################################## - # ITERATIVE OPTIMIZATION PROCESS # - ################################## - - # parameters for each type of simulation during optimization cycles - # sim duration (ns), max nb of SWARM iterations, max nb SWARM iterations without finding new global best, percentage applied for generating variations around initial guesses/values fed humanly - # sim_type 0 is used for initialization exclusively + detecting too high force constants to lower them, no real optimization is expected from these runs - - # Settings: TEST / utlra-fast settings only for debugging -- DIHEDRALS APPLIED IN THE END EXCLUSIVELY - # sim_types = {0: {'sim_duration': 0.3, 'max_swarm_iter': 1, 'max_swarm_iter_without_new_global_best': 1, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, - # 1: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, - # 2: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.2}, - # 3: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 0.4, 'fct_guess_fact': 0.1}} - # opti_cycles = [['constraint', 'bond', 'angle'], ['constraint', 'bond'], ['angle'], ['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects - # sim_cycles = [0, 1, 1, 2, 2, 3] # simulations types - - # Settings: TEST / utlra-fast settings only for debugging -- DIHEDRALS APPLIED IN THE END EXCLUSIVELY - # sim_types = {0: {'sim_duration': 0.3, 'max_swarm_iter': 1, 'max_swarm_iter_without_new_global_best': 1, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, - # 1: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, - # 2: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.2}, - # 3: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 0.4, 'fct_guess_fact': 0.1}} - # opti_cycles = [['constraint', 'bond', 'angle'], ['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects - # sim_cycles = [0, 2, 2, 3] # simulations types - - # Settings: ROBUST / Suited for big molecules - # sim_types = {0: {'sim_duration': 5, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 1, 'fct_guess_fact': 0.30}, - # 1: {'sim_duration': 8, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}, - # 2: {'sim_duration': 10, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}, - # 3: {'sim_duration': 15, 'max_swarm_iter': 20, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}} - # opti_cycles = [['constraint', 'bond', 'angle'], ['constraint', 'bond'], ['angle'], ['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects - # sim_cycles = [0, 1, 1, 3, 2, 3] # simulations types - - # Strategy 1 - # Settings: FASTER / Suited for small molecules or rapid optimization - # sim_types = {0: {'sim_duration': 10, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 1, 'fct_guess_fact': 0.40}, - # 1: {'sim_duration': 10, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, - # 2: {'sim_duration': 15, 'max_swarm_iter': 15, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}} - # opti_cycles = [['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects - # sim_cycles = [0, 1, 2] # simulations types - - # THIS IS THE CURRENT CHOICE - # Startegy 4 - # Settings: OPTIMAL / Should be fine with any type of molecule, big or small, as long as the BI keeps yielding close enough results, which should be the case - # sim_types = {0: {'sim_duration': 10, 'max_swarm_iter': int(5+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles)), 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 1, 'fct_guess_fact': 0.35}, - # 1: {'sim_duration': 10, 'max_swarm_iter': int(5+np.sqrt(ns.nb_angles+ns.nb_dihedrals)), 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, - # 2: {'sim_duration': 10, 'max_swarm_iter': int(5+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles+ns.nb_dihedrals)), 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.15, 'fct_guess_fact': 0.20}} - # opti_cycles = [['constraint', 'bond', 'angle'], ['angle', 'dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects - # sim_cycles = [0, 1, 2] # simulations types - - # Startegy 5 -- Coupled to fewer particles - # Settings: OPTIMAL / Should be fine with any type of molecule, big or small, as long as the BI keeps yielding close enough results, which should be the case - sim_types = {0: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': int(round(6+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles))), 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 1, 'fct_guess_fact': 0.40}, - 1: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': int(round(6+np.sqrt(ns.nb_angles+ns.nb_dihedrals))), 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, - 2: {'sim_duration': ns.sim_duration_long, 'max_swarm_iter': int(round(6+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles+ns.nb_dihedrals))), 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.20}} - opti_cycles = [['constraint', 'bond', 'angle'], ['angle', 'dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects - sim_cycles = [0, 1, 2] # simulations types - - # for tests - # sim_types = {0: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 1, 'fct_guess_fact': 0.40}, - # 1: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, - # 2: {'sim_duration': ns.sim_duration_long, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.20}} - # opti_cycles = [['constraint', 'bond', 'angle'], ['angle', 'dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects - # sim_cycles = [0, 1, 2] # simulations types - - # NOTE: currently, due to an issue in FST-PSO, number of swarm iterations performed is +2 when compared to the numbers we feed - - ns.opti_itp = copy.deepcopy(ns.cg_itp) # the ITP object that will be optimized stepwise, at the end of each optimization cycle (geom type wise) - ns.eval_nb_geoms = {'constraint': 0, 'bond': 0, 'angle': 0, 'dihedral': 0} # geoms to optimize at each step - - # remove dihedrals from cycles if CG ITP file does NOT contain dihedrals - if ns.nb_dihedrals == 0: - opti_cycles_cp, sim_cycles_cp = [], [] - nb_poped = 0 - for i in range(len(opti_cycles)): - opti_cycles_cp.extend([[]]) - for j in range(len(opti_cycles[i])): - if opti_cycles[i][j] != 'dihedral': - opti_cycles_cp[i-nb_poped].append(opti_cycles[i][j]) - if len(opti_cycles_cp[i-nb_poped]) == 0: - opti_cycles_cp.pop() - nb_poped += 1 - else: - sim_cycles_cp.extend([sim_cycles[i]]) - opti_cycles, sim_cycles = opti_cycles_cp, sim_cycles_cp - # print(opti_cycles) - - # state variables for the cycles of optimization - ns.performed_init_BI = {'bond': False, 'angle': False, 'dihedral': False} - ns.opti_geoms_all = set(geom for opti_cycle_geoms in opti_cycles for geom in opti_cycle_geoms) - ns.best_fitness = [np.inf, None] # fitness_score, eval_step_best_score - - # storage for best independent set of parameters by geom, for initialization of a (few ?) special particle after 1st opti cycle - ns.all_best_emd_dist_geoms = {'constraints': {}, 'bonds': {}, 'angles': {}, 'dihedrals': {}} - ns.all_best_params_dist_geoms = {'constraints': {}, 'bonds': {}, 'angles': {}, 'dihedrals': {}} - for i in range(ns.nb_constraints): - ns.all_best_emd_dist_geoms['constraints'][i] = config.sim_crash_EMD_indep_score - ns.all_best_params_dist_geoms['constraints'][i] = {} - for i in range(ns.nb_bonds): - ns.all_best_emd_dist_geoms['bonds'][i] = config.sim_crash_EMD_indep_score - ns.all_best_params_dist_geoms['bonds'][i] = {} - for i in range(ns.nb_angles): - ns.all_best_emd_dist_geoms['angles'][i] = config.sim_crash_EMD_indep_score - ns.all_best_params_dist_geoms['angles'][i] = {} - for i in range(ns.nb_dihedrals): - ns.all_best_emd_dist_geoms['dihedrals'][i] = config.sim_crash_EMD_indep_score - ns.all_best_params_dist_geoms['dihedrals'][i] = {} - - - ############################# - # START OPTIMIZATION CYCLES # - ############################# - - for i in range(len(opti_cycles)): - - ns.opti_cycle = {'nb_cycle': i+1, 'geoms': opti_cycles[i], 'nb_geoms': {'constraint': 0, 'bond': 0, 'angle': 0, 'dihedral': 0}} - ns.out_itp = copy.deepcopy(ns.opti_itp) # input ITP copy, on which we might perform BI, and that is the object we will modify at each evaluation step to store the values from FST-PSO - - # model selection based on fitness + Rg during last optimization cycle - # ns.all_rg_last_cycle, ns.all_fitness_last_cycle = np.array([]), np.array([]) - # ns.best_fitness_Rg_combined = 0 # id of the best model based on bonded fitness + Rg selection - - ns.prod_sim_time = sim_types[sim_cycles[i]]['sim_duration'] - ns.val_guess_fact = sim_types[sim_cycles[i]]['val_guess_fact'] - ns.fct_guess_fact = sim_types[sim_cycles[i]]['fct_guess_fact'] - ns.max_swarm_iter = sim_types[sim_cycles[i]]['max_swarm_iter'] - ns.max_swarm_iter_without_new_global_best = sim_types[sim_cycles[i]]['max_swarm_iter_without_new_global_best'] - - # adapt number of geoms according to the optimization cycle - geoms_display = [] - if 'constraint' in ns.opti_cycle['geoms'] or 'bond' in ns.opti_cycle['geoms']: - geoms_display.append('constraints/bonds') - if 'constraint' in ns.opti_cycle['geoms']: - ns.opti_cycle['nb_geoms']['constraint'] = ns.nb_constraints - if 'bond' in ns.opti_cycle['geoms']: - ns.opti_cycle['nb_geoms']['bond'] = ns.nb_bonds - if 'angle' in ns.opti_cycle['geoms']: - ns.opti_cycle['nb_geoms']['angle'] = ns.nb_angles - geoms_display.append('angles') - if 'dihedral' in ns.opti_cycle['geoms']: - ns.opti_cycle['nb_geoms']['dihedral'] = ns.nb_dihedrals - geoms_display.append('dihedrals') - geoms_display = ' & '.join(geoms_display) + # TODO: AT OPTI CYCLE 2, FIND ANGLES THAT ARE TOO STEEP (CG) AND WHEN GENERATING THE NEW GUESSES, PUT 10-30-50-70% OF THE CURRENT BEST FORCE CONSTANT IN SEVERAL PARTICLES !!!!!!!!! + + # NOTE: gmx trjconv and sasa may produce bugs when using TPR produced with gromacs v5, only current solution seems to be implementing the SASA calculation using MDTraj + + ##################################### + # ARGUMENTS HANDLING / HELP DISPLAY # + ##################################### + + # namespace variables not directly linked to arguments for plotting or for global package interpretation + ns.mismatch_order = False + ns.row_x_scaling = True + ns.row_y_scaling = True + ns.ncols_max = 0 # 0 to display all + # ns.atom_only = False + ns.molname_in = None # if None the first found using TPR atom ordering will be used + ns.process_alive_time_sleep = 10 # nb of seconds between process alive check cycles + ns.process_alive_nb_cycles_dead = int(ns.sim_kill_delay / ns.process_alive_time_sleep) # nb of cycles without .log file bytes size changes to determine that the MD run is stuck + ns.bonds_rescaling_performed = False # for user information display + + # get basenames for simulation files + ns.cg_itp_basename = os.path.basename(ns.cg_itp_filename) + ns.gro_input_basename = os.path.basename(ns.gro_input_filename) + ns.top_input_basename = os.path.basename(ns.top_input_filename) + ns.mdp_minimization_basename = os.path.basename(ns.mdp_minimization_filename) + ns.mdp_equi_basename = os.path.basename(ns.mdp_equi_filename) + ns.mdp_md_basename = os.path.basename(ns.mdp_md_filename) + + + #################### + # ARGUMENTS CHECKS # + #################### print() print() - print(config.sep_close) - print('| STARTING OPTIMIZATION CYCLE', ns.opti_cycle['nb_cycle'], ' |') - print('| Optimizing', geoms_display, ' '*(95-16-len(geoms_display)), '|') - print(config.sep_close) - - # actual BI to get the initial guesses of force constants, for all selected geoms at this given optimization step - # BI is performed: - # -- exec_mode 1: all values and force constants - # -- exec_mode 2: values are not touched for angles and dihedrals, but all force constants are estimated - # -- exec_mode 3: values are not touched for dihedrals, but all force constants are estimated - scg.perform_BI(ns) # performed on object ns.out_itp - - # build vector for search space boundaries + create variations around the BI initial guesses - search_space_boundaries = scg.get_search_space_boundaries(ns) - # ns.worst_fit_score = round(len(search_space_boundaries) * config.sim_crash_EMD_indep_score, 3) - ns.worst_fit_score = round(\ - np.sqrt((ns.nb_constraints+ns.nb_bonds) * config.sim_crash_EMD_indep_score) + \ - np.sqrt(ns.nb_angles * config.sim_crash_EMD_indep_score) + \ - np.sqrt(ns.nb_dihedrals * config.sim_crash_EMD_indep_score) \ - , 3) - # nb_particles = int(10 + 2*np.sqrt(len(search_space_boundaries))) # formula used by FST-PSO to choose nb of particles, which defines the number of initial guesses we can use - nb_particles = int(round(2 + np.sqrt(len(search_space_boundaries)))) # adapted to have less particles and fitted to our problems, which has good initial guesses and error driven initialization - # nb_particles = 2 # for tests - initial_guess_list = scg.get_initial_guess_list(ns, nb_particles) - - # actual optimization + print(swarmcg.shared.styling.sep_close) + print('| PRE-PROCESSING AND CONTROLS |') + print(swarmcg.shared.styling.sep_close) + # print() + + # TODO: check that at least 10-20% of the simulations of the 1st swarm iteration finished properly, otherwise lower all energies or tell the user he is not writting into the log file regularly enough + # TODO: test this program with ITP files that contain all the different dihedral functions, angles functions, constraints etc + # TODO: find some fuzzy logic to determine number of swarm iterations + take some large margin to ensure it will optimize correctly + + # avoid overwriting an output directory of a previous optimization run + if os.path.isfile(ns.exec_folder) or os.path.isdir(ns.exec_folder): + sys.exit( + swarmcg.shared.styling.header_error + 'Provided output folder already exists, please delete existing folder manually or provide another folder name.' + ) + + # check if we can find files at user-provided location(s) + arg_entries = vars(ns) # dict view of the arguments namespace + user_provided_filenames = ['aa_tpr_filename', 'aa_traj_filename', 'cg_map_filename', 'cg_itp_filename', 'gro_input_filename', 'top_input_filename', 'mdp_minimization_filename', 'mdp_equi_filename', 'mdp_md_filename'] + args_names = ['aa_tpr', 'aa_traj', 'cg_map', 'cg_itp', 'cg_sim_gro', 'cg_sim_top', 'cg_sim_mdp_mini', 'cg_sim_mdp_equi', 'cg_sim_mdp_md'] + + for i in range(len(user_provided_filenames)): + arg_entry = user_provided_filenames[i] + if not os.path.isfile(arg_entries[arg_entry]): + data_folder_path = ns.input_folder+'/'+arg_entries[arg_entry] + if ns.input_folder != '.' and os.path.isfile(data_folder_path): + arg_entries[arg_entry] = data_folder_path + else: + if ns.input_folder == '': + data_folder_path = arg_entries[arg_entry] + sys.exit(swarmcg.shared.styling.header_error + 'Cannot find file for argument -' + args_names[i] + ' (expected at location: ' + data_folder_path + ')') + + # check that gromacs alias is correct with open(os.devnull, 'w') as devnull: - with contextlib.redirect_stdout(devnull): - FP = FuzzyPSO() - FP.set_search_space(search_space_boundaries) - FP.set_swarm_size(nb_particles) - FP.set_fitness(fitness=scg.eval_function, arguments=ns, skip_test=True) - result = FP.solve_with_fstpso(max_iter=ns.max_swarm_iter, initial_guess_list=initial_guess_list, max_iter_without_new_global_best=ns.max_swarm_iter_without_new_global_best) - - # update ITP object with the best solution using geoms considered at this given optimization step - scg.update_cg_itp_obj(ns, parameters_set=result[0].X, update_type=2) - - # clean temporary copied directory with user's input files - shutil.rmtree(ns.exec_folder+'/'+config.input_sim_files_dirname) - - # print some stats - total_time_sec = datetime.now().timestamp() - ns.start_opti_ts - total_time = round(total_time_sec / (60 * 60), 2) - fitness_eval_time = round(ns.total_eval_time / (60 * 60), 2) - init_time = round((total_time_sec - ns.total_eval_time) / (60 * 60), 2) - ns.total_gmx_time = round(ns.total_gmx_time / (60 * 60), 2) - ns.total_model_eval_time = round(ns.total_model_eval_time / (60 * 60), 2) - print() - print(config.sep_close) - print('| FINISHED PROPERLY |') - print(config.sep_close) - print() - print('Total nb of evaluation steps:', ns.nb_eval) - print('Best model obtained at evaluation step number:', ns.best_fitness[1]) - print() - print('Total execution time :', total_time, 'h') - print('Initialization time :', init_time, 'h ('+str(round(init_time/total_time*100, 2))+' %)') - print('Simulations time :', ns.total_gmx_time, 'h ('+str(round(ns.total_gmx_time/total_time*100, 2))+' %)') - print('Models scoring time :', ns.total_model_eval_time, 'h ('+str(round(ns.total_model_eval_time/total_time*100, 2))+' %)') - print() + try: + subprocess.call(ns.gmx_path, stdout=devnull, stderr=devnull) + except OSError: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot find GROMACS using alias \'' + ns.gmx_path + '\', please provide the right GROMACS alias or path') + + # check that ITP filename for the model to optimize is indeed included in the TOP file of the simulation directory + # then find all TOP includes for copying files for simulations at each iteration + top_includes_filenames = [] + with open(ns.top_input_filename, 'r') as fp: + all_top_lines = fp.read() + if ns.cg_itp_basename not in all_top_lines: + sys.exit( + swarmcg.shared.styling.header_error + 'The CG ITP model filename you provided is not included in your TOP file') + + top_lines = all_top_lines.split('\n') + top_lines = [top_line.strip().split(';')[0] for top_line in top_lines] # split for comments + for top_line in top_lines: + if top_line.startswith('#include'): + top_include = top_line.split()[1].replace('"', '').replace("'", '') # remove potential single and double quotes + top_includes_filenames.append(top_include) + # TODO: VERIFY THE PRESENCE OF ALLLLLLLLL TOP FILES, NOT ONLY THE CG MODEL'S + + # check gmx arguments conflicts + if ns.gmx_args_str != '' and (ns.nb_threads != 0 or ns.gpu_id != ''): + print( + swarmcg.shared.styling.header_warning + 'Argument -gmx_args_str is provided together with one of arguments: -nb_threads, -gpu_id\nOnly argument -gmx_args_str will be used during this execution') + + # check bonds scaling arguments conflicts + if (ns.bonds_scaling != config.bonds_scaling and ns.min_bonds_length != config.min_bonds_length) or (ns.bonds_scaling != config.bonds_scaling and ns.bonds_scaling_str != config.bonds_scaling_str) or (ns.min_bonds_length != config.min_bonds_length and ns.bonds_scaling_str != config.bonds_scaling_str): + sys.exit( + swarmcg.shared.styling.header_error + 'Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length can be provided\nPlease check your parameters') + # if ns.bonds_scaling < 1: + # sys.exit(config.header_error+'Bonds scaling factor is inferior to 1, please check your parameters') + + ################## + # INITIALIZATION # + ################## + + scg.set_MDA_backend(ns) + ns.mda_backend = 'serial' # clusters execution + + # directory to write all files for current execution of optimizations routines + os.mkdir(ns.exec_folder) + os.mkdir(ns.exec_folder+'/.internal') + os.mkdir(ns.exec_folder+'/'+config.distrib_plots_all_evals_dirname) + os.mkdir(ns.exec_folder+'/'+config.log_files_all_evals_dirname) + if ns.keep_all_sims: + os.mkdir(ns.exec_folder+'/'+config.sim_files_all_evals_dirname) + + # prepare a directory to be copied at each iteration of the optimization, to run the new simulation + os.mkdir(ns.exec_folder+'/'+config.input_sim_files_dirname) + user_provided_sim_files = ['cg_itp_filename', 'gro_input_filename', 'top_input_filename', 'mdp_minimization_filename', 'mdp_equi_filename', 'mdp_md_filename'] + + for sim_file in user_provided_sim_files: + shutil.copy(arg_entries[sim_file], ns.exec_folder+'/'+config.input_sim_files_dirname) + + # get all TOP file includes copied into input simulation directory + for top_include in top_includes_filenames: + shutil.copy(ns.input_folder+'/'+top_include, ns.exec_folder+'/'+config.input_sim_files_dirname) + + # modify the TOP file to adapt includes paths + with open(ns.exec_folder+'/'+config.input_sim_files_dirname+'/'+ns.top_input_basename, 'r') as fp: + all_top_lines = fp.read().split('\n') + with open(ns.exec_folder+'/'+config.input_sim_files_dirname+'/'+ns.top_input_basename, 'w+') as fp: + nb_includes = 0 + for i in range(len(all_top_lines)): + if all_top_lines[i].startswith('#include'): + all_top_lines[i] = '#include "'+os.path.basename(top_includes_filenames[nb_includes])+'"' + nb_includes += 1 + fp.writelines('\n'.join(all_top_lines)) + + ns.nb_eval = 0 # global count of evaluation steps + ns.start_opti_ts = datetime.now().timestamp() + ns.total_eval_time, ns.total_gmx_time, ns.total_model_eval_time = 0, 0, 0 + + scg.create_bins_and_dist_matrices(ns) # bins for EMD calculations + scg.read_ndx_atoms2beads(ns) # read mapping, get atoms accurences in beads + scg.get_atoms_weights_in_beads(ns) # get weights of atoms within beads + + print() + + # read starting CG ITP file + with open(ns.cg_itp_filename, 'r') as fp: + itp_lines = fp.read().split('\n') + itp_lines = [itp_line.strip() for itp_line in itp_lines] + scg.read_cg_itp_file(ns, itp_lines) # loads ITP object that contains our reference atomistic data -- won't ever be modified during execution + + # touch results files to be appended to later + with open(ns.exec_folder+'/'+config.opti_perf_recap_file, 'w') as fp: + # TODO: print that file has been generated with Swarm-CG etc -- do this for basically all files + # TODO: add some info on the opti cycles ?? + fp.write('# nb constraints: '+str(ns.nb_constraints)+'\n') + fp.write('# nb bonds: '+str(ns.nb_bonds)+'\n') + fp.write('# nb angles: '+str(ns.nb_angles)+'\n') + fp.write('# nb dihedrals: '+str(ns.nb_dihedrals)+'\n') + fp.write('#\n') + fp.write('# opti_cycle nb_eval fit_score_all fit_score_cstrs_bonds fit_score_angles fit_score_dihedrals eval_score Rg_AA_mapped Rg_CG parameters_set eval_time current_total_time\n') + with open(ns.exec_folder+'/'+config.opti_pairwise_distances_file, 'w'): + pass + + # process specific bonds scaling string, if provided + ns.bonds_scaling_specific = None + if ns.bonds_scaling_str != config.bonds_scaling_str: + sp_str = ns.bonds_scaling_str.split() + if len(sp_str) % 2 != 0: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') + ns.bonds_scaling_specific = dict() + i = 0 + try: + while i < len(sp_str): + geom_id = sp_str[i][1:] + if sp_str[i][0].upper() == 'C': + if int(geom_id) > ns.nb_constraints: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id exceeds the number of constraints groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') + if not 'C'+geom_id in ns.bonds_scaling_specific: + if float(sp_str[i+1]) < 0: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') + ns.bonds_scaling_specific['C'+geom_id] = float(sp_str[i+1]) + else: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') + elif sp_str[i][0].upper() == 'B': + if int(geom_id) > ns.nb_bonds: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id exceeds the number of bonds groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') + if not 'B'+geom_id in ns.bonds_scaling_specific: + if float(sp_str[i+1]) < 0: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') + ns.bonds_scaling_specific['B'+geom_id] = float(sp_str[i+1]) + else: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') + i += 2 + except ValueError: + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') + + # read atom mapped trajectory + find domains boundaries for values ranges (NOT the force constants, for which it is config/user defined already) + print() + scg.read_aa_traj(ns) + scg.load_aa_data(ns) + scg.make_aa_traj_whole_for_selected_mols(ns) + + print('\nCalculating bonds, angles and dihedrals distributions for reference AA-mapped model') + + # for each CG bead, create atom groups for trajectory geoms calculation using mass and atom weights across beads + scg.get_beads_MDA_atomgroups(ns) + + ns.gyr_aa_mapped, ns.gyr_aa_mapped_std = None, None # will be computed one single time with model evaluation script + ns.sasa_aa_mapped, ns.sasa_aa_mapped_std = None, None # will be computed one single time with model evaluation script + + ns.domains_val = {'constraint': [], 'bond': [], 'angle': [], 'dihedral': []} + ns.data_BI = {'bond': [], 'angle': [], 'dihedral': []} # store hists for BI, std and possibly some other stats + + # create all ref atom histograms to be used for pairwise distributions comparisons + find average geoms values as first guesses (without BI at this point) + # get ref atom hists + find very first distances guesses for constraints groups + for grp_constraint in range(ns.nb_constraints): + constraint_avg, constraint_hist, constraint_values = scg.get_AA_bonds_distrib(ns, beads_ids=ns.cg_itp['constraint'][grp_constraint]['beads'], grp_type='constraint group', grp_nb=grp_constraint) + # if ns.exec_mode == 1: + ns.cg_itp['constraint'][grp_constraint]['value'] = constraint_avg + ns.cg_itp['constraint'][grp_constraint]['avg'] = constraint_avg + ns.cg_itp['constraint'][grp_constraint]['hist'] = constraint_hist + ns.domains_val['constraint'].append([round(np.min(constraint_values), 3), round(np.max(constraint_values), 3)]) + + # get ref atom hists + find very first distances and force constants guesses for bonds groups + for grp_bond in range(ns.nb_bonds): + + bond_avg, bond_hist, bond_values = scg.get_AA_bonds_distrib(ns, beads_ids=ns.cg_itp['bond'][grp_bond]['beads'], grp_type='bond group', grp_nb=grp_bond) + # if ns.exec_mode == 1: + ns.cg_itp['bond'][grp_bond]['value'] = bond_avg + ns.cg_itp['bond'][grp_bond]['avg'] = bond_avg + ns.cg_itp['bond'][grp_bond]['hist'] = bond_hist + + xmin, xmax = min(np.inf, ns.bins_bonds[np.min(np.nonzero(bond_hist))]), max(-np.inf, ns.bins_bonds[np.max(np.nonzero(bond_hist))+1]) + xmin, xmax = xmin-ns.bw_bonds, xmax+ns.bw_bonds + ns.data_BI['bond'].append([np.histogram(bond_values, range=(xmin, xmax), bins=config.bi_nb_bins)[0], np.std(bond_values), np.mean(bond_values), (xmin, xmax)]) + + ns.domains_val['bond'].append([round(np.min(bond_values), 3), round(np.max(bond_values), 3)]) # boundaries of force constats during optimization + + # get ref atom hists + find very first values and force constants guesses for angles groups + for grp_angle in range(ns.nb_angles): + + angle_avg, angle_hist, angle_values_deg, angle_values_rad = scg.get_AA_angles_distrib(ns, beads_ids=ns.cg_itp['angle'][grp_angle]['beads']) + if ns.exec_mode == 1 or ns.exec_mode == 3: + ns.cg_itp['angle'][grp_angle]['value'] = angle_avg + ns.cg_itp['angle'][grp_angle]['avg'] = angle_avg + ns.cg_itp['angle'][grp_angle]['hist'] = angle_hist + + xmin, xmax = min(np.inf, ns.bins_angles[np.min(np.nonzero(angle_hist))]), max(-np.inf, ns.bins_angles[np.max(np.nonzero(angle_hist))+1]) + xmin, xmax = xmin+ns.bw_angles/2, xmax-ns.bw_angles/2 + ns.data_BI['angle'].append([np.histogram(angle_values_rad, range=(np.deg2rad(xmin), np.deg2rad(xmax)), bins=config.bi_nb_bins)[0], np.std(angle_values_rad), (xmin, xmax)]) + + ns.domains_val['angle'].append([round(np.min(angle_values_deg), 2), round(np.max(angle_values_deg), 2)]) # boundaries of force constats during optimization + + # get ref atom hists + find very first values and force constants guesses for dihedrals groups + for grp_dihedral in range(ns.nb_dihedrals): + + dihedral_avg, dihedral_hist, dihedral_values_deg, dihedral_values_rad = scg.get_AA_dihedrals_distrib(ns, beads_ids=ns.cg_itp['dihedral'][grp_dihedral]['beads']) + if ns.exec_mode == 1: # the angle value for dihedral will be calculated from the BI fit, because for dihedrals it makes no sense to use the average + ns.cg_itp['dihedral'][grp_dihedral]['value'] = dihedral_avg + ns.cg_itp['dihedral'][grp_dihedral]['avg'] = dihedral_avg + ns.cg_itp['dihedral'][grp_dihedral]['hist'] = dihedral_hist + + xmin, xmax = -180, 180 + ns.data_BI['dihedral'].append([np.histogram(dihedral_values_rad, range=(np.deg2rad(xmin), np.deg2rad(xmax)), bins=2*config.bi_nb_bins)[0], np.std(dihedral_values_rad), np.mean(dihedral_values_rad), (xmin, xmax)]) + + ns.domains_val['dihedral'].append([round(np.min(dihedral_values_deg), 2), round(np.max(dihedral_values_deg), 2)]) # boundaries of force constats during optimization + + if not ns.bonds_rescaling_performed: + print(' No bonds rescaling performed') + + # output png with all the reference distributions, so the user can check + ns.atom_only = True + ns.plot_filename = ns.exec_folder+'/'+config.ref_distrib_plots + with open(os.devnull, 'w') as devnull: + with contextlib.redirect_stdout(devnull): + scg.compare_models(ns, manual_mode=False) + print() + print('Plotted reference AA-mapped distributions (used as target during optimization) at location:\n ', ns.exec_folder+'/'+config.ref_distrib_plots) + ns.atom_only = False + + + ################################## + # ITERATIVE OPTIMIZATION PROCESS # + ################################## + + # parameters for each type of simulation during optimization cycles + # sim duration (ns), max nb of SWARM iterations, max nb SWARM iterations without finding new global best, percentage applied for generating variations around initial guesses/values fed humanly + # sim_type 0 is used for initialization exclusively + detecting too high force constants to lower them, no real optimization is expected from these runs + + # Settings: TEST / utlra-fast settings only for debugging -- DIHEDRALS APPLIED IN THE END EXCLUSIVELY + # sim_types = {0: {'sim_duration': 0.3, 'max_swarm_iter': 1, 'max_swarm_iter_without_new_global_best': 1, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, + # 1: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, + # 2: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.2}, + # 3: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 0.4, 'fct_guess_fact': 0.1}} + # opti_cycles = [['constraint', 'bond', 'angle'], ['constraint', 'bond'], ['angle'], ['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects + # sim_cycles = [0, 1, 1, 2, 2, 3] # simulations types + + # Settings: TEST / utlra-fast settings only for debugging -- DIHEDRALS APPLIED IN THE END EXCLUSIVELY + # sim_types = {0: {'sim_duration': 0.3, 'max_swarm_iter': 1, 'max_swarm_iter_without_new_global_best': 1, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, + # 1: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.3}, + # 2: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 1.0, 'fct_guess_fact': 0.2}, + # 3: {'sim_duration': 0.3, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 2, 'val_guess_fact': 0.4, 'fct_guess_fact': 0.1}} + # opti_cycles = [['constraint', 'bond', 'angle'], ['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects + # sim_cycles = [0, 2, 2, 3] # simulations types + + # Settings: ROBUST / Suited for big molecules + # sim_types = {0: {'sim_duration': 5, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 1, 'fct_guess_fact': 0.30}, + # 1: {'sim_duration': 8, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}, + # 2: {'sim_duration': 10, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}, + # 3: {'sim_duration': 15, 'max_swarm_iter': 20, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}} + # opti_cycles = [['constraint', 'bond', 'angle'], ['constraint', 'bond'], ['angle'], ['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects + # sim_cycles = [0, 1, 1, 3, 2, 3] # simulations types + + # Strategy 1 + # Settings: FASTER / Suited for small molecules or rapid optimization + # sim_types = {0: {'sim_duration': 10, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 1, 'fct_guess_fact': 0.40}, + # 1: {'sim_duration': 10, 'max_swarm_iter': 10, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, + # 2: {'sim_duration': 15, 'max_swarm_iter': 15, 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.25}} + # opti_cycles = [['constraint', 'bond', 'angle'], ['dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects + # sim_cycles = [0, 1, 2] # simulations types + + # THIS IS THE CURRENT CHOICE + # Startegy 4 + # Settings: OPTIMAL / Should be fine with any type of molecule, big or small, as long as the BI keeps yielding close enough results, which should be the case + # sim_types = {0: {'sim_duration': 10, 'max_swarm_iter': int(5+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles)), 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 1, 'fct_guess_fact': 0.35}, + # 1: {'sim_duration': 10, 'max_swarm_iter': int(5+np.sqrt(ns.nb_angles+ns.nb_dihedrals)), 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, + # 2: {'sim_duration': 10, 'max_swarm_iter': int(5+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles+ns.nb_dihedrals)), 'max_swarm_iter_without_new_global_best': 5, 'val_guess_fact': 0.15, 'fct_guess_fact': 0.20}} + # opti_cycles = [['constraint', 'bond', 'angle'], ['angle', 'dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects + # sim_cycles = [0, 1, 2] # simulations types + + # Startegy 5 -- Coupled to fewer particles + # Settings: OPTIMAL / Should be fine with any type of molecule, big or small, as long as the BI keeps yielding close enough results, which should be the case + sim_types = {0: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': int(round(6+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles))), 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 1, 'fct_guess_fact': 0.40}, + 1: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': int(round(6+np.sqrt(ns.nb_angles+ns.nb_dihedrals))), 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, + 2: {'sim_duration': ns.sim_duration_long, 'max_swarm_iter': int(round(6+np.sqrt(ns.nb_constraints+ns.nb_bonds+ns.nb_angles+ns.nb_dihedrals))), 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.20}} + opti_cycles = [['constraint', 'bond', 'angle'], ['angle', 'dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects + sim_cycles = [0, 1, 2] # simulations types + + # for tests + # sim_types = {0: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 1, 'fct_guess_fact': 0.40}, + # 1: {'sim_duration': ns.sim_duration_short, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.30}, + # 2: {'sim_duration': ns.sim_duration_long, 'max_swarm_iter': 2, 'max_swarm_iter_without_new_global_best': 6, 'val_guess_fact': 0.25, 'fct_guess_fact': 0.20}} + # opti_cycles = [['constraint', 'bond', 'angle'], ['angle', 'dihedral'], ['constraint', 'bond', 'angle', 'dihedral']] # optimization cycles to perform with given geom objects + # sim_cycles = [0, 1, 2] # simulations types + + # NOTE: currently, due to an issue in FST-PSO, number of swarm iterations performed is +2 when compared to the numbers we feed + + ns.opti_itp = copy.deepcopy(ns.cg_itp) # the ITP object that will be optimized stepwise, at the end of each optimization cycle (geom type wise) + ns.eval_nb_geoms = {'constraint': 0, 'bond': 0, 'angle': 0, 'dihedral': 0} # geoms to optimize at each step + + # remove dihedrals from cycles if CG ITP file does NOT contain dihedrals + if ns.nb_dihedrals == 0: + opti_cycles_cp, sim_cycles_cp = [], [] + nb_poped = 0 + for i in range(len(opti_cycles)): + opti_cycles_cp.extend([[]]) + for j in range(len(opti_cycles[i])): + if opti_cycles[i][j] != 'dihedral': + opti_cycles_cp[i-nb_poped].append(opti_cycles[i][j]) + if len(opti_cycles_cp[i-nb_poped]) == 0: + opti_cycles_cp.pop() + nb_poped += 1 + else: + sim_cycles_cp.extend([sim_cycles[i]]) + opti_cycles, sim_cycles = opti_cycles_cp, sim_cycles_cp + + # state variables for the cycles of optimization + ns.performed_init_BI = {'bond': False, 'angle': False, 'dihedral': False} + ns.opti_geoms_all = set(geom for opti_cycle_geoms in opti_cycles for geom in opti_cycle_geoms) + ns.best_fitness = [np.inf, None] # fitness_score, eval_step_best_score + + # storage for best independent set of parameters by geom, for initialization of a (few ?) special particle after 1st opti cycle + ns.all_best_emd_dist_geoms = {'constraints': {}, 'bonds': {}, 'angles': {}, 'dihedrals': {}} + ns.all_best_params_dist_geoms = {'constraints': {}, 'bonds': {}, 'angles': {}, 'dihedrals': {}} + for i in range(ns.nb_constraints): + ns.all_best_emd_dist_geoms['constraints'][i] = config.sim_crash_EMD_indep_score + ns.all_best_params_dist_geoms['constraints'][i] = {} + for i in range(ns.nb_bonds): + ns.all_best_emd_dist_geoms['bonds'][i] = config.sim_crash_EMD_indep_score + ns.all_best_params_dist_geoms['bonds'][i] = {} + for i in range(ns.nb_angles): + ns.all_best_emd_dist_geoms['angles'][i] = config.sim_crash_EMD_indep_score + ns.all_best_params_dist_geoms['angles'][i] = {} + for i in range(ns.nb_dihedrals): + ns.all_best_emd_dist_geoms['dihedrals'][i] = config.sim_crash_EMD_indep_score + ns.all_best_params_dist_geoms['dihedrals'][i] = {} + + ############################# + # START OPTIMIZATION CYCLES # + ############################# + + for i in range(len(opti_cycles)): + + ns.opti_cycle = {'nb_cycle': i+1, 'geoms': opti_cycles[i], 'nb_geoms': {'constraint': 0, 'bond': 0, 'angle': 0, 'dihedral': 0}} + ns.out_itp = copy.deepcopy(ns.opti_itp) # input ITP copy, on which we might perform BI, and that is the object we will modify at each evaluation step to store the values from FST-PSO + + # model selection based on fitness + Rg during last optimization cycle + # ns.all_rg_last_cycle, ns.all_fitness_last_cycle = np.array([]), np.array([]) + # ns.best_fitness_Rg_combined = 0 # id of the best model based on bonded fitness + Rg selection + + ns.prod_sim_time = sim_types[sim_cycles[i]]['sim_duration'] + ns.val_guess_fact = sim_types[sim_cycles[i]]['val_guess_fact'] + ns.fct_guess_fact = sim_types[sim_cycles[i]]['fct_guess_fact'] + ns.max_swarm_iter = sim_types[sim_cycles[i]]['max_swarm_iter'] + ns.max_swarm_iter_without_new_global_best = sim_types[sim_cycles[i]]['max_swarm_iter_without_new_global_best'] + + # adapt number of geoms according to the optimization cycle + geoms_display = [] + if 'constraint' in ns.opti_cycle['geoms'] or 'bond' in ns.opti_cycle['geoms']: + geoms_display.append('constraints/bonds') + if 'constraint' in ns.opti_cycle['geoms']: + ns.opti_cycle['nb_geoms']['constraint'] = ns.nb_constraints + if 'bond' in ns.opti_cycle['geoms']: + ns.opti_cycle['nb_geoms']['bond'] = ns.nb_bonds + if 'angle' in ns.opti_cycle['geoms']: + ns.opti_cycle['nb_geoms']['angle'] = ns.nb_angles + geoms_display.append('angles') + if 'dihedral' in ns.opti_cycle['geoms']: + ns.opti_cycle['nb_geoms']['dihedral'] = ns.nb_dihedrals + geoms_display.append('dihedrals') + geoms_display = ' & '.join(geoms_display) + + print() + print() + print(swarmcg.shared.styling.sep_close) + print('| STARTING OPTIMIZATION CYCLE', ns.opti_cycle['nb_cycle'], ' |') + print('| Optimizing', geoms_display, ' '*(95-16-len(geoms_display)), '|') + print(swarmcg.shared.styling.sep_close) + + # actual BI to get the initial guesses of force constants, for all selected geoms at this given optimization step + # BI is performed: + # -- exec_mode 1: all values and force constants + # -- exec_mode 2: values are not touched for angles and dihedrals, but all force constants are estimated + # -- exec_mode 3: values are not touched for dihedrals, but all force constants are estimated + scg.perform_BI(ns) # performed on object ns.out_itp + + # build vector for search space boundaries + create variations around the BI initial guesses + search_space_boundaries = scg.get_search_space_boundaries(ns) + # ns.worst_fit_score = round(len(search_space_boundaries) * config.sim_crash_EMD_indep_score, 3) + ns.worst_fit_score = round(\ + np.sqrt((ns.nb_constraints+ns.nb_bonds) * config.sim_crash_EMD_indep_score) + \ + np.sqrt(ns.nb_angles * config.sim_crash_EMD_indep_score) + \ + np.sqrt(ns.nb_dihedrals * config.sim_crash_EMD_indep_score) \ + , 3) + # nb_particles = int(10 + 2*np.sqrt(len(search_space_boundaries))) # formula used by FST-PSO to choose nb of particles, which defines the number of initial guesses we can use + nb_particles = int(round(2 + np.sqrt(len(search_space_boundaries)))) # adapted to have less particles and fitted to our problems, which has good initial guesses and error driven initialization + # nb_particles = 2 # for tests + initial_guess_list = scg.get_initial_guess_list(ns, nb_particles) + + # actual optimization + with open(os.devnull, 'w') as devnull: + with contextlib.redirect_stdout(devnull): + FP = FuzzyPSO() + FP.set_search_space(search_space_boundaries) + FP.set_swarm_size(nb_particles) + FP.set_fitness(fitness=scg.eval_function, arguments=ns, skip_test=True) + result = FP.solve_with_fstpso(max_iter=ns.max_swarm_iter, initial_guess_list=initial_guess_list, max_iter_without_new_global_best=ns.max_swarm_iter_without_new_global_best) + + # update ITP object with the best solution using geoms considered at this given optimization step + scg.update_cg_itp_obj(ns, parameters_set=result[0].X, update_type=2) + + # clean temporary copied directory with user's input files + shutil.rmtree(ns.exec_folder+'/'+config.input_sim_files_dirname) + + # print some stats + total_time_sec = datetime.now().timestamp() - ns.start_opti_ts + total_time = round(total_time_sec / (60 * 60), 2) + fitness_eval_time = round(ns.total_eval_time / (60 * 60), 2) + init_time = round((total_time_sec - ns.total_eval_time) / (60 * 60), 2) + ns.total_gmx_time = round(ns.total_gmx_time / (60 * 60), 2) + ns.total_model_eval_time = round(ns.total_model_eval_time / (60 * 60), 2) + print() + print(swarmcg.shared.styling.sep_close) + print('| FINISHED PROPERLY |') + print(swarmcg.shared.styling.sep_close) + print() + print('Total nb of evaluation steps:', ns.nb_eval) + print('Best model obtained at evaluation step number:', ns.best_fitness[1]) + print() + print('Total execution time :', total_time, 'h') + print('Initialization time :', init_time, 'h ('+str(round(init_time/total_time*100, 2))+' %)') + print('Simulations time :', ns.total_gmx_time, 'h ('+str(round(ns.total_gmx_time/total_time*100, 2))+' %)') + print('Models scoring time :', ns.total_model_eval_time, 'h ('+str(round(ns.total_model_eval_time/total_time*100, 2))+' %)') + print() +if __name__ == '__main__': + + print( + swarmcg.shared.styling.header_package(' Module: CG model optimization\n')) + + formatter = lambda prog: RawTextHelpFormatter(prog, width=135, max_help_position=52) + args_parser = ArgumentParser( + description=OPTIMISE_DESCR, + formatter_class=formatter, + add_help=False, + usage=SUPPRESS + ) + + # TODO: handle trajectories for which no box informations are provided + # TODO: explain what is modified in the MDP + # TODO: explain module analyze_opti_moves.py can be used to monitor optimization at any point of the process + # TODO: end the help message by a new frame with examples from the demo data + + req_args_header = swarmcg.shared.styling.sep_close + '\n| REQUIRED ARGUMENTS |\n' + swarmcg.shared.styling.sep_close + opt_args_header = swarmcg.shared.styling.sep_close + '\n| OPTIONAL ARGUMENTS |\n' + swarmcg.shared.styling.sep_close + bullet = ' ' + + optional_args0 = args_parser.add_argument_group( + req_args_header + '\n\n' + bullet + 'EXECUTION MODE') + optional_args0.add_argument('-exec_mode', dest='exec_mode', + help='MODE 1: Tune both bonds lengths, angles/dihedrals values\n and their force constants\nMODE 2: Like MODE 1 but angles/dihedrals values in the prelim.\n CG model ITP are conserved during optimization\nMODE 3: Like MODE 1 but only dihedrals values in the prelim.\n CG model ITP are conserved during optimization', + type=int, default=1, metavar=' (1)') + + required_args = args_parser.add_argument_group(bullet + 'REFERENCE AA MODEL') + required_args.add_argument('-aa_tpr', dest='aa_tpr_filename', help=config.help_aa_tpr, type=str, + default=config.metavar_aa_tpr, + metavar=' ' + scg.par_wrap(config.metavar_aa_tpr)) + required_args.add_argument('-aa_traj', dest='aa_traj_filename', help=config.help_aa_traj, + type=str, default=config.metavar_aa_traj, + metavar=' ' + scg.par_wrap(config.metavar_aa_traj)) + required_args.add_argument('-cg_map', dest='cg_map_filename', help=config.help_cg_map, type=str, + default=config.metavar_cg_map, + metavar=' ' + scg.par_wrap(config.metavar_cg_map)) + + sim_filenames_args = args_parser.add_argument_group(bullet + 'CG MODEL OPTIMIZATION') + sim_filenames_args.add_argument('-cg_itp', dest='cg_itp_filename', + help='ITP file of the CG model to optimize', type=str, + default=config.metavar_cg_itp, + metavar=' ' + scg.par_wrap(config.metavar_cg_itp)) + sim_filenames_args.add_argument('-cg_gro', dest='gro_input_filename', + help='Starting GRO file used for iterative simulation\nWill be minimized and relaxed before each MD run', + type=str, default='start_conf.gro', + metavar=' (start_conf.gro)') + sim_filenames_args.add_argument('-cg_top', dest='top_input_filename', + help='TOP file used for iterative simulation', type=str, + default='system.top', metavar=' (system.top)') + sim_filenames_args.add_argument('-cg_mdp_mini', dest='mdp_minimization_filename', + help='MDP file used for minimization runs', type=str, + default='mini.mdp', metavar=' (mini.mdp)') + sim_filenames_args.add_argument('-cg_mdp_equi', dest='mdp_equi_filename', + help='MDP file used for equilibration runs', type=str, + default='equi.mdp', metavar=' (equi.mdp)') + sim_filenames_args.add_argument('-cg_mdp_md', dest='mdp_md_filename', + help='MDP file used for the MD runs analyzed for optimization', + type=str, default='md.mdp', metavar=' (md.mdp)') + + optional_args4 = args_parser.add_argument_group( + opt_args_header + '\n\n' + bullet + 'FILES HANDLING') + optional_args4.add_argument('-in_dir', dest='input_folder', + help='Additional prefix path used to find argument-provided files\nIf ambiguous, files found without prefix are preferred', + type=str, default='.', metavar='') + optional_args4.add_argument('-out_dir', dest='output_folder', + help='Directory where to store all outputs of this program\nDefault -out_dir is named after timestamp', + type=str, default='', metavar='') + + optional_args1 = args_parser.add_argument_group(bullet + 'GROMACS SETTINGS') + optional_args1.add_argument('-gmx', dest='gmx_path', help=config.help_gmx_path, type=str, + default=config.gmx_path, + metavar=' ' + scg.par_wrap(config.gmx_path)) + optional_args1.add_argument('-nt', dest='nb_threads', + help='Number of threads to use, forwarded to gmx mdrun -nt', type=int, + default=0, metavar=' (0)') + optional_args1.add_argument('-gpu_id', dest='gpu_id', + help='String (use quotes) space-separated list of GPU device IDs', + type=str, default='', metavar='') + optional_args1.add_argument('-gmx_args_str', dest='gmx_args_str', + help='String (use quotes) of arguments to forward to gmx mdrun\nIf provided, arguments -nt and -gpu_id are ignored', + type=str, default='', metavar='') + optional_args1.add_argument('-mini_maxwarn', dest='mini_maxwarn', + help='Max. number of warnings to ignore, forwarded to gmx\ngrompp -maxwarn at each minimization step', + type=int, default=1, metavar=' (1)') + optional_args1.add_argument('-sim_kill_delay', dest='sim_kill_delay', + help='Time (s) after which to kill a simulation that has not been\nwriting into its log file, in case a simulation gets stuck', + type=int, default=60, metavar=' (60)') + + optional_args2 = args_parser.add_argument_group(bullet + 'CG MODEL SCALING') + optional_args2.add_argument('-aa_rg_offset', dest='aa_rg_offset', + help='Radius of gyration offset (nm) to be applied to AA data\naccording to your potential bonds rescaling (for display only)', + type=float, default=0.00, metavar=' ' + scg.par_wrap('0.00')) + optional_args2.add_argument('-bonds_scaling', dest='bonds_scaling', + help=config.help_bonds_scaling, type=float, + default=config.bonds_scaling, + metavar=' ' + scg.par_wrap(config.bonds_scaling)) + optional_args2.add_argument('-bonds_scaling_str', dest='bonds_scaling_str', + help=config.help_bonds_scaling_str, type=str, + default=config.bonds_scaling_str, metavar='') + optional_args2.add_argument('-min_bonds_length', dest='min_bonds_length', + help=config.help_min_bonds_length, type=float, + default=config.min_bonds_length, + metavar=' ' + scg.par_wrap(config.min_bonds_length)) + + optional_args5 = args_parser.add_argument_group(bullet + 'CG MODEL SCORING') + optional_args5.add_argument('-cg_time_short', dest='sim_duration_short', + help='Simulation time (ns) of the MD runs analyzed for optimization\nIn opti. cycles 1 and 2, this will modify MDP file for the MD runs', + type=float, default=10, metavar=' (10)') + optional_args5.add_argument('-cg_time_long', dest='sim_duration_long', + help='Simulation time (ns) of the MD runs analyzed for optimization\nIn opti. cycle 3, this will modify MDP file for the MD runs', + type=float, default=25, metavar=' (25)') + optional_args5.add_argument('-b2a_score_fact', dest='bonds2angles_scoring_factor', + help=config.help_bonds2angles_scoring_factor, type=float, + default=config.bonds2angles_scoring_factor, + metavar=' ' + scg.par_wrap(config.bonds2angles_scoring_factor)) + optional_args5.add_argument('-bw_constraints', dest='bw_constraints', + help=config.help_bw_constraints, type=float, + default=config.bw_constraints, + metavar=' ' + scg.par_wrap(config.bw_constraints)) + optional_args5.add_argument('-bw_bonds', dest='bw_bonds', help=config.help_bw_bonds, type=float, + default=config.bw_bonds, + metavar=' ' + scg.par_wrap(config.bw_bonds)) + optional_args5.add_argument('-bw_angles', dest='bw_angles', help=config.help_bw_angles, + type=float, default=config.bw_angles, + metavar=' ' + scg.par_wrap(config.bw_angles)) + optional_args5.add_argument('-bw_dihedrals', dest='bw_dihedrals', help=config.help_bw_dihedrals, + type=float, default=config.bw_dihedrals, + metavar=' ' + scg.par_wrap(config.bw_dihedrals)) + optional_args5.add_argument('-bonds_max_range', dest='bonded_max_range', + help=config.help_bonds_max_range, type=float, + default=config.bonds_max_range, + metavar=' ' + scg.par_wrap(config.bonds_max_range)) + + optional_args6 = args_parser.add_argument_group(bullet + 'CG MODEL FORCE CONSTANTS') + optional_args6.add_argument('-max_fct_bonds_f1', dest='default_max_fct_bonds_opti', + help=config.help_max_fct_bonds, type=float, + default=config.default_max_fct_bonds_opti, + metavar=' ' + scg.par_wrap(config.default_max_fct_bonds_opti)) + optional_args6.add_argument('-max_fct_angles_f1', dest='default_max_fct_angles_opti_f1', + help=config.help_max_fct_angles_f1, type=float, + default=config.default_max_fct_angles_opti_f1, + metavar=' ' + scg.par_wrap(config.default_max_fct_angles_opti_f1)) + optional_args6.add_argument('-max_fct_angles_f2', dest='default_max_fct_angles_opti_f2', + help=config.help_max_fct_angles_f2, type=float, + default=config.default_max_fct_angles_opti_f2, + metavar=' ' + scg.par_wrap(config.default_max_fct_angles_opti_f2)) + optional_args6.add_argument('-max_fct_dihedrals_f149', + dest='default_abs_range_fct_dihedrals_opti_func_with_mult', + help=config.help_max_fct_dihedrals_with_mult, type=float, + default=config.default_abs_range_fct_dihedrals_opti_func_with_mult, + metavar='' + scg.par_wrap( + config.default_abs_range_fct_dihedrals_opti_func_with_mult)) + optional_args6.add_argument('-max_fct_dihedrals_f2', + dest='default_max_fct_dihedrals_opti_func_without_mult', + help=config.help_max_fct_dihedrals_without_mult, type=float, + default=config.default_max_fct_dihedrals_opti_func_without_mult, + metavar='' + scg.par_wrap( + config.default_max_fct_dihedrals_opti_func_without_mult)) + + optional_args3 = args_parser.add_argument_group(bullet + 'OTHERS') + optional_args3.add_argument('-temp', dest='temp', + help='Temperature used to perform Boltzmann inversion (K)', + type=float, default=config.sim_temperature, + metavar=' ' + scg.par_wrap(config.sim_temperature)) + optional_args3.add_argument('-keep_all_sims', dest='keep_all_sims', + help='Store all gmx files for all simulations, may use disk space', + action='store_true', default=False) + optional_args3.add_argument('-h', '--help', help='Show this help message and exit', action='help') + optional_args3.add_argument('-v', '--verbose', dest='verbose', help=config.help_verbose, + action='store_true', default=False) + + # display help if script was called without arguments + if len(sys.argv) == 1: + args_parser.print_help() + sys.exit() + + # arguments handling, display command line if help or no arguments provided + # argcomplete.autocomplete(parser) + ns = args_parser.parse_args() + input_cmdline = ' '.join(map(cmd_quote, sys.argv)) + ns.exec_folder = time.strftime( + "MODEL_OPTI__STARTED_%d-%m-%Y_%Hh%Mm%Ss") # default folder name for all files of this optimization run, in case none is provided + if ns.output_folder != '': + ns.exec_folder = ns.output_folder + + print('Working directory:', os.getcwd()) + print('Command line:', input_cmdline) + print('Results directory:', ns.exec_folder) + + main(ns) diff --git a/swarmcg/shared/styling.py b/swarmcg/shared/styling.py new file mode 100644 index 0000000..3dd2f09 --- /dev/null +++ b/swarmcg/shared/styling.py @@ -0,0 +1,142 @@ +import swarmcg +from .. import config + +sep = '----------------------------------------------------------------------' +sep_close = '+---------------------------------------------------------------------------------------------+' +header_warning = '\n-- ! WARNING ! --\n' +header_error = '\n-- ! ERROR ! --\n' +header_gmx_error = sep + '\n GMX ERROR MSG\n' + sep + '\n\n' + +# String 'S m a r t . C G' Ivrit style Fitted/Full +def header_package(module_line): + return f""" + + + ███████╗██╗ ██╗ █████╗ ██████╗ ███╗ ███╗ ██████╗ ██████╗ + ██╔════╝██║ ██║██╔══██╗██╔══██╗████╗ ████║ ██╔════╝██╔════╝ + ███████╗██║ █╗ ██║███████║██████╔╝██╔████╔██║█████╗██║ ██║ ███╗ + ╚════██║██║███╗██║██╔══██║██╔══██╗██║╚██╔╝██║╚════╝██║ ██║ ██║ + ███████║╚███╔███╔╝██║ ██║██║ ██║██║ ╚═╝ ██║ ╚██████╗╚██████╔╝ + ╚══════╝ ╚══╝╚══╝ ╚═╝ ╚═╝╚═╝ ╚═╝╚═╝ ╚═╝ ╚═════╝ ╚═════╝ v {swarmcg.__version__ } + {module_line} +{sep_close} +| Swarm-CG is distributed under the terms of the MIT License. | +| | +| Feedback, questions and bug reports are welcome at: | +| {config.github_url}/issues | +| | +| If you found Swarm-CG useful in your research, please cite: | +| Swarm-CG: Automatic parametrization of bonded terms in CG models | +| of simple to complex molecules via FST-PSO | +| Empereur-mot C., Pesce L., Bochicchio D., Perego C., Pavan G.M. ChemRxiv 2020 | +| | +| Swarm-CG relies on FST-PSO: | +| Fuzzy Self-Tuning PSO: A settings-free algorithm for global optimization | +| Nobile M.S., Cazzaniga P., Besozzi D., Colombo R., Mauri G., Pasia G. Swarm Evo Comp 2018 | +{sep_close} +""" + +ANALYSE_DESCR = """ +This module produces a visual summary (big plot) of an optimization procedure started with +module 'scg_optimize' to refine the bonded terms of a coarse-grained (CG) molecular model. +It works whether the optimization is ongoing or finished. The plot will be produced in the +directory provided via argument -opti_dir. + +Top row displays bonded terms score (global and breakdown) together with radius of gyration +(Rg) and solvent accessible surface area (SASA) estimations. We call these estimations because +they are calculated on short simulations used during optimization (time depends on parameters +used for optimization), therefore one should always run a long simulation at the end of the +optimizaton process, from which one can calculate the real Rg and SASA values for your model. + +Other rows display bond, angle and dihedral parameters tested together with their independant +score (distance from the AA distributions using EMD/Wasserstein). This allows to diagnose +issues, notably related to the topology defined in the ITP file, for example if the score +cannot go down for a specific group of bonds, angles or dihedrals. The optimization procedure +is in principle robust, as demonstrated in the paper, however problems can arise from the CG +representation used (e.g. if topology is too restrictive or incorrectly defined) and non-bonded +parameters (e.g. strong intra-molecular attractions that would not allow the molecule to adopt +extended conformations). +""" + +EVALUATE_DESCR = """ +This module enables quick evaluation of the fit of bond, angle and dihedral distributions between +a CG model trajectory and a reference AA model trajectory of an identical molecule, in a single +comprehensive figure. The figure's rows display bond, angle and dihedral distributions for groups +present in your system according to the ITP file. + +Arguments allows to specify scaling of the AA bonds used as reference to optimize the CG model. +An image displaying all AA reference distributions will be created at the very beginning of the +optimization process. You can check it to make sure scaling is conform to your expectations. + +The CG model preliminary ITP file follows the standard ITP format, with one subtlety. The file +can include groups of bonds, angles and dihedrals that will be considered identical. Their +distributions will be averaged within groups. This is important to obtain reliable results for +symmetrical molecules. Groups can be formed using empty line(s) or comment(s), like this: + + [ angles ] + + ; i j k funct angle force.c. + ; grp 1 + 5 6 10 1 150 40 + 9 8 11 1 150 40 + ; grp 2 + 1 6 10 2 120 0 ; NOTE: either comment(s) or empty line(s) + 4 8 11 2 120 0 ; separate groups of bonds/ang/dihe. + +The AA trajectory is mapped on-the-fly using file from argument -cg_map, which uses gromacs NDX +file format. Periodic boundary conditions are handled internally if the input trajectories +contain box dimensions. +""" + +OPTIMISE_DESCR = """ +This module automatically optimizes the bonded parameters of a CG model to best match the bonds, +angles and dihedrals distributions of a reference AA model. Different sets of bonded parameters +are explored via swarm optimization (FST-PSO) and iterative CG simulations. Bonded parameters are +evaluated for the matching they produce between AA and CG distributions via a scoring function +relying on the Earth Movers' Distance (EMD/Wasserstein). The process is designed to execute in +4-24h on a standard desktop machine, according to hardware, molecule size and simulations setup. + +This module has 2 optimization modes: + +(1) TUNE BOTH BONDS LENGTHS, ANGLES/DIHEDRALS VALUES AND THEIR FORCE CONSTANTS. First uses + Boltzmann Inversion to estimate bonds lengths, angles/dihedrals values and their force + constants, then runs optimization to best fit the reference AA-mapped distributions. + +(2) TUNE ONLY FORCE CONSTANTS FOR ANGLES/DIHEDRALS VALUES AND ALL PARAMETERS FOR BONDS. + Equilibrium values of angles/dihedrals provided in the preliminary CG ITP model are + conserved while optimization best fits reference AA-mapped distributions. + +Independently of parameters, the expected input is: + +(1) Atomistic trajectory of the molecule (gromacs binary TPR + trajectory files XTC TRR) +(2) Mapping file, atoms to CG beads (gromacs NDX format) +(3) CG model ITP file to be optimized (group identical bonds/angles/dihedrals, see below) +(4) CG simulation files (initial configuration GRO + system TOP + MDP files) + +You can prepare a directory using default input filenames, then provide only argument -in_dir. +If -in_dir is provided, all filenames provided as arguments will also be searched for within +this directory. Demonstration data are available at ''' + config.github_url + '''. + +Arguments allows to specify scaling of the AA bonds used as reference to optimize the CG model. +An image displaying all AA reference distributions will be created at the very beginning of the +optimization process. You can check it to make sure scaling is conform to your expectations. + +The CG model preliminary ITP file follows the standard ITP format, with one subtlety. The file +can include groups of bonds, angles and dihedrals that will be considered identical. Their +distributions will be averaged within groups. This is important to obtain reliable results for +symmetrical molecules. Groups can be formed using empty line(s) or comment(s), like this: + +[ angles ] + +; i j k funct angle force.c. +; grp 1 + 5 6 10 1 150 40 ; NOTE 1: force constants can be set to 0 + 9 8 11 1 150 40 ; in the prelim. model to optimize +; grp 2 + 1 6 10 2 120 0 ; NOTE 2: either comment(s) or empty line(s) + 4 8 11 2 120 0 ; separate groups of bonds/ang/dihe. + +The AA trajectory is mapped on-the-fly using file from argument -cg_map, which uses gromacs NDX +file format. Periodic boundary conditions are handled internally if the input AA trajectory +contains box dimensions +""" \ No newline at end of file diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index f5ef5be..b01fcaa 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -1,10 +1,11 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings -warnings.filterwarnings("ignore") -import collections -import (sys, re, random, os, shutil, subprocess, signal, time, contextlib, - warnings, textwrap, collections) +import swarmcg.shared.styling + +warnings.filterwarnings("ignore") +import sys, re, random, os, shutil, subprocess, signal, time, contextlib +import warnings, collections from datetime import datetime # matplotlib new version has some problems with incorrectly uninstalled files at version upgrade and display a lot of warnings @@ -25,42 +26,10 @@ # TODO: When provided trajectory file does NOT contain PBC infos (box position and size for each frame, which are present in XTC format for example), we want to stil accept the provided trajectory format (if accepted by MDAnalysis) but we automatically disable the handling of PBC by the code - -# String 'S m a r t . C G' Ivrit style Fitted/Full -def header_package(module_line): - - return '''\ - - - ███████╗██╗ ██╗ █████╗ ██████╗ ███╗ ███╗ ██████╗ ██████╗ - ██╔════╝██║ ██║██╔══██╗██╔══██╗████╗ ████║ ██╔════╝██╔════╝ - ███████╗██║ █╗ ██║███████║██████╔╝██╔████╔██║█████╗██║ ██║ ███╗ - ╚════██║██║███╗██║██╔══██║██╔══██╗██║╚██╔╝██║╚════╝██║ ██║ ██║ - ███████║╚███╔███╔╝██║ ██║██║ ██║██║ ╚═╝ ██║ ╚██████╗╚██████╔╝ - ╚══════╝ ╚══╝╚══╝ ╚═╝ ╚═╝╚═╝ ╚═╝╚═╝ ╚═╝ ╚═════╝ ╚═════╝ v '''+config.module_version+''' - '''+module_line+''' -'''+config.sep_close+''' -| Swarm-CG is distributed under the terms of the MIT License. | -| | -| Feedback, questions and bug reports are welcome at: | -| '''+config.github_url+'''/issues | -| | -| If you found Swarm-CG useful in your research, please cite: | -| Swarm-CG: Automatic parametrization of bonded terms in CG models | -| of simple to complex molecules via FST-PSO | -| Empereur-mot C., Pesce L., Bochicchio D., Perego C., Pavan G.M. ChemRxiv 2020 | -| | -| Swarm-CG relies on FST-PSO: | -| Fuzzy Self-Tuning PSO: A settings-free algorithm for global optimization | -| Nobile M.S., Cazzaniga P., Besozzi D., Colombo R., Mauri G., Pasia G. Swarm Evo Comp 2018 | -'''+config.sep_close+'\n' - - # cast object as string, enclose by parentheses and return a string -- for arguments display in help def par_wrap(string): return '('+str(string)+')' - # set MDAnalysis backend and number of threads def set_MDA_backend(ns): @@ -223,16 +192,21 @@ def verify_handled_functions(geom, func_obj, line_obj): try: func = int(func_obj) except (ValueError, IndexError): - sys.exit(config.header_error+'Error while reading CG ITP file at line '+str(line_obj)+', please check this file') + sys.exit( + swarmcg.shared.styling.header_error + 'Error while reading CG ITP file at line ' + str(line_obj) + ', please check this file') if geom == 'constraint' and func not in config.handled_constraints_functions: - sys.exit(config.header_error+'Error while reading constraint function in CG ITP file at line '+str(line_obj)+'\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these constraint potential functions: '+", ".join(map(str, config.handled_constraints_functions))) + sys.exit( + swarmcg.shared.styling.header_error + 'Error while reading constraint function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these constraint potential functions: ' + ", ".join(map(str, config.handled_constraints_functions))) elif geom == 'bond' and func not in config.handled_bonds_functions: - sys.exit(config.header_error+'Error while reading bond function in CG ITP file at line '+str(line_obj)+'\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these bond potential functions: '+", ".join(map(str, config.handled_bonds_functions))) + sys.exit( + swarmcg.shared.styling.header_error + 'Error while reading bond function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these bond potential functions: ' + ", ".join(map(str, config.handled_bonds_functions))) elif geom == 'angle' and func not in config.handled_angles_functions: - sys.exit(config.header_error+'Error while reading angle function in CG ITP file at line '+str(line_obj)+'\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these angle potential functions: '+", ".join(map(str, config.handled_angles_functions))) + sys.exit( + swarmcg.shared.styling.header_error + 'Error while reading angle function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these angle potential functions: ' + ", ".join(map(str, config.handled_angles_functions))) elif geom == 'dihedral' and func not in config.handled_dihedrals_functions: - sys.exit(config.header_error+'Error while reading dihedral function in CG ITP file at line '+str(line_obj)+'\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these dihedral potential functions: '+", ".join(map(str, config.handled_dihedrals_functions))) + sys.exit( + swarmcg.shared.styling.header_error + 'Error while reading dihedral function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these dihedral potential functions: ' + ", ".join(map(str, config.handled_dihedrals_functions))) return func @@ -296,7 +270,8 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['constraint'][ns.nb_constraints]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:2]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit(config.header_error+'Incorrect reading of the CG ITP file within [constraints] section, please check this file') + sys.exit( + swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [constraints] section, please check this file') func = verify_handled_functions('constraint', sp_itp_line[2], i+1) ns.cg_itp['constraint'][ns.nb_constraints]['funct'].append(func) ns.cg_itp['constraint'][ns.nb_constraints]['value'].append(float(sp_itp_line[3])) @@ -319,7 +294,8 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['bond'][ns.nb_bonds]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:2]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit(config.header_error+'Incorrect reading of the CG ITP file within [bonds] section, please check this file') + sys.exit( + swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [bonds] section, please check this file') func = verify_handled_functions('bond', sp_itp_line[2], i+1) ns.cg_itp['bond'][ns.nb_bonds]['funct'].append(func) ns.cg_itp['bond'][ns.nb_bonds]['value'].append(float(sp_itp_line[3])) @@ -343,7 +319,8 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['angle'][ns.nb_angles]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:3]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit(config.header_error+'Incorrect reading of the CG ITP file within [angles] section, please check this file') + sys.exit( + swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [angles] section, please check this file') func = verify_handled_functions('angle', sp_itp_line[3], i+1) ns.cg_itp['angle'][ns.nb_angles]['funct'].append(func) ns.cg_itp['angle'][ns.nb_angles]['value'].append(float(sp_itp_line[4])) @@ -367,7 +344,8 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['dihedral'][ns.nb_dihedrals]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:4]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit(config.header_error+'Incorrect reading of the CG ITP file within [dihedrals] section, please check this file') + sys.exit( + swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [dihedrals] section, please check this file') func = verify_handled_functions('dihedral', sp_itp_line[4], i+1) ns.cg_itp['dihedral'][ns.nb_dihedrals]['funct'].append(func) ns.cg_itp['dihedral'][ns.nb_dihedrals]['value'].append(float(sp_itp_line[5])) # issue happens here for functions that are not handled @@ -402,7 +380,8 @@ def read_cg_itp_file(ns, itp_lines): if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit(config.header_error+'In the provided CG ITP file '+geom+' have been grouped, but '+geom+' group '+str(grp_geom+1)+' holds '+geom+' lines that have different parameters\nParameters should be identical within a '+geom+' group, only CG beads IDs should differ\nPlease correct the CG ITP file and separate groups using a blank or commented line') + sys.exit( + swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within a ' + geom + ' group, only CG beads IDs should differ\nPlease correct the CG ITP file and separate groups using a blank or commented line') for geom in ['bond', 'angle']: # bonds and angles only for grp_geom in range(len(ns.cg_itp[geom])): @@ -411,7 +390,8 @@ def read_cg_itp_file(ns, itp_lines): if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit(config.header_error+'In the provided CG ITP file '+geom+' have been grouped, but '+geom+' group '+str(grp_geom+1)+' holds '+geom+' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a '+geom+' group\nPlease correct the CG ITP file and separate groups using a blank or commented line') + sys.exit( + swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a ' + geom + ' group\nPlease correct the CG ITP file and separate groups using a blank or commented line') for geom in ['dihedral']: # dihedrals only for grp_geom in range(len(ns.cg_itp[geom])): @@ -420,13 +400,15 @@ def read_cg_itp_file(ns, itp_lines): if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit(config.header_error+'In the provided CG ITP file '+geom+' have been grouped, but '+geom+' group '+str(grp_geom+1)+' holds '+geom+' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a '+geom+' group\nPlease correct the CG ITP file and separate groups using a blank or commented line') + sys.exit( + swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a ' + geom + ' group\nPlease correct the CG ITP file and separate groups using a blank or commented line') for var in ['mult']: var_set = set(ns.cg_itp[geom][grp_geom][var]) if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit(config.header_error+'In the provided CG ITP file '+geom+' have been grouped, but '+geom+' group '+str(grp_geom+1)+' holds '+geom+' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a '+geom+' group') + sys.exit( + swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a ' + geom + ' group') ns.nb_constraints += 1 ns.nb_bonds += 1 @@ -466,7 +448,8 @@ def read_ndx_atoms2beads(ns): try: lines_read += 1 if lines_read > 1: - sys.exit(config.header_error+'A section of the CG beads mapping (NDX) file has multiple lines, while Swarm-CG accepts only one line per section\nPlease use a single line for IDs under section '+current_section+' near line '+str(i+1)) + sys.exit( + swarmcg.shared.styling.header_error + 'A section of the CG beads mapping (NDX) file has multiple lines, while Swarm-CG accepts only one line per section\nPlease use a single line for IDs under section ' + current_section + ' near line ' + str(i + 1)) bead_atoms_id = [int(atom_id)-1 for atom_id in ndx_line.split()] # retrieve indexing from 0 for atoms IDs for MDAnalysis ns.all_beads[bead_id]['atoms_id'].extend(bead_atoms_id) # all atoms included in current bead @@ -475,9 +458,11 @@ def read_ndx_atoms2beads(ns): bead_id += 1 except NameError: - sys.exit(config.header_error+'The CG beads mapping (NDX) file does NOT seem to contain CG beads sections, please verify the input mapping\nThe expected format is Gromacs NDX') + sys.exit( + swarmcg.shared.styling.header_error + 'The CG beads mapping (NDX) file does NOT seem to contain CG beads sections, please verify the input mapping\nThe expected format is Gromacs NDX') except ValueError: # non-integer atom ID provided - sys.exit(config.header_error+'Incorrect reading of the sections content in the CG beads mapping (NDX) file\nFound non-integer values for some IDs at line '+str(i+1)+' under section '+current_section) + sys.exit( + swarmcg.shared.styling.header_error + 'Incorrect reading of the sections content in the CG beads mapping (NDX) file\nFound non-integer values for some IDs at line ' + str(i + 1) + ' under section ' + current_section) return @@ -514,7 +499,8 @@ def get_beads_MDA_atomgroups(ns): ns.mda_weights_atom_grps[bead_id] = np.array([ns.atom_w[bead_id][atom_id]*ns.aa_universe.atoms[atom_id].mass for atom_id in ns.atom_w[bead_id]]) # ns.mda_weights_atom_grps[bead_id] = np.array([ns.atom_w[bead_id][atom_id]*ns.all_atoms[atom_id]['atom_mass'] for atom_id in ns.atom_w[bead_id]]) except IndexError as e: - sys.exit(config.header_error+'An ID present in your mapping (NDX) file could not be found in the AA trajectory, please check your mapping (NDX) file\nSee the error below to understand which ID (here 0-indexed) could not be found:\n '+str(e)) + sys.exit( + swarmcg.shared.styling.header_error + 'An ID present in your mapping (NDX) file could not be found in the AA trajectory, please check your mapping (NDX) file\nSee the error below to understand which ID (here 0-indexed) could not be found:\n ' + str(e)) return @@ -753,7 +739,8 @@ def update_cg_itp_obj(ns, parameters_set, update_type): elif update_type == 2: # cycles optimized itp_obj = ns.opti_itp else: - sys.exit(config.header_error+'Code error in function update_cg_itp_obj, please consider opening an issue on GitHub at '+config.github_url) + sys.exit( + swarmcg.shared.styling.header_error + 'Code error in function update_cg_itp_obj, please consider opening an issue on GitHub at ' + config.github_url) for i in range(ns.opti_cycle['nb_geoms']['constraint']): itp_obj['constraint'][i]['value'] = round(parameters_set[i], 3) # constraint - distance @@ -1549,7 +1536,8 @@ def perform_BI(ns): popt[0] = 30 else: - sys.exit(config.header_error+'Code error, we should never arrive here because functions have been checked during CG ITP file reading') + sys.exit( + swarmcg.shared.styling.header_error + 'Code error, we should never arrive here because functions have been checked during CG ITP file reading') # here we just update the force constant, angle value is already set to the average of distribution ns.out_itp['angle'][grp_angle]['fct'] = min(max(popt[0], config.default_min_fct_angles), config.default_max_fct_angles_bi) # stay within specified range for force constants @@ -1587,7 +1575,8 @@ def perform_BI(ns): popt[0] = abs(popt[0]) # just to be safe, in case the fit yielded negative fct values but this is very unlikely since we provide good starting parameters for the fit else: - sys.exit(config.header_error+'Code error, we should never arrive here because functions have been checked during CG ITP file reading') + sys.exit( + swarmcg.shared.styling.header_error + 'Code error, we should never arrive here because functions have been checked during CG ITP file reading') if ns.exec_mode == 1: ns.out_itp['dihedral'][grp_dihedral]['value'] = np.rad2deg(popt[1]) @@ -1615,7 +1604,8 @@ def process_scaling_str(ns): if ns.bonds_scaling_str != config.bonds_scaling_str: sp_str = ns.bonds_scaling_str.split() if len(sp_str) % 2 != 0: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') ns.bonds_scaling_specific = dict() i = 0 try: @@ -1623,25 +1613,32 @@ def process_scaling_str(ns): geom_id = sp_str[i][1:] if sp_str[i][0].upper() == 'C': if int(geom_id) > ns.nb_constraints: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA constraint group id exceeds the number of constraints groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id exceeds the number of constraints groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') if not 'C'+geom_id in ns.bonds_scaling_specific: if float(sp_str[i+1]) < 0: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') ns.bonds_scaling_specific['C'+geom_id] = float(sp_str[i+1]) else: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA constraint group id is provided multiple times (id: '+str(geom_id)+')\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') elif sp_str[i][0].upper() == 'B': if int(geom_id) > ns.nb_bonds: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA bond group id exceeds the number of bonds groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id exceeds the number of bonds groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') if not 'B'+geom_id in ns.bonds_scaling_specific: if float(sp_str[i+1]) < 0: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') ns.bonds_scaling_specific['B'+geom_id] = float(sp_str[i+1]) else: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nA bond group id is provided multiple times (id: '+str(geom_id)+')\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') i += 2 except ValueError: - sys.exit(config.header_error+'Cannot interpret argument -bonds_scaling_str as provided: \''+ns.bonds_scaling_str+'\'\nPlease check your parameters, or help for an example') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') return @@ -1667,7 +1664,8 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False read_cg_itp_file(ns, itp_lines) process_scaling_str(ns) except UnicodeDecodeError: - sys.exit(config.header_error+'Cannot read CG ITP, it seems you provided a binary file.') + sys.exit( + swarmcg.shared.styling.header_error + 'Cannot read CG ITP, it seems you provided a binary file.') # if we do not have reference already from the optimization procedure if manual_mode: @@ -1727,9 +1725,9 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False return 0, 0, 0, 0, 0, None # ns.sasa_cg == None will be checked in eval_function and worst score will be attributed print() - print(config.sep_close, flush=True) + print(swarmcg.shared.styling.sep_close, flush=True) print('| SCORING AND PLOTTING |', flush=True) - print(config.sep_close, flush=True) + print(swarmcg.shared.styling.sep_close, flush=True) print() # constraints @@ -1770,7 +1768,8 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False domain_max = max(constraints[grp_constraint]['AA']['x'][-1], constraints[grp_constraint]['CG']['x'][-1]) avg_diff_grp_constraints.append(emd(constraints[grp_constraint]['AA']['hist'], constraints[grp_constraint]['CG']['hist'], ns.bins_constraints_dist_matrix) * ns.bonds2angles_scoring_factor) except IndexError: - sys.exit(config.header_error+'Most probably because you have bonds or constraints that exceed '+str(ns.bonded_max_range)+' nm. Increase bins range for bonds and constraints and retry! See argument -bonds_max_range.') + sys.exit( + swarmcg.shared.styling.header_error + 'Most probably because you have bonds or constraints that exceed ' + str(ns.bonded_max_range) + ' nm. Increase bins range for bonds and constraints and retry! See argument -bonds_max_range.') else: avg_diff_grp_constraints.append(constraints[grp_constraint]['AA']['avg']) @@ -1824,7 +1823,8 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False domain_max = max(bonds[grp_bond]['AA']['x'][-1], bonds[grp_bond]['CG']['x'][-1]) avg_diff_grp_bonds.append(emd(bonds[grp_bond]['AA']['hist'], bonds[grp_bond]['CG']['hist'], ns.bins_bonds_dist_matrix) * ns.bonds2angles_scoring_factor) except IndexError: - sys.exit(config.header_error+'Most probably because you have bonds or constraints that exceed '+str(ns.bonded_max_range)+' nm. Increase bins range for bonds and bonds and retry! See argument -bonds_max_range.') + sys.exit( + swarmcg.shared.styling.header_error + 'Most probably because you have bonds or constraints that exceed ' + str(ns.bonded_max_range) + ' nm. Increase bins range for bonds and bonds and retry! See argument -bonds_max_range.') else: avg_diff_grp_bonds.append(bonds[grp_bond]['AA']['avg']) @@ -1957,7 +1957,7 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False print('Displaying max '+str(ncols)+' distributions per row using the CG ITP file ordering of distributions groups ('+str(hidden_cols)+' more are hidden)', flush=True) else: if not ns.mismatch_order: - print(config.header_warning+'Displaying max '+str(ncols)+' distributions groups per row and this can be MISLEADING because ordering by pairwise AA-mapped vs. CG distributions mismatch is DISABLED ('+str(hidden_cols)+' more are hidden)', flush=True) + print(swarmcg.shared.styling.header_warning + 'Displaying max ' + str(ncols) + ' distributions groups per row and this can be MISLEADING because ordering by pairwise AA-mapped vs. CG distributions mismatch is DISABLED (' + str(hidden_cols) + ' more are hidden)', flush=True) else: print('Displaying max '+str(ncols)+' distributions groups per row ordered by pairwise AA-mapped vs. CG distributions difference ('+str(hidden_cols)+' more are hidden)', flush=True) else: @@ -2360,7 +2360,8 @@ def modify_mdp(mdp_filename, sim_time=None, nb_frames=1500, log_write_freq=5000, nsteps = int(sim_time*1000 / dt) mdp_lines_in[nsteps_line] = sp_nsteps_line[0]+'= '+str(nsteps)+' ; automatically modified by Swarm-CG' else: - sys.exit(config.header_error+'The provided MD MDP file does not contain one of these entries: dt, nsteps') + sys.exit( + swarmcg.shared.styling.header_error + 'The provided MD MDP file does not contain one of these entries: dt, nsteps') # force writting to the log file every given nb of steps, to make sure simulations won't be killed for insufficient writting to the log file # (which we use to check for simulations that are stuck/bugged) @@ -2368,7 +2369,8 @@ def modify_mdp(mdp_filename, sim_time=None, nb_frames=1500, log_write_freq=5000, nstlog = log_write_freq mdp_lines_in[nstlog_line] = sp_nstlog_line[0]+'= '+str(nstlog)+' ; automatically modified by Swarm-CG' else: - sys.exit(config.header_error+'The provided MD MDP file does not contain one of these entries: nstlog') + sys.exit( + swarmcg.shared.styling.header_error + 'The provided MD MDP file does not contain one of these entries: nstlog') # force NOT writting coordinates data, as this can only slow the simulation and we don't need it if nstxout_line != -1: @@ -2509,7 +2511,7 @@ def eval_function(parameters_set, ns): gmx_process.kill() else: - sys.exit('\n\n'+config.header_gmx_error+gmx_out+'\n'+config.header_error+'Gmx grompp failed at minimization step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_mini\nYou may also want to look into argument -mini_maxwarn\nIf you think this is a bug, please consider opening an issue on GitHub at '+config.github_url+'\n') + sys.exit('\n\n' + swarmcg.shared.styling.header_gmx_error + gmx_out + '\n' + swarmcg.shared.styling.header_error + 'Gmx grompp failed at minimization step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_mini\nYou may also want to look into argument -mini_maxwarn\nIf you think this is a bug, please consider opening an issue on GitHub at ' + config.github_url + '\n') # if minimization finished properly, we just check for the .gro file printed in the end if os.path.isfile('mini.gro'): @@ -2546,7 +2548,7 @@ def eval_function(parameters_set, ns): else: # pass - sys.exit('\n\n'+config.header_gmx_error+gmx_out+'\n'+config.header_error+'Gmx grompp failed at equilibration step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_equi\nIf you think this is a bug, please consider opening an issue on GitHub at '+config.github_url+'\n') + sys.exit('\n\n' + swarmcg.shared.styling.header_gmx_error + gmx_out + '\n' + swarmcg.shared.styling.header_error + 'Gmx grompp failed at equilibration step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_equi\nIf you think this is a bug, please consider opening an issue on GitHub at ' + config.github_url + '\n') # if EQUI finished properly, we just check for the .gro file printed in the end if os.path.isfile('equi.gro'): @@ -2586,7 +2588,7 @@ def eval_function(parameters_set, ns): else: # pass - sys.exit('\n\n'+config.header_gmx_error+gmx_out+'\n'+config.header_error+'Gmx grompp failed at the MD step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_prod\nIf you think this is a bug, please consider opening an issue on GitHub at '+config.github_url+'\n') + sys.exit('\n\n' + swarmcg.shared.styling.header_gmx_error + gmx_out + '\n' + swarmcg.shared.styling.header_error + 'Gmx grompp failed at the MD step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_prod\nIf you think this is a bug, please consider opening an issue on GitHub at ' + config.github_url + '\n') # to verify if MD run finished properly, we check for the .gro file printed in the end if os.path.isfile('md.gro'): From 79c5098170a430b60da11cc963050bbff709a603 Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Thu, 10 Sep 2020 13:13:21 +0200 Subject: [PATCH 07/40] Added more exceptions --- swarmcg/analyze_optimization.py | 21 ++++++---- swarmcg/evaluate_model.py | 42 +++++++++++--------- swarmcg/optimize_model.py | 68 ++++++++++++++++++++------------- swarmcg/shared/exceptions.py | 64 ++++++++++++++++++++++++++++++- 4 files changed, 140 insertions(+), 55 deletions(-) diff --git a/swarmcg/analyze_optimization.py b/swarmcg/analyze_optimization.py index fee2066..c72f948 100644 --- a/swarmcg/analyze_optimization.py +++ b/swarmcg/analyze_optimization.py @@ -13,6 +13,7 @@ import numpy as np from swarmcg import config +from swarmcg.shared import exceptions from swarmcg.shared.styling import ANALYSE_DESCR from swarmcg.shared.utils import forward_fill @@ -46,10 +47,14 @@ def main(ns): try: used_dihedrals = iter_indep_scores[:,0] for i in range(1, iter_indep_scores.shape[1]): - iter_indep_scores[:,i] = forward_fill(iter_indep_scores[:,i], config.sim_crash_EMD_indep_score) - except IndexError: - sys.exit( - swarmcg.shared.styling.header_error + 'The optimization recap file seems empty, please wait for your optimization process to start or check for errors during execution') + iter_indep_scores[:, i] = forward_fill(iter_indep_scores[:,i], config.sim_crash_EMD_indep_score) + except IndexError as e: + msg = ( + "The optimization recap file seems empty, please wait for your optimization process " + "to start or check for errors during execution" + ) + raise exceptions.IncompleteOptimisationFile(msg) + # process files and plot with open(ns.opti_dirname+'/'+config.opti_perf_recap_file, 'r') as fp: @@ -90,10 +95,10 @@ def main(ns): all_eval_scores, all_eval_times, all_total_times = [], [], [] # worst_fit_score = round((nb_constraints+nb_bonds+nb_angles+nb_dihedrals) * config.sim_crash_EMD_indep_score, 3) - worst_fit_score = round(\ - np.sqrt((nb_constraints+nb_bonds) * config.sim_crash_EMD_indep_score) + \ - np.sqrt(nb_angles * config.sim_crash_EMD_indep_score) + \ - np.sqrt(nb_dihedrals * config.sim_crash_EMD_indep_score) \ + worst_fit_score = round( + np.sqrt((nb_constraints+nb_bonds) * config.sim_crash_EMD_indep_score) + + np.sqrt(nb_angles * config.sim_crash_EMD_indep_score) + + np.sqrt(nb_dihedrals * config.sim_crash_EMD_indep_score) , 3) all_fit_score_total, all_fit_score_constraints_bonds, all_fit_score_angles, all_fit_score_dihedrals = np.array([]), np.array([]), np.array([]), np.array([]) all_gyr_aa_mapped, all_gyr_aa_mapped_std, all_gyr_cg, all_gyr_cg_std = np.array([]), np.array([]), np.array([]), np.array([]) diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index 8584e81..ccc5d53 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -12,6 +12,7 @@ from swarmcg import swarmCG as scg from swarmcg import config +from swarmcg.shared import exceptions from swarmcg.shared.styling import EVALUATE_DESCR warnings.resetwarnings() @@ -35,23 +36,33 @@ def main(): # TODO: add missing checks -- if some are missing # TODO: factorize all checks and put them in global lib if not os.path.isfile(ns.aa_tpr_filename): - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot find coordinate file of the atomistic simulation\n(GRO, PDB, or other trajectory formats supported by MDAnalysis)') + msg = ( + "Cannot find coordinate file of the atomistic simulation" + "(GRO, PDB, or other trajectory formats supported by MDAnalysis)" + ) + raise exceptions.MissingCoordinateFile(msg) if not os.path.isfile(ns.aa_traj_filename): - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot find trajectory file of the atomistic simulation\n(XTC, TRR, or other trajectory formats supported by MDAnalysis)') + msg = ( + "Cannot find trajectory file of the atomistic simulation" + "(XTC, TRR, or other trajectory formats supported by MDAnalysis)" + ) + raise exceptions.MissingTrajectoryFile(msg) + if not os.path.isfile(ns.cg_map_filename): - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot find CG beads mapping file (NDX-like file format)') + msg = "Cannot find CG beads mapping file (NDX-like file format)" + raise exceptions.MissingIndexFile(msg) + if not os.path.isfile(ns.cg_itp_filename): - sys.exit(swarmcg.shared.styling.header_error + 'Cannot find ITP file of the CG model') + msg = "Cannot find ITP file of the CG model" + raise exceptions.MissingItpFile(msg) # check bonds scaling arguments conflicts if (ns.bonds_scaling != config.bonds_scaling and ns.min_bonds_length != config.min_bonds_length) or (ns.bonds_scaling != config.bonds_scaling and ns.bonds_scaling_str != config.bonds_scaling_str) or (ns.min_bonds_length != config.min_bonds_length and ns.bonds_scaling_str != config.bonds_scaling_str): - sys.exit( - swarmcg.shared.styling.header_error + 'Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length can be provided\nPlease check your parameters') - # if ns.bonds_scaling < 1: - # sys.exit(config.header_error+'Bonds scaling factor is inferior to 1, please check your parameters') + msg = ( + "Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length " + "can be provided. Please check your parameters" + ) + raise exceptions.ConflictingArgument(msg) print() print(swarmcg.shared.styling.sep_close) @@ -68,18 +79,11 @@ def main(): ns.atom_only = True else: ns.atom_only = False - # elif ns.cg_tpr_filename is not None and ns.cg_traj_filename is not None: - # ns.atom_only = False - # elif ns.cg_tpr_filename is not None or ns.cg_traj_filename is not None: - # if not os.path.isfile(str(ns.cg_tpr_filename)): - # sys.exit(config.header_error+'Cannot find portable run file of the coarse-grained simulation\n(TPR, or other portable formats supported by MDAnalysis)\nIf you want to look at distributions of your atomistic simulation\nexclusively, you have to omit both arguments -cg_tpr and -cg_traj') - # if not os.path.isfile(str(ns.cg_traj_filename)): - # sys.exit(config.header_error+'Cannot find trajectory file of the coarse-grained simulation (XTC, TRR, or other trajectory formats supported by MDAnalysis)\nIf you want to look at distributions of your atomistic simulation\nexclusively, you have to omit both arguments -aa_tpr and -cg_traj') try: if not ns.plot_filename.split('.')[-1] in ['eps', 'pdf', 'pgf', 'png', 'ps', 'raw', 'rgba', 'svg', 'svgz']: ns.plot_filename = ns.plot_filename+'.png' - except IndexError: + except IndexError as e: ns.plot_filename = ns.plot_filename+'.png' scg.create_bins_and_dist_matrices(ns) diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index d3943af..6d18685 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -13,6 +13,7 @@ import numpy as np from swarmcg import config +from swarmcg.shared import exceptions from swarmcg import swarmCG as scg from swarmcg.shared.styling import OPTIMISE_DESCR @@ -74,9 +75,11 @@ def main(): # avoid overwriting an output directory of a previous optimization run if os.path.isfile(ns.exec_folder) or os.path.isdir(ns.exec_folder): - sys.exit( - swarmcg.shared.styling.header_error + 'Provided output folder already exists, please delete existing folder manually or provide another folder name.' + msg = ( + "Provided output folder already exists, please delete existing folder " + "manually or provide another folder name." ) + raise exceptions.AvoidOverwritingFolder(msg) # check if we can find files at user-provided location(s) arg_entries = vars(ns) # dict view of the arguments namespace @@ -92,15 +95,22 @@ def main(): else: if ns.input_folder == '': data_folder_path = arg_entries[arg_entry] - sys.exit(swarmcg.shared.styling.header_error + 'Cannot find file for argument -' + args_names[i] + ' (expected at location: ' + data_folder_path + ')') + msg = ( + f"Cannot find file for argument - {args_names[i]} " + f"(expected at location: {data_folder_path})" + ) + raise FileNotFoundError(msg) # check that gromacs alias is correct with open(os.devnull, 'w') as devnull: try: subprocess.call(ns.gmx_path, stdout=devnull, stderr=devnull) except OSError: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot find GROMACS using alias \'' + ns.gmx_path + '\', please provide the right GROMACS alias or path') + msg = ( + f"Cannot find GROMACS using alias {ns.gmx_path}, please provide " + f"the right GROMACS alias or path" + ) + raise exceptions.ExecutableNotFound(msg) # check that ITP filename for the model to optimize is indeed included in the TOP file of the simulation directory # then find all TOP includes for copying files for simulations at each iteration @@ -108,8 +118,8 @@ def main(): with open(ns.top_input_filename, 'r') as fp: all_top_lines = fp.read() if ns.cg_itp_basename not in all_top_lines: - sys.exit( - swarmcg.shared.styling.header_error + 'The CG ITP model filename you provided is not included in your TOP file') + msg = "The CG ITP model filename you provided is not included in your TOP file." + raise exceptions.MDSimulationInputError(msg) top_lines = all_top_lines.split('\n') top_lines = [top_line.strip().split(';')[0] for top_line in top_lines] # split for comments @@ -126,10 +136,11 @@ def main(): # check bonds scaling arguments conflicts if (ns.bonds_scaling != config.bonds_scaling and ns.min_bonds_length != config.min_bonds_length) or (ns.bonds_scaling != config.bonds_scaling and ns.bonds_scaling_str != config.bonds_scaling_str) or (ns.min_bonds_length != config.min_bonds_length and ns.bonds_scaling_str != config.bonds_scaling_str): - sys.exit( - swarmcg.shared.styling.header_error + 'Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length can be provided\nPlease check your parameters') - # if ns.bonds_scaling < 1: - # sys.exit(config.header_error+'Bonds scaling factor is inferior to 1, please check your parameters') + msg = ( + "Only one of arguments -bonds_scaling, -bonds_scaling_str and " + "-min_bonds_length can be provided. Please check your parameters" + ) + raise exceptions.ConflictingArgument(msg) ################## # INITIALIZATION # @@ -202,8 +213,12 @@ def main(): if ns.bonds_scaling_str != config.bonds_scaling_str: sp_str = ns.bonds_scaling_str.split() if len(sp_str) % 2 != 0: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') + msg = ( + f"Cannot interpret argument -bonds_scaling_str as provided: {ns.bonds_scaling_str}. " + f"Please check your parameters, or help for an example" + ) + raise exceptions.InvalidArgument(msg) + ns.bonds_scaling_specific = dict() i = 0 try: @@ -211,32 +226,31 @@ def main(): geom_id = sp_str[i][1:] if sp_str[i][0].upper() == 'C': if int(geom_id) > ns.nb_constraints: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id exceeds the number of constraints groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') + info = "A constraint group id exceeds the number of constraints groups defined in the input CG ITP file." + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str, info) if not 'C'+geom_id in ns.bonds_scaling_specific: if float(sp_str[i+1]) < 0: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') + info = "You cannot provide negative values for average distribution length." + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str, info) ns.bonds_scaling_specific['C'+geom_id] = float(sp_str[i+1]) else: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') + info = f"A constraint group id is provided multiple times (id: {geom_id})" + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str, info) elif sp_str[i][0].upper() == 'B': if int(geom_id) > ns.nb_bonds: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id exceeds the number of bonds groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') + info = "A bond group id exceeds the number of bonds groups defined in the input CG ITP file." + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str, info) if not 'B'+geom_id in ns.bonds_scaling_specific: if float(sp_str[i+1]) < 0: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') + info = "You cannot provide negative values for average distribution length." + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str, info) ns.bonds_scaling_specific['B'+geom_id] = float(sp_str[i+1]) else: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') + info = f"A bond group id is provided multiple times (id: {geom_id})" + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str, info) i += 2 except ValueError: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str) # read atom mapped trajectory + find domains boundaries for values ranges (NOT the force constants, for which it is config/user defined already) print() diff --git a/swarmcg/shared/exceptions.py b/swarmcg/shared/exceptions.py index 385c687..d3049e7 100644 --- a/swarmcg/shared/exceptions.py +++ b/swarmcg/shared/exceptions.py @@ -1,3 +1,65 @@ header_error = "\n-- ! ERROR ! --\n" header_warning = "\n-- ! WARNING ! --\n" -header_gmx_error = "\n GMX ERROR MSG\n'+sep+'\n\n" \ No newline at end of file +header_gmx_error = "\n GMX ERROR MSG\n'+sep+'\n\n" + + +class BaseError(Exception): + """ + Base exception class. + """ + def __init__(self, msg): + self.message = header_error + msg + super().__init__(self.message) + + +class InvalidArgument(BaseError): + + base_msg = ( + "Cannot interpret argument -{name} as provided: {value}. " + "{additional_info}" + "Please check your parameters, or help for an example" + ) + + def __init__(self, argument, value, additional_info=""): + self.argument = argument + self.value = value + self.additional_info = additional_info + self.message = self.base_msg.format( + name=argument, value=value, additional_info=additional_info + ) + super().__init__(self.message) + + +class IncompleteOptimisationFile(BaseError): + pass + + +class MissingCoordinateFile(BaseError): + pass + + +class MissingTrajectoryFile(BaseError): + pass + + +class MissingItpFile(BaseError): + pass + + +class MissingIndexFile(BaseError): + pass + + +class ConflictingArgument(BaseError): + pass + +class ExecutableNotFound(BaseError): + pass + + +class AvoidOverwritingFolder(BaseError): + pass + + +class MDSimulationInputError(BaseError): + pass \ No newline at end of file From ad1945180f3e55eb802ea9d6342e3664ffcc517a Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Thu, 10 Sep 2020 13:21:04 +0200 Subject: [PATCH 08/40] Add tests --- swarmcg/shared/exceptions.py | 4 ++++ swarmcg/shared/utils.py | 25 +++++++++++++------------ tests/shared/test_utils.py | 13 +++++++++++++ 3 files changed, 30 insertions(+), 12 deletions(-) diff --git a/swarmcg/shared/exceptions.py b/swarmcg/shared/exceptions.py index d3049e7..cb7cdf7 100644 --- a/swarmcg/shared/exceptions.py +++ b/swarmcg/shared/exceptions.py @@ -34,6 +34,10 @@ class IncompleteOptimisationFile(BaseError): pass +class OptimisationResultsError(BaseError): + pass + + class MissingCoordinateFile(BaseError): pass diff --git a/swarmcg/shared/utils.py b/swarmcg/shared/utils.py index bfb380e..a9d3699 100644 --- a/swarmcg/shared/utils.py +++ b/swarmcg/shared/utils.py @@ -6,12 +6,12 @@ def forward_fill(arr, cond_value): - - # out = np.empty(len(arr)) + """ + Foward fill a list of values with the last valid one. + """ valid_val = None for i in range(len(arr)): if arr[i] != cond_value: - # out[i] = arr[i] valid_val = arr[i] else: j = i @@ -22,19 +22,20 @@ def forward_fill(arr, cond_value): valid_val = arr[j] break except IndexError as e: - msg = """{} Unexpected read of the optimization results, - please check that your simulations have not all been crashing - """.format(exceptions.header_error) - sys.exit(msg) + msg = ( + "Unexpected read of the optimization results, " + "please check that your simulations have not all been crashing" + ) + raise exceptions.OptimisationResultsError(msg) if valid_val is not None: - # out[i] = valid_val arr[i] = valid_val else: - msg = """All simulations crashed, nothing to display. - Please check the setup and settings of your optimization run - """ - sys.exit(msg) + msg = ( + "All simulations crashed, nothing to display. " + "Please check the setup and settings of your optimization run." + ) + raise exceptions.OptimisationResultsError(msg) return arr diff --git a/tests/shared/test_utils.py b/tests/shared/test_utils.py index 94e235d..a6c69be 100644 --- a/tests/shared/test_utils.py +++ b/tests/shared/test_utils.py @@ -1,7 +1,10 @@ +import pytest + import numpy as np from numpy.testing import assert_almost_equal from swarmcg.shared import utils +from swarmcg.shared.exceptions import OptimisationResultsError # TODO: add test on failure but needs dedicated exceptions rather and sys.exit @@ -18,6 +21,16 @@ def test_forward_fill(): assert result == expected +def test_forward_fill_fail(): + # given: + x = [1, 2, 10, 4, None, None, 10, 10] + + # when: + cond_value = None + with pytest.raises(OptimisationResultsError): + _ = utils.forward_fill(x, cond_value) + + def test_sma(): # given: x = np.arange(10) From 0972709bfd30495f04f619ffa8c641521d0a1e31 Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Thu, 10 Sep 2020 13:46:16 +0200 Subject: [PATCH 09/40] Add missing imports --- swarmcg/analyze_optimization.py | 2 +- swarmcg/swarmCG.py | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/swarmcg/analyze_optimization.py b/swarmcg/analyze_optimization.py index c72f948..70cdc5f 100644 --- a/swarmcg/analyze_optimization.py +++ b/swarmcg/analyze_optimization.py @@ -9,8 +9,8 @@ from shlex import quote as cmd_quote import matplotlib.pyplot as plt -from matplotlib.ticker import MaxNLocator import numpy as np +from matplotlib.ticker import MaxNLocator from swarmcg import config from swarmcg.shared import exceptions diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index b01fcaa..8137238 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -14,6 +14,7 @@ import matplotlib import matplotlib.pyplot as plt from pyemd import emd +import MDAnalysis as mda from scipy.spatial.distance import cdist from scipy.optimize import curve_fit From 54ee2f53d5e0522fb2f795630ce83abe9f4695ec Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Thu, 10 Sep 2020 14:59:19 +0200 Subject: [PATCH 10/40] Fix test --- tests/shared/test_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/shared/test_utils.py b/tests/shared/test_utils.py index a6c69be..a57f4d5 100644 --- a/tests/shared/test_utils.py +++ b/tests/shared/test_utils.py @@ -23,7 +23,7 @@ def test_forward_fill(): def test_forward_fill_fail(): # given: - x = [1, 2, 10, 4, None, None, 10, 10] + x = [None, None] # when: cond_value = None From a9e7ae332356b3afd32cd78d8fbe8d55a8e77e6d Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Thu, 10 Sep 2020 15:54:10 +0200 Subject: [PATCH 11/40] Reintroduce main for entrypoints --- setup.py | 14 +++++++------- swarmcg/analyze_optimization.py | 7 ++++--- swarmcg/evaluate_model.py | 17 +++-------------- swarmcg/optimize_model.py | 6 +++--- 4 files changed, 17 insertions(+), 27 deletions(-) diff --git a/setup.py b/setup.py index 5176a00..5865596 100644 --- a/setup.py +++ b/setup.py @@ -9,13 +9,13 @@ name='swarm-cg', version=swarmcg.__version__, description='Tools for automatic parametrization of bonded terms in coarse-grained molecular models, with respect to an all-atom trajectory', - author='Charly Empereur-mot', - author_email='charly.empereur@gmail.com', + author='Charly Empereur-mot', + author_email='charly.empereur@gmail.com', license='MIT', - url = 'https://github.com/GMPavanLab/Swarm-CG', + url = 'https://github.com/GMPavanLab/Swarm-CG', long_description=README, long_description_content_type="text/markdown", - keywords = ['gromacs', 'coarse-grain', 'molecular model', 'optimization', 'force field'], + keywords=['gromacs', 'coarse-grain', 'molecular model', 'optimization', 'force field'], packages=find_packages(include=['swarmcg', 'swarmcg.*']), install_requires=[ 'numpy>=1.16.4', @@ -27,9 +27,9 @@ ], entry_points={ 'console_scripts': [ - 'scg_optimize=swarmcg.optimize_model:main', - 'scg_evaluate=swarmcg.evaluate_model:main', - 'scg_monitor=swarmcg.analyze_optimization:main' + 'scg_optimize=swarmcg.optimize_model:main', + 'scg_evaluate=swarmcg.evaluate_model:main', + 'scg_monitor=swarmcg.analyze_optimization:main' ] } ) diff --git a/swarmcg/analyze_optimization.py b/swarmcg/analyze_optimization.py index 70cdc5f..0bd982e 100644 --- a/swarmcg/analyze_optimization.py +++ b/swarmcg/analyze_optimization.py @@ -20,7 +20,7 @@ warnings.resetwarnings() -def main(ns): +def run(ns): # TODO: print some text to tell user if opti run finished or not -- then we can only look at the results files, not the running processes on the machine @@ -612,7 +612,8 @@ def main(ns): print('Wrote visual optimization summary file at location:\n ', os.path.normpath(ns.opti_dirname+'/'+ns.plot_filename)) print() -if __name__ == '__main__': + +def main(): print(swarmcg.shared.styling.header_package( ' Module: Optimization run analysis\n')) @@ -660,6 +661,6 @@ def main(ns): print(swarmcg.shared.styling.sep_close) print() - main(ns) + run(ns) diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index ccc5d53..ae55e4b 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -19,7 +19,7 @@ matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation -def main(): +def run(ns): from numpy import VisibleDeprecationWarning warnings.filterwarnings("ignore", category=VisibleDeprecationWarning) # filter MDAnalysis + numpy deprecation stuff that is annoying @@ -90,18 +90,7 @@ def main(): scg.compare_models(ns, manual_mode=True, calc_sasa=False) -if __name__ == '__main__': - - # command for tests - # ./evaluate_model.py -aa_tpr ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.tpr -aa_traj ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.xtc -cg_map ../DATA_MDL/Mono_B/MOB_atom_mapping/atomistic/MOB_mapping.ndx -cg_itp MOB_HUMAN_SIM/Mono_B.itp -cg_tpr MOB_HUMAN_SIM/cg_solvated.tpr -cg_traj MOB_HUMAN_SIM/cg_solvated.xtc - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.tpr -aa_traj ../DATA_MDL/Mono_B/atomistic/MOB_atomistic_solvated.xtc -cg_map ../DATA_MDL/Mono_B/MOB_atom_mapping/atomistic/MOB_mapping.ndx -cg_itp MOB_HUMAN_SIM/Mono_B.itp - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/fake_for_test.tpr -aa_traj ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/ATOM_TRAJ.xtc -cg_map ../DATA_MDL/BTA/BTA_atom_mapping/atomistic/index_bta.ndx -cg_itp BTA_HUMAN_SIM/bta_P3.itp -cg_tpr BTA_HUMAN_SIM/cg_solvated.tpr -cg_traj BTA_HUMAN_SIM/cg_solvated.xtc - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/POPC/AA/topol.tpr -aa_traj ../DATA_MDL/POPC/AA/traj.trr -cg_map ../DATA_MDL/POPC/CG/mapping.ndx -cg_itp POPC_CG_SIM/martini_v2.0_POPC_02.itp -cg_tpr POPC_CG_SIM/cg_solvated.tpr -cg_traj POPC_CG_SIM/cg_solvated.xtc - - # ./evaluate_model.py -aa_tpr ../DATA_MDL/B3T/AA/topol.tpr -aa_traj ../DATA_MDL/B3T/AA/traj_atom.xtc -cg_map ../DATA_MDL/B3T/CG/MAPPING.ndx -cg_itp ../DATA_MDL/B3T/CG/MARTINI/B3T_CG.itp -cg_tpr B3T_HUMAN_SIM/produced.tpr -cg_traj B3T_HUMAN_SIM/produced.xtc +def main(): print(swarmcg.shared.styling.header_package( ' Module: Model bonded terms assessment\n')) @@ -213,4 +202,4 @@ def main(): print('Working directory:', os.getcwd()) print('Command line:', input_cmdline) - main(ns) \ No newline at end of file + run(ns) \ No newline at end of file diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 6d18685..1569420 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -20,7 +20,7 @@ warnings.resetwarnings() -def main(): +def run(ns): from numpy import VisibleDeprecationWarning warnings.filterwarnings("ignore", category=VisibleDeprecationWarning) # filter MDAnalysis + numpy deprecation stuff that is annoying @@ -544,7 +544,7 @@ def main(): print() -if __name__ == '__main__': +def main(): print( swarmcg.shared.styling.header_package(' Module: CG model optimization\n')) @@ -735,5 +735,5 @@ def main(): print('Command line:', input_cmdline) print('Results directory:', ns.exec_folder) - main(ns) + run(ns) From cbf9f989058a26d0313c399701bcebb652b405ab Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Fri, 11 Sep 2020 11:05:23 +0200 Subject: [PATCH 12/40] Adding exceptions to swarmCG --- swarmcg/analyze_optimization.py | 4 +-- swarmcg/config.py | 16 +++++++----- swarmcg/evaluate_model.py | 3 +-- swarmcg/optimize_model.py | 4 +-- swarmcg/shared/exceptions.py | 4 +++ swarmcg/swarmCG.py | 44 ++++++++++++++------------------- 6 files changed, 36 insertions(+), 39 deletions(-) diff --git a/swarmcg/analyze_optimization.py b/swarmcg/analyze_optimization.py index 0bd982e..3e8185b 100644 --- a/swarmcg/analyze_optimization.py +++ b/swarmcg/analyze_optimization.py @@ -1,8 +1,5 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings - -import swarmcg.shared.styling - warnings.filterwarnings("ignore") import os, sys from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS @@ -12,6 +9,7 @@ import numpy as np from matplotlib.ticker import MaxNLocator +import swarmcg.shared.styling from swarmcg import config from swarmcg.shared import exceptions from swarmcg.shared.styling import ANALYSE_DESCR diff --git a/swarmcg/config.py b/swarmcg/config.py index 91c5233..c0eb77e 100644 --- a/swarmcg/config.py +++ b/swarmcg/config.py @@ -59,12 +59,16 @@ # gromacs functions that are properly treated at the moment # if we find a function that is not handled, program will exit with an appropriate error message -handled_constraints_functions = [1] -handled_bonds_functions = [1] -handled_angles_functions = [1, 2] -handled_dihedrals_functions = [1, 2, 4] -dihedral_func_with_mult = [1, 4] # these functions use 3 parameters, the last one being multiplicity (if it's omitted gromacs will use 1 by default, we reproduce this behavior) -# TODO: handle dihedral function 9 correctly so that different potentials can be stacked for the same beads -- this is the primary purpose of function 9 !! +# TODO: handle dihedral function 9 correctly so that different potentials can be stacked +# TODO: for the same beads -- this is the primary purpose of function 9 !! +handled_functions = { + 'contraint': [1], + 'bond': [1], + 'angle': [1, 2], + 'dihedral': [1, 2, 4], + 'dihedral_with_mult': [1, 4] + # these functions use 3 parameters, the last one being multiplicity (if it's omitted gromacs will use 1 by default, we reproduce this behavior) +} # plots display parameters use_hists = False # hists are not implemented in a way that they will be displayed with left and right borders, as it is already the case for bonds diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index ae55e4b..5e5c481 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -1,8 +1,6 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings -import swarmcg.shared.styling - warnings.filterwarnings("ignore") import os, sys from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS @@ -10,6 +8,7 @@ import matplotlib +import swarmcg.shared.styling from swarmcg import swarmCG as scg from swarmcg import config from swarmcg.shared import exceptions diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 1569420..3f817a9 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -1,8 +1,5 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings - -import swarmcg.shared.styling - warnings.filterwarnings("ignore") import os, sys, shutil, subprocess, time, copy, contextlib from argparse import ArgumentParser, RawTextHelpFormatter, SUPPRESS @@ -12,6 +9,7 @@ from fstpso import FuzzyPSO import numpy as np +import swarmcg.shared.styling from swarmcg import config from swarmcg.shared import exceptions from swarmcg import swarmCG as scg diff --git a/swarmcg/shared/exceptions.py b/swarmcg/shared/exceptions.py index cb7cdf7..fcab715 100644 --- a/swarmcg/shared/exceptions.py +++ b/swarmcg/shared/exceptions.py @@ -66,4 +66,8 @@ class AvoidOverwritingFolder(BaseError): class MDSimulationInputError(BaseError): + pass + + +class MissformattedFile(BaseError): pass \ No newline at end of file diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 8137238..5b427da 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -1,8 +1,5 @@ # some numpy version have this ufunc warning at import + many packages call numpy and display annoying warnings import warnings - -import swarmcg.shared.styling - warnings.filterwarnings("ignore") import sys, re, random, os, shutil, subprocess, signal, time, contextlib import warnings, collections @@ -13,14 +10,14 @@ import numpy as np import matplotlib import matplotlib.pyplot as plt -from pyemd import emd import MDAnalysis as mda - +from pyemd import emd from scipy.spatial.distance import cdist from scipy.optimize import curve_fit -from . import config -from .shared import utils +from swarmcg import config +from swarmcg.shared import utils +from swarmcg.shared import exceptions matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation warnings.resetwarnings() @@ -48,7 +45,7 @@ def set_MDA_backend(ns): # draw random float between given range and apply rounding to given digit def draw_float(low, high, dg_rnd): - + return round(random.uniform(low, high), dg_rnd) # low and high included @@ -124,7 +121,7 @@ def draw_float(low, high, dg_rnd): # ns.all_atoms[atom_id_2]['conn'].add(atom_id_1) # print('Net charge in the reference all atom model:', round(total_charge, 4)) - + # return @@ -138,7 +135,6 @@ def load_aa_data(ns): molname_atom_group = ns.aa_universe.atoms[0].fragment # select the AA connected graph for the first moltype found in TPR ns.all_aa_mols.append(molname_atom_group) - # print(dir(molname_atom_group.atoms[0])) # for dev, display properties # atoms and their attributes for i in range(len(molname_atom_group)): @@ -193,21 +189,19 @@ def verify_handled_functions(geom, func_obj, line_obj): try: func = int(func_obj) except (ValueError, IndexError): - sys.exit( - swarmcg.shared.styling.header_error + 'Error while reading CG ITP file at line ' + str(line_obj) + ', please check this file') - - if geom == 'constraint' and func not in config.handled_constraints_functions: - sys.exit( - swarmcg.shared.styling.header_error + 'Error while reading constraint function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these constraint potential functions: ' + ", ".join(map(str, config.handled_constraints_functions))) - elif geom == 'bond' and func not in config.handled_bonds_functions: - sys.exit( - swarmcg.shared.styling.header_error + 'Error while reading bond function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these bond potential functions: ' + ", ".join(map(str, config.handled_bonds_functions))) - elif geom == 'angle' and func not in config.handled_angles_functions: - sys.exit( - swarmcg.shared.styling.header_error + 'Error while reading angle function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these angle potential functions: ' + ", ".join(map(str, config.handled_angles_functions))) - elif geom == 'dihedral' and func not in config.handled_dihedrals_functions: - sys.exit( - swarmcg.shared.styling.header_error + 'Error while reading dihedral function in CG ITP file at line ' + str(line_obj) + '\nThis potential function is not implemented in Swarm-CG at the moment\nPlease use one of these dihedral potential functions: ' + ", ".join(map(str, config.handled_dihedrals_functions))) + msg = ( + f"Error while reading CG ITP file at line {line_obj}, please check this file" + ) + raise exceptions.MissformattedFile(msg) + + if func not in config.handled_functions[geom]: + funstions_str = ", ".join(map(str, config.handled_functions[geom])) + msg = ( + f"Error while reading {geom} function in CG ITP file at line {line_obj}. " + f"This potential function is not implemented in Swarm-CG at the moment. " + f"Please use one of these constraint potential functions: {funstions_str}" + ) + raise exceptions.MissformattedFile(msg) return func From 6d15ec6fad6916c991e134716aa46456ffcd64f0 Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Fri, 11 Sep 2020 12:13:31 +0200 Subject: [PATCH 13/40] More exceptions --- swarmcg/shared/exceptions.py | 7 +- swarmcg/shared/potentials.py | 0 swarmcg/swarmCG.py | 253 ++++++++++++++++++++++++----------- 3 files changed, 181 insertions(+), 79 deletions(-) create mode 100644 swarmcg/shared/potentials.py diff --git a/swarmcg/shared/exceptions.py b/swarmcg/shared/exceptions.py index fcab715..c424b07 100644 --- a/swarmcg/shared/exceptions.py +++ b/swarmcg/shared/exceptions.py @@ -17,7 +17,7 @@ class InvalidArgument(BaseError): base_msg = ( "Cannot interpret argument -{name} as provided: {value}. " "{additional_info}" - "Please check your parameters, or help for an example" + "Please check your parameters, or look for help in an example." ) def __init__(self, argument, value, additional_info=""): @@ -38,7 +38,7 @@ class OptimisationResultsError(BaseError): pass -class MissingCoordinateFile(BaseError): +class MissingInputFileError(BaseError): pass @@ -70,4 +70,7 @@ class MDSimulationInputError(BaseError): class MissformattedFile(BaseError): + pass + +class ComputationError(BaseError) pass \ No newline at end of file diff --git a/swarmcg/shared/potentials.py b/swarmcg/shared/potentials.py new file mode 100644 index 0000000..e69de29 diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 5b427da..2f9ea0f 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -265,8 +265,12 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['constraint'][ns.nb_constraints]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:2]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit( - swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [constraints] section, please check this file') + msg = ( + "Incorrect reading of the CG ITP file within [constraints] section. " + "Please check this file." + ) + raise exceptions.MissformattedFile(msg) + func = verify_handled_functions('constraint', sp_itp_line[2], i+1) ns.cg_itp['constraint'][ns.nb_constraints]['funct'].append(func) ns.cg_itp['constraint'][ns.nb_constraints]['value'].append(float(sp_itp_line[3])) @@ -289,8 +293,12 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['bond'][ns.nb_bonds]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:2]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit( - swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [bonds] section, please check this file') + msg = ( + "Incorrect reading of the CG ITP file within [bonds] section. " + "Please check this file." + ) + raise exceptions.MissformattedFile(msg) + func = verify_handled_functions('bond', sp_itp_line[2], i+1) ns.cg_itp['bond'][ns.nb_bonds]['funct'].append(func) ns.cg_itp['bond'][ns.nb_bonds]['value'].append(float(sp_itp_line[3])) @@ -314,8 +322,12 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['angle'][ns.nb_angles]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:3]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit( - swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [angles] section, please check this file') + msg = ( + "Incorrect reading of the CG ITP file within [angles] section. " + "Please check this file." + ) + raise exceptions.MissformattedFile(msg) + func = verify_handled_functions('angle', sp_itp_line[3], i+1) ns.cg_itp['angle'][ns.nb_angles]['funct'].append(func) ns.cg_itp['angle'][ns.nb_angles]['value'].append(float(sp_itp_line[4])) @@ -339,8 +351,12 @@ def read_cg_itp_file(ns, itp_lines): try: ns.cg_itp['dihedral'][ns.nb_dihedrals]['beads'].append([int(bead_id)-1 for bead_id in sp_itp_line[0:4]]) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except ValueError: - sys.exit( - swarmcg.shared.styling.header_error + 'Incorrect reading of the CG ITP file within [dihedrals] section, please check this file') + msg = ( + "Incorrect reading of the CG ITP file within [dihedrals] section. " + "Please check this file." + ) + raise exceptions.MissformattedFile(msg) + func = verify_handled_functions('dihedral', sp_itp_line[4], i+1) ns.cg_itp['dihedral'][ns.nb_dihedrals]['funct'].append(func) ns.cg_itp['dihedral'][ns.nb_dihedrals]['value'].append(float(sp_itp_line[5])) # issue happens here for functions that are not handled @@ -368,6 +384,13 @@ def read_cg_itp_file(ns, itp_lines): # error handling, verify that funct, value and fct are all identical within the group, as they should be, and reduce arrays to single elements # TODO: make these messages more clear and CORRECT for the dihedral function handling -- also explain this is the current Opti.CG implementation, function 9 might come in next version # TODO: check what kind of error or processing is done when a correct line is duplicated within a group ?? probably it goes on in a bad way + + msg = ( + f"In the provided CG ITP file {geom} have been grouped, but {geom} group " + f"{str(grp_geom + 1)} holds lines that have different parameters. Parameters should be " + f"identical within a group, only CG beads IDs should differ. " + f"Please correct the CG ITP file and separate groups using a blank or commented line" + ) for geom in ['constraint']: # constraints only for grp_geom in range(len(ns.cg_itp[geom])): for var in ['funct', 'value']: @@ -375,8 +398,7 @@ def read_cg_itp_file(ns, itp_lines): if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit( - swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within a ' + geom + ' group, only CG beads IDs should differ\nPlease correct the CG ITP file and separate groups using a blank or commented line') + raise exceptions.MissformattedFile(msg) for geom in ['bond', 'angle']: # bonds and angles only for grp_geom in range(len(ns.cg_itp[geom])): @@ -385,8 +407,7 @@ def read_cg_itp_file(ns, itp_lines): if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit( - swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a ' + geom + ' group\nPlease correct the CG ITP file and separate groups using a blank or commented line') + raise exceptions.MissformattedFile(msg) for geom in ['dihedral']: # dihedrals only for grp_geom in range(len(ns.cg_itp[geom])): @@ -395,16 +416,15 @@ def read_cg_itp_file(ns, itp_lines): if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit( - swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a ' + geom + ' group\nPlease correct the CG ITP file and separate groups using a blank or commented line') + raise exceptions.MissformattedFile(msg) + for var in ['mult']: var_set = set(ns.cg_itp[geom][grp_geom][var]) if len(var_set) == 1: ns.cg_itp[geom][grp_geom][var] = var_set.pop() else: - sys.exit( - swarmcg.shared.styling.header_error + 'In the provided CG ITP file ' + geom + ' have been grouped, but ' + geom + ' group ' + str(grp_geom + 1) + ' holds ' + geom + ' lines that have different parameters\nParameters should be identical within groups, only CG beads IDs should differ between lines of a ' + geom + ' group') - + raise exceptions.MissformattedFile(msg) + ns.nb_constraints += 1 ns.nb_bonds += 1 ns.nb_angles += 1 @@ -443,8 +463,14 @@ def read_ndx_atoms2beads(ns): try: lines_read += 1 if lines_read > 1: - sys.exit( - swarmcg.shared.styling.header_error + 'A section of the CG beads mapping (NDX) file has multiple lines, while Swarm-CG accepts only one line per section\nPlease use a single line for IDs under section ' + current_section + ' near line ' + str(i + 1)) + msg = ( + f"A section of the CG beads mapping (NDX) file has multiple lines, " + f"while Swarm-CG accepts only one line per section. Please use a " + f"single line for IDs under section {current_section} " + f"near line {str(i + 1)}" + ) + raise exceptions.MissformattedFile(msg) + bead_atoms_id = [int(atom_id)-1 for atom_id in ndx_line.split()] # retrieve indexing from 0 for atoms IDs for MDAnalysis ns.all_beads[bead_id]['atoms_id'].extend(bead_atoms_id) # all atoms included in current bead @@ -453,11 +479,19 @@ def read_ndx_atoms2beads(ns): bead_id += 1 except NameError: - sys.exit( - swarmcg.shared.styling.header_error + 'The CG beads mapping (NDX) file does NOT seem to contain CG beads sections, please verify the input mapping\nThe expected format is Gromacs NDX') + msg = ( + "The CG beads mapping (NDX) file does NOT seem to contain CG beads " + "sections. Please verify the input mapping. The expected format is " + "Gromacs NDX." + ) + raise exceptions.MissformattedFile(msg) except ValueError: # non-integer atom ID provided - sys.exit( - swarmcg.shared.styling.header_error + 'Incorrect reading of the sections content in the CG beads mapping (NDX) file\nFound non-integer values for some IDs at line ' + str(i + 1) + ' under section ' + current_section) + msg = ( + f"Incorrect reading of the sections content in the CG beads mapping " + f"(NDX) file. Found non-integer values for some IDs at line " + f"{str(i + 1)} under section {current_section}." + ) + raise exceptions.MissformattedFile(msg) return @@ -494,8 +528,12 @@ def get_beads_MDA_atomgroups(ns): ns.mda_weights_atom_grps[bead_id] = np.array([ns.atom_w[bead_id][atom_id]*ns.aa_universe.atoms[atom_id].mass for atom_id in ns.atom_w[bead_id]]) # ns.mda_weights_atom_grps[bead_id] = np.array([ns.atom_w[bead_id][atom_id]*ns.all_atoms[atom_id]['atom_mass'] for atom_id in ns.atom_w[bead_id]]) except IndexError as e: - sys.exit( - swarmcg.shared.styling.header_error + 'An ID present in your mapping (NDX) file could not be found in the AA trajectory, please check your mapping (NDX) file\nSee the error below to understand which ID (here 0-indexed) could not be found:\n ' + str(e)) + msg = ( + f"An ID present in your mapping (NDX) file could not be found in the AA trajectory. " + f"Please check your mapping (NDX) file. See the error below to understand which " + f"ID (here 0-indexed) could not be found: {str(e)}" + ) + raise exceptions.MissformattedFile(msg) return @@ -555,7 +593,7 @@ def compute_Rg(ns, traj_type): # pass else: - sys.exit('Code error compute_Rg') + raise RuntimeError('Code error compute_Rg') return @@ -589,7 +627,7 @@ def exec_gmx(gmx_cmd): def compute_SASA(ns, traj_type): if traj_type == 'AA': - sys.exit('Compute_SASA not implemented for AA atm') + raise exceptions.InvalidArgument('Compute_SASA not implemented for AA atm') elif traj_type == 'AA_mapped': @@ -685,8 +723,11 @@ def compute_SASA(ns, traj_type): non_zero_return_code = True if non_zero_return_code: - print_stdout_forced('There were some errors while calculating SASA for AA-mapped trajectory, please check the error messages displayed above') - sys.exit() # exit, otherwise it will try to calculate AA-mapped SASA at every iteration + msg = ( + "There were some errors while calculating SASA for AA-mapped trajectory. " + "Please check the error messages displayed above." + ) + raise exceptions.ComputationError(msg) else: sasa_aa_mapped_per_frame = read_xvg_col(ns.aa_mapped_sasa_filename, 1) ns.sasa_aa_mapped = round(np.mean(sasa_aa_mapped_per_frame), 2) @@ -721,7 +762,7 @@ def compute_SASA(ns, traj_type): # print_stdout_forced('COMPUTED CG SASA:', ns.sasa_cg) else: - sys.exit('Code error compute SASA') + raise exceptions.ComputationError('Code error compute SASA') return @@ -734,8 +775,11 @@ def update_cg_itp_obj(ns, parameters_set, update_type): elif update_type == 2: # cycles optimized itp_obj = ns.opti_itp else: - sys.exit( - swarmcg.shared.styling.header_error + 'Code error in function update_cg_itp_obj, please consider opening an issue on GitHub at ' + config.github_url) + msg = ( + f"Code error in function update_cg_itp_obj, please consider opening an issue on GitHub " + f"at {config.github_url}." + ) + raise exceptions.InvalidArgument(msg) for i in range(ns.opti_cycle['nb_geoms']['constraint']): itp_obj['constraint'][i]['value'] = round(parameters_set[i], 3) # constraint - distance @@ -937,7 +981,8 @@ def get_search_space_boundaries(ns): elif ns.cg_itp['angle'][grp_angle]['funct'] == 2: search_space_boundaries.extend([[config.default_min_fct_angles, ns.default_max_fct_angles_opti_f2]]) else: - sys.exit('Code error in force constants calculations, in the angles block') + msg = "Code error in force constants calculations, in the angles block." + raise exceptions.InvalidArgument(msg) if ns.opti_cycle['nb_geoms']['dihedral'] > 0: if ns.exec_mode == 1: @@ -949,7 +994,8 @@ def get_search_space_boundaries(ns): elif ns.cg_itp['dihedral'][grp_dihedral]['funct'] in [1, 4, 9]: search_space_boundaries.extend([[-ns.default_abs_range_fct_dihedrals_opti_func_with_mult, ns.default_abs_range_fct_dihedrals_opti_func_with_mult]]) else: - sys.exit('Code error in force constants calculations, in the dihedrals block') + msg = "Code error in force constants calculations, in the dihedrals block." + raise exceptions.InvalidArgument(msg) return search_space_boundaries @@ -983,7 +1029,12 @@ def get_initial_guess_list(ns, nb_particles): elif ns.cg_itp['angle'][i]['funct'] == 2: fct_angles.append(min(max(ns.out_itp['angle'][i]['fct'], config.default_min_fct_angles), ns.default_max_fct_angles_opti_f2)) # angles force constants else: - sys.exit('Code error during force constants range definition while getting the initial guesses from BI') + msg = ( + "Code error during force constants range definition while getting the initial " + "guesses from BI." + ) + raise exceptions.InvalidArgument(msg) + input_guess.extend(fct_angles) if ns.exec_mode == 1: @@ -1116,7 +1167,12 @@ def get_initial_guess_list(ns, nb_particles): elif ns.cg_itp['angle'][j]['funct'] == 2: draw_high = min(max(ns.out_itp['angle'][j]['fct']*(1+ns.fct_guess_fact*emd_err_fact), ns.out_itp['angle'][j]['fct']+config.fct_guess_min_flat_diff_angles), ns.default_max_fct_angles_opti_f2) else: - sys.exit('Code error during force constants range definition for angles during particles initialization') + msg = ( + "Code error during force constants range definition for angles during particles " + "initialization guesses from BI." + ) + raise exceptions.InvalidArgument(msg) + init_guess.append(draw_float(draw_low, draw_high, 3)) # dihedrals values @@ -1531,8 +1587,11 @@ def perform_BI(ns): popt[0] = 30 else: - sys.exit( - swarmcg.shared.styling.header_error + 'Code error, we should never arrive here because functions have been checked during CG ITP file reading') + msg = ( + "Code error, we should never arrive here because functions have been " + "checked during CG ITP file reading." + ) + raise exceptions.InvalidArgument(msg) # here we just update the force constant, angle value is already set to the average of distribution ns.out_itp['angle'][grp_angle]['fct'] = min(max(popt[0], config.default_min_fct_angles), config.default_max_fct_angles_bi) # stay within specified range for force constants @@ -1570,8 +1629,11 @@ def perform_BI(ns): popt[0] = abs(popt[0]) # just to be safe, in case the fit yielded negative fct values but this is very unlikely since we provide good starting parameters for the fit else: - sys.exit( - swarmcg.shared.styling.header_error + 'Code error, we should never arrive here because functions have been checked during CG ITP file reading') + msg = ( + "Code error, we should never arrive here because functions have been checked " + "during CG ITP file reading." + ) + raise exceptions.InvalidArgument(msg) if ns.exec_mode == 1: ns.out_itp['dihedral'][grp_dihedral]['value'] = np.rad2deg(popt[1]) @@ -1597,43 +1659,80 @@ def process_scaling_str(ns): # process specific bonds scaling string, if provided ns.bonds_scaling_specific = None if ns.bonds_scaling_str != config.bonds_scaling_str: - sp_str = ns.bonds_scaling_str.split() - if len(sp_str) % 2 != 0: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') - ns.bonds_scaling_specific = dict() - i = 0 - try: - while i < len(sp_str): - geom_id = sp_str[i][1:] - if sp_str[i][0].upper() == 'C': - if int(geom_id) > ns.nb_constraints: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id exceeds the number of constraints groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') - if not 'C'+geom_id in ns.bonds_scaling_specific: - if float(sp_str[i+1]) < 0: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') - ns.bonds_scaling_specific['C'+geom_id] = float(sp_str[i+1]) - else: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA constraint group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') - elif sp_str[i][0].upper() == 'B': - if int(geom_id) > ns.nb_bonds: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id exceeds the number of bonds groups defined in the input CG ITP file\nPlease check your parameters, or help for an example') - if not 'B'+geom_id in ns.bonds_scaling_specific: - if float(sp_str[i+1]) < 0: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nYou cannot provide negative values for average distribution length\nPlease check your parameters, or help for an example') - ns.bonds_scaling_specific['B'+geom_id] = float(sp_str[i+1]) - else: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nA bond group id is provided multiple times (id: ' + str(geom_id) + ')\nPlease check your parameters, or help for an example') - i += 2 - except ValueError: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot interpret argument -bonds_scaling_str as provided: \'' + ns.bonds_scaling_str + '\'\nPlease check your parameters, or help for an example') + sp_str = ns.bonds_scaling_str.split() + if len(sp_str) % 2 != 0: + msg = ( + f"Cannot interpret argument -bonds_scaling_str as provided: {ns.bonds_scaling_str}. " + f"Please check your parameters, or look for help in an example." + ) + raise ValueError(msg) + + ns.bonds_scaling_specific = dict() + i = 0 + try: + while i < len(sp_str): + geom_id = sp_str[i][1:] + if sp_str[i][0].upper() == 'C': + if int(geom_id) > ns.nb_constraints: + info = ( + f"A constraint group id exceeds the number of " + f"constraints groups defined in the input CG ITP file. " + ) + raise exceptions.InvalidArgument( + 'bonds_scaling_str', ns.bonds_scaling_str, info + ) + + if not 'C' + geom_id in ns.bonds_scaling_specific: + if float(sp_str[i + 1]) < 0: + info = ( + f"You cannot provide negative values for average distribution length." + ) + raise exceptions.InvalidArgument( + 'bonds_scaling_str', ns.bonds_scaling_str, info + ) + + ns.bonds_scaling_specific['C'+ geom_id] = float(sp_str[i + 1]) + else: + info = ( + f"A constraint group id is provided multiple " + f"times (id: { str(geom_id)}." + ) + raise exceptions.InvalidArgument( + 'bonds_scaling_str', ns.bonds_scaling_str, info + ) + + elif sp_str[i][0].upper() == 'B': + if int(geom_id) > ns.nb_bonds: + info = ( + f"A bond group id exceeds the number of bonds groups defined in the " + f"input CG ITP file." + ) + raise exceptions.InvalidArgument( + 'bonds_scaling_str', ns.bonds_scaling_str, info + ) + + if not 'B' + geom_id in ns.bonds_scaling_specific: + if float(sp_str[i + 1]) < 0: + info = ( + f"You cannot provide negative values for average distribution " + f"length." + ) + raise exceptions.InvalidArgument( + 'bonds_scaling_str', ns.bonds_scaling_str, info + ) + + ns.bonds_scaling_specific['B'+geom_id] = float(sp_str[i+1]) + else: + info = ( + f"A bond group id is provided multiple times (id: {str(geom_id)})." + ) + raise exceptions.InvalidArgument( + 'bonds_scaling_str', ns.bonds_scaling_str, info + ) + i += 2 + + except ValueError: + raise exceptions.InvalidArgument('bonds_scaling_str', ns.bonds_scaling_str, '') return From b14ee79403371f8a1b075674b75128bdc756d7b6 Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Fri, 11 Sep 2020 12:51:46 +0200 Subject: [PATCH 14/40] Finished exceptions --- swarmcg/evaluate_model.py | 2 +- swarmcg/optimize_model.py | 2 +- swarmcg/shared/exceptions.py | 15 ++++++- swarmcg/shared/io.py | 0 swarmcg/swarmCG.py | 85 ++++++++++++++++++++++++++---------- 5 files changed, 78 insertions(+), 26 deletions(-) create mode 100644 swarmcg/shared/io.py diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index 5e5c481..0d99ab8 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -61,7 +61,7 @@ def run(ns): "Only one of arguments -bonds_scaling, -bonds_scaling_str and -min_bonds_length " "can be provided. Please check your parameters" ) - raise exceptions.ConflictingArgument(msg) + raise exceptions.InputArgumentError(msg) print() print(swarmcg.shared.styling.sep_close) diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 3f817a9..9d01829 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -138,7 +138,7 @@ def run(ns): "Only one of arguments -bonds_scaling, -bonds_scaling_str and " "-min_bonds_length can be provided. Please check your parameters" ) - raise exceptions.ConflictingArgument(msg) + raise exceptions.InputArgumentError(msg) ################## # INITIALIZATION # diff --git a/swarmcg/shared/exceptions.py b/swarmcg/shared/exceptions.py index c424b07..b5ab8d8 100644 --- a/swarmcg/shared/exceptions.py +++ b/swarmcg/shared/exceptions.py @@ -12,6 +12,15 @@ def __init__(self, msg): super().__init__(self.message) +class ExecError(Exception): + """ + Base exception class. + """ + def __init__(self, msg): + self.message = header_gmx_error + msg + super().__init__(self.message) + + class InvalidArgument(BaseError): base_msg = ( @@ -54,9 +63,10 @@ class MissingIndexFile(BaseError): pass -class ConflictingArgument(BaseError): +class InputArgumentError(BaseError): pass + class ExecutableNotFound(BaseError): pass @@ -72,5 +82,6 @@ class MDSimulationInputError(BaseError): class MissformattedFile(BaseError): pass -class ComputationError(BaseError) + +class ComputationError(ExecError): pass \ No newline at end of file diff --git a/swarmcg/shared/io.py b/swarmcg/shared/io.py new file mode 100644 index 0000000..e69de29 diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 2f9ea0f..46af709 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -1758,8 +1758,8 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False read_cg_itp_file(ns, itp_lines) process_scaling_str(ns) except UnicodeDecodeError: - sys.exit( - swarmcg.shared.styling.header_error + 'Cannot read CG ITP, it seems you provided a binary file.') + msg = "Cannot read CG ITP, it seems you provided a binary file." + raise exceptions.MissformattedFile(msg) # if we do not have reference already from the optimization procedure if manual_mode: @@ -1862,8 +1862,12 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False domain_max = max(constraints[grp_constraint]['AA']['x'][-1], constraints[grp_constraint]['CG']['x'][-1]) avg_diff_grp_constraints.append(emd(constraints[grp_constraint]['AA']['hist'], constraints[grp_constraint]['CG']['hist'], ns.bins_constraints_dist_matrix) * ns.bonds2angles_scoring_factor) except IndexError: - sys.exit( - swarmcg.shared.styling.header_error + 'Most probably because you have bonds or constraints that exceed ' + str(ns.bonded_max_range) + ' nm. Increase bins range for bonds and constraints and retry! See argument -bonds_max_range.') + msg = ( + f"Most probably because you have bonds or constraints that " + f"exceed {ns.bonded_max_range} nm. Increase bins range for bonds and " + f"constraints and retry! See argument -bonds_max_range." + ) + raise ValueError(msg) else: avg_diff_grp_constraints.append(constraints[grp_constraint]['AA']['avg']) @@ -1917,8 +1921,12 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False domain_max = max(bonds[grp_bond]['AA']['x'][-1], bonds[grp_bond]['CG']['x'][-1]) avg_diff_grp_bonds.append(emd(bonds[grp_bond]['AA']['hist'], bonds[grp_bond]['CG']['hist'], ns.bins_bonds_dist_matrix) * ns.bonds2angles_scoring_factor) except IndexError: - sys.exit( - swarmcg.shared.styling.header_error + 'Most probably because you have bonds or constraints that exceed ' + str(ns.bonded_max_range) + ' nm. Increase bins range for bonds and bonds and retry! See argument -bonds_max_range.') + msg = ( + f"Most probably because you have bonds or constraints that " + f"exceed {ns.bonded_max_range} nm. Increase bins range for bonds and " + f"constraints and retry! See argument -bonds_max_range." + ) + raise ValueError(msg) else: avg_diff_grp_bonds.append(bonds[grp_bond]['AA']['avg']) @@ -2454,8 +2462,8 @@ def modify_mdp(mdp_filename, sim_time=None, nb_frames=1500, log_write_freq=5000, nsteps = int(sim_time*1000 / dt) mdp_lines_in[nsteps_line] = sp_nsteps_line[0]+'= '+str(nsteps)+' ; automatically modified by Swarm-CG' else: - sys.exit( - swarmcg.shared.styling.header_error + 'The provided MD MDP file does not contain one of these entries: dt, nsteps') + msg = "The provided MD MDP file does not contain one of these entries: dt, nsteps." + raise exceptions.MissformattedFile(msg) # force writting to the log file every given nb of steps, to make sure simulations won't be killed for insufficient writting to the log file # (which we use to check for simulations that are stuck/bugged) @@ -2463,8 +2471,8 @@ def modify_mdp(mdp_filename, sim_time=None, nb_frames=1500, log_write_freq=5000, nstlog = log_write_freq mdp_lines_in[nstlog_line] = sp_nstlog_line[0]+'= '+str(nstlog)+' ; automatically modified by Swarm-CG' else: - sys.exit( - swarmcg.shared.styling.header_error + 'The provided MD MDP file does not contain one of these entries: nstlog') + msg = "The provided MD MDP file does not contain one of these entries: nstlog." + raise exceptions.MissformattedFile(msg) # force NOT writting coordinates data, as this can only slow the simulation and we don't need it if nstxout_line != -1: @@ -2544,7 +2552,11 @@ def eval_function(parameters_set, ns): start_eval_ts = datetime.now().timestamp() print_stdout_forced() - print_stdout_forced('Starting iteration', ns.nb_eval, 'at', time.strftime('%H:%M:%S'), 'on', time.strftime('%d-%m-%Y')) + # TODO: this should use logging + print_stdout_forced( + f"Starting iteration {ns.nb_eval} at {time.strftime('%H:%M:%S')} " + f"on {time.strftime('%d-%m-%Y')}" + ) # enter the execution directory os.chdir(ns.exec_folder) @@ -2605,7 +2617,13 @@ def eval_function(parameters_set, ns): gmx_process.kill() else: - sys.exit('\n\n' + swarmcg.shared.styling.header_gmx_error + gmx_out + '\n' + swarmcg.shared.styling.header_error + 'Gmx grompp failed at minimization step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_mini\nYou may also want to look into argument -mini_maxwarn\nIf you think this is a bug, please consider opening an issue on GitHub at ' + config.github_url + '\n') + msg = ( + f"Gmx grompp failed at minimisation step, see gmx error message above. Please check " + f"the parameters of the MDP file provided through argument -cg_sim_mdp_mini. If you " + f"think this is a bug, please consider opening an issue on GitHub " + f"at {config.github_url}" + ) + raise exceptions.ComputationError(msg) # if minimization finished properly, we just check for the .gro file printed in the end if os.path.isfile('mini.gro'): @@ -2641,8 +2659,13 @@ def eval_function(parameters_set, ns): gmx_process.kill() else: - # pass - sys.exit('\n\n' + swarmcg.shared.styling.header_gmx_error + gmx_out + '\n' + swarmcg.shared.styling.header_error + 'Gmx grompp failed at equilibration step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_equi\nIf you think this is a bug, please consider opening an issue on GitHub at ' + config.github_url + '\n') + msg = ( + f"Gmx grompp failed at equilibration step, see gmx error message above. Please check " + f"the parameters of the MDP file provided through argument -cg_sim_mdp_equi. If you " + f"think this is a bug, please consider opening an issue on GitHub " + f"at {config.github_url }" + ) + raise exceptions.ComputationError(msg) # if EQUI finished properly, we just check for the .gro file printed in the end if os.path.isfile('equi.gro'): @@ -2681,8 +2704,13 @@ def eval_function(parameters_set, ns): gmx_process.kill() else: - # pass - sys.exit('\n\n' + swarmcg.shared.styling.header_gmx_error + gmx_out + '\n' + swarmcg.shared.styling.header_error + 'Gmx grompp failed at the MD step, see gmx error message above\nPlease check the parameters of the MDP file provided through argument -cg_sim_mdp_prod\nIf you think this is a bug, please consider opening an issue on GitHub at ' + config.github_url + '\n') + msg = ( + f"Gmx grompp failed at MD step, see gmx error message above. Please check " + f"the parameters of the MDP file provided through argument -cg_sim_mdp_prod. If you " + f"think this is a bug, please consider opening an issue on GitHub " + f"at {config.github_url}" + ) + raise exceptions.ComputationError(msg) # to verify if MD run finished properly, we check for the .gro file printed in the end if os.path.isfile('md.gro'): @@ -2762,7 +2790,7 @@ def eval_function(parameters_set, ns): ns.all_emd_dist_geoms = all_emd_dist_geoms else: - print_stdout_forced(' MD run failed (molecule exploded)') + print_stdout_forced(" MD run failed (molecule exploded)") eval_score, fit_score_total, fit_score_constraints_bonds, fit_score_angles, fit_score_dihedrals = [ns.worst_fit_score]*5 ns.gyr_cg, ns.gyr_cg_std, ns.sasa_cg, ns.sasa_cg_std = None, None, None, None # ns.all_rg_last_cycle = np.append(ns.all_rg_last_cycle, None) @@ -2771,7 +2799,10 @@ def eval_function(parameters_set, ns): else: if md_run_killed: - print_stdout_forced(' MD run failed (unstable simulation was killed, with unstable = NOT writing in log file for '+str(ns.sim_kill_delay)+' sec)') + print_stdout_forced( + f" MD run failed (unstable simulation was killed, with unstable " + f"= NOT writing in log file for {str(ns.sim_kill_delay)} sec)" + ) else: print_stdout_forced(' MD run failed (simulation process terminated with error)') eval_score, fit_score_total, fit_score_constraints_bonds, fit_score_angles, fit_score_dihedrals = [ns.worst_fit_score]*5 @@ -2782,9 +2813,14 @@ def eval_function(parameters_set, ns): else: if equi_killed: - print_stdout_forced(' Equilibration run failed (unstable simulation was killed, with unstable = NOT writing in log file for '+str(ns.sim_kill_delay)+' sec)') + print_stdout_forced( + f" Equilibration run failed (unstable simulation was killed, with unstable " + f"= NOT writing in log file for {str(ns.sim_kill_delay)} sec)" + ) else: - print_stdout_forced(' Equilibration run failed (simulation process terminated with error)') + print_stdout_forced( + " Equilibration run failed (simulation process terminated with error)" + ) eval_score, fit_score_total, fit_score_constraints_bonds, fit_score_angles, fit_score_dihedrals = [ns.worst_fit_score]*5 ns.gyr_cg, ns.gyr_cg_std, ns.sasa_cg, ns.sasa_cg_std = None, None, None, None # ns.all_rg_last_cycle = np.append(ns.all_rg_last_cycle, None) @@ -2792,9 +2828,14 @@ def eval_function(parameters_set, ns): ns.total_gmx_time += datetime.now().timestamp() - start_gmx_ts else: if mini_killed: - print_stdout_forced(' Minimization run failed (unstable simulation was killed, with unstable = NOT writing in log file for '+str(ns.sim_kill_delay)+' sec)') + print_stdout_forced( + f" Minimization run failed (unstable simulation was killed, with unstable " + f"= NOT writing in log file for {str(ns.sim_kill_delay)} sec)" + ) else: - print_stdout_forced(' Minimization run failed (simulation process terminated with error)') + print_stdout_forced( + " Minimization run failed (simulation process terminated with error)" + ) eval_score, fit_score_total, fit_score_constraints_bonds, fit_score_angles, fit_score_dihedrals = [ns.worst_fit_score]*5 ns.gyr_cg, ns.gyr_cg_std, ns.sasa_cg, ns.sasa_cg_std = None, None, None, None # ns.all_rg_last_cycle = np.append(ns.all_rg_last_cycle, None) From fbe634606152dd068899ebd785dab899d892555a Mon Sep 17 00:00:00 2001 From: Giovanni <9051577+giovannidoni@users.noreply.github.com> Date: Fri, 11 Sep 2020 13:27:21 +0200 Subject: [PATCH 15/40] Move pontentials in new folder --- .../potentials.py => simulations/__init__.py} | 0 swarmcg/simulations/potentials.py | 44 +++++++++++++++ swarmcg/swarmCG.py | 54 +++---------------- 3 files changed, 51 insertions(+), 47 deletions(-) rename swarmcg/{shared/potentials.py => simulations/__init__.py} (100%) create mode 100644 swarmcg/simulations/potentials.py diff --git a/swarmcg/shared/potentials.py b/swarmcg/simulations/__init__.py similarity index 100% rename from swarmcg/shared/potentials.py rename to swarmcg/simulations/__init__.py diff --git a/swarmcg/simulations/potentials.py b/swarmcg/simulations/potentials.py new file mode 100644 index 0000000..48cb777 --- /dev/null +++ b/swarmcg/simulations/potentials.py @@ -0,0 +1,44 @@ +import numpy as np + + +def gmx_bonds_func_1(x, a, b, c): + """ + Gromacs potential function 1 for bonds. + """ + return a / 2 * (x - b) ** 2 + c + + +def gmx_angles_func_1(x, a, b, c): + """ + Gromacs potential function 1 for angles. + """ + return gmx_bonds_func_1(x, a, b, c) + + +def gmx_angles_func_2(x, a, b, c): + """ + Gromacs potential function 2 for angles. + """ + return a / 2 * (np.cos(x) - np.cos(b)) ** 2 + c + + +def gmx_dihedrals_func_1(mult): + """ + Gromacs potential function 1 for angles -- generated on the fly with adjusted multiplicity + """ + def mult_adjusted(x, a, b, c): + return a * (1 + np.cos(mult * x - b)) + c + return mult_adjusted + + +def gmx_dihedrals_func_2(x, a, b, c): + """ + Gromacs potential function 2 for dihedrals -- the same as potential function 1 for angles + """ + return gmx_bonds_func_1(x, a, b, c) # it's actually the same + + +# TODO: for dihedral function 9, this is the merging of several potentials of +# TODO: gmx_dihedrals_func_1 -- here one of mult=1 together with another of mult=2 +# def f(x,a,b,c,d,e): +# return a * (1+np.cos(x-b)) + d * (1+np.cos(2*x-e)) + c \ No newline at end of file diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 46af709..6e55127 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -16,8 +16,10 @@ from scipy.optimize import curve_fit from swarmcg import config -from swarmcg.shared import utils +from swarmcg.shared import utils, styling from swarmcg.shared import exceptions +from swarmcg.simulations.potentials import (gmx_bonds_func_1, gmx_angles_func_1, gmx_angles_func_2, + gmx_dihedrals_func_1, gmx_dihedrals_func_2) matplotlib.use('AGG') # use the Anti-Grain Geometry non-interactive backend suited for scripted PNG creation warnings.resetwarnings() @@ -1453,48 +1455,6 @@ def get_CG_dihedrals_distrib(ns, beads_ids): return dihedral_avg, dihedral_hist, dihedral_values_deg, dihedral_values_rad - -# gromacs potential function 1 for bonds -def gmx_bonds_func_1(x, a, b, c): - - return a/2 * (x-b)**2 + c - - -# gromacs potential function 1 for angles -def gmx_angles_func_1(x, a, b, c): - - # return a/2 * (x-b)**2 + c - return gmx_bonds_func_1(x, a, b, c) # it's actually the same - - -# gromacs potential function 2 for angles -def gmx_angles_func_2(x, a, b, c): - - return a/2 * (np.cos(x)-np.cos(b))**2 + c - - -# gromacs potential function 1 for dihedrals -- generated on the fly with adjusted multiplicity -def gmx_dihedrals_func_1(mult): - - def mult_adjusted(x, a, b, c): - - return a * (1 + np.cos(mult*x-b)) + c - - return mult_adjusted - - -# gromacs potential function 2 for dihedrals -- basically the same as potential function 2 for angles -def gmx_dihedrals_func_2(x, a, b, c): - - # return gmx_angles_func_1(x, a, b, c) - return gmx_bonds_func_1(x, a, b, c) # it's actually the same - - -# TODO: for dihedral function 9, this is the merging of several potentials of gmx_dihedrals_func_1 -- here one of mult=1 together with another of mult=2 -# def f(x,a,b,c,d,e): -# return a * (1+np.cos(x-b)) + d * (1+np.cos(2*x-e)) + c - - # update ITP force constants with Boltzmann inversion for selected geoms at this given optimization step def perform_BI(ns): @@ -1543,7 +1503,7 @@ def perform_BI(ns): deriv = 1/deriv sigma = np.where(y < max(y), deriv, np.inf) - popt, pcov = curve_fit(gmx_bonds_func_1, x*10, y, p0=params_guess, sigma=sigma, maxfev=99999, absolute_sigma=False) # multiply for amgstrom for BI + popt, pcov = curve_fit(gmx_bonds_func_1, x * 10, y, p0=params_guess, sigma=sigma, maxfev=99999, absolute_sigma=False) # multiply for amgstrom for BI # here we just update the force constant, bond length is already set to the average of distribution ns.out_itp['bond'][grp_bond]['fct'] = min(max(popt[0]*100, config.default_min_fct_bonds), config.default_max_fct_bonds_bi) # stay within specified range for force constants @@ -1819,9 +1779,9 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False return 0, 0, 0, 0, 0, None # ns.sasa_cg == None will be checked in eval_function and worst score will be attributed print() - print(swarmcg.shared.styling.sep_close, flush=True) + print(styling.sep_close, flush=True) print('| SCORING AND PLOTTING |', flush=True) - print(swarmcg.shared.styling.sep_close, flush=True) + print(styling.sep_close, flush=True) print() # constraints @@ -2059,7 +2019,7 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False print('Displaying max '+str(ncols)+' distributions per row using the CG ITP file ordering of distributions groups ('+str(hidden_cols)+' more are hidden)', flush=True) else: if not ns.mismatch_order: - print(swarmcg.shared.styling.header_warning + 'Displaying max ' + str(ncols) + ' distributions groups per row and this can be MISLEADING because ordering by pairwise AA-mapped vs. CG distributions mismatch is DISABLED (' + str(hidden_cols) + ' more are hidden)', flush=True) + print(styling.header_warning + 'Displaying max ' + str(ncols) + ' distributions groups per row and this can be MISLEADING because ordering by pairwise AA-mapped vs. CG distributions mismatch is DISABLED (' + str(hidden_cols) + ' more are hidden)', flush=True) else: print('Displaying max '+str(ncols)+' distributions groups per row ordered by pairwise AA-mapped vs. CG distributions difference ('+str(hidden_cols)+' more are hidden)', flush=True) else: From 6051f0329ecf61ac0596c883d5a6f1b26c42ced8 Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Tue, 15 Sep 2020 14:40:50 +0200 Subject: [PATCH 16/40] Error handling of VS reader from .itp --- swarmcg/config.py | 1 + swarmcg/shared/vs_functions.py | 4 ++ swarmcg/swarmCG.py | 77 ++++++++++++++++++++++++++++++---- 3 files changed, 74 insertions(+), 8 deletions(-) create mode 100644 swarmcg/shared/vs_functions.py diff --git a/swarmcg/config.py b/swarmcg/config.py index c0eb77e..ba9248e 100644 --- a/swarmcg/config.py +++ b/swarmcg/config.py @@ -67,6 +67,7 @@ 'angle': [1, 2], 'dihedral': [1, 2, 4], 'dihedral_with_mult': [1, 4] + 'virtual_sitesn': [1] # these functions use 3 parameters, the last one being multiplicity (if it's omitted gromacs will use 1 by default, we reproduce this behavior) } diff --git a/swarmcg/shared/vs_functions.py b/swarmcg/shared/vs_functions.py new file mode 100644 index 0000000..4e117a4 --- /dev/null +++ b/swarmcg/shared/vs_functions.py @@ -0,0 +1,4 @@ +#Virtual sites function definition +def vsn_1(pos): + + return(vpos=[x,y,z]) \ No newline at end of file diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 6e55127..35d8776 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -220,21 +220,23 @@ def read_cg_itp_file(ns, itp_lines): if itp_line != '' and not itp_line.startswith(';'): if bool(re.search('\[.*moleculetype.*\]', itp_line)): - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = True, False, False, False, False, False, False + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = True, False, False, False, False, False, False, False elif bool(re.search('\[.*atoms.*\]', itp_line)): - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = False, True, False, False, False, False, False + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, True, False, False, False, False, False, False elif bool(re.search('\[.*constraint.*\]', itp_line)): - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = False, False, True, False, False, False, False + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, True, False, False, False, False, False elif bool(re.search('\[.*bond.*\]', itp_line)): - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = False, False, False, True, False, False, False + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, True, False, False, False, False elif bool(re.search('\[.*angle.*\]', itp_line)): - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = False, False, False, False, True, False, False + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, False, True, False, False, False elif bool(re.search('\[.*dihedral.*\]', itp_line)): - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = False, False, False, False, False, True, False + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, False, False, True, False, False elif bool(re.search('\[.*exclusion.*\]', itp_line)): - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = False, False, False, False, False, False, True + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, False, False, False, True, False + elif bool(re.search('\[.*virtual_sitesn.*\]', itp_line)): + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, False, False, False, False, True elif bool(re.search('\[.*\]', itp_line)): # all other sections - r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion = False, False, False, False, False, False, False + r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, False, False, False, False, False else: sp_itp_line = itp_line.split() @@ -251,6 +253,14 @@ def read_cg_itp_file(ns, itp_lines): ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge), 'mass_and_eol': mass_and_eol}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis except IndexError: ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge)}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis + #Check if the atom index correspond to the length of the atoms list, + # if this check is passed it allow to do direct accesses within the list + if not len(ns.cg_itp['atoms']) == int(bead_id): + msg = ( + "Swarm-CG handles .itp files with atoms indexed consecutively starting from 1.\n" + "The atom {} does not follow this formatting.".format(bead_id) + ) + raise exceptions.MissformattedFile(msg) elif r_constraints: @@ -379,6 +389,57 @@ def read_cg_itp_file(ns, itp_lines): except IndexError: ns.cg_itp['dihedral'][ns.nb_dihedrals]['plt_id'].append('') + elif r_virtual: + # For user information we need to provide the number of VS. + # + # We need to take into account: the atom associated to the virtual site must be VT type + # + # We need to define the function types for the VSn + + #Read VS index, and VS function, list_cg_atoms + bead_id, vs_type, cg_atomlist = int(sp_itp_line[0])-1, sp_itp_line[1], [int(bid)-1 for bid in sp_itp_line[2:]] + + + #Check if the bead is defined in the atom list + if bead_id >= len(ns.cg_itp['atoms']): + msg = ( + "The bead index definition of the CG virtual sites {} in not defined" + " within in the atomlist".format(bead_id) + ) + raise exceptions.MissformattedFile(msg) + else: + #Check if the bead is defined as VS + if not ns.cg_itp['atoms'][bead_id]['bead_type'] == 'VS': + msg = ( + "The virtual site {} should be defined with bead type" + " VS".format(bead_id+1) + ) + raise exceptions.MissformattedFile(msg) + #Function is in the function list + if not vs_type in config.handled_functions['virtual_sitesn']: + msg = ( + "The definition of the CG virtual sites {} uses a function which is" + " not defined in the code ({}). Please check the .itp file or use " + "one of the functions defined within SwarmCG.".format(bead_id,vs_type) + ) + raise exceptions.MissformattedFile(msg) + + #The cg_atoms in list_cg_atoms + for bid in cg_atomlist: + if bid >= bead_id: + msg = ( + "The definition of the CG virtual sites {} includes atoms that " + "either they are not in the list or their index comes after the " + "index is higher than the one of the virtual site.".format(bead_id) + ) + raise exceptions.MissformattedFile(msg) + + try: + mass_and_eol = ' '.join(sp_itp_line[7:]) + ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge), 'mass_and_eol': mass_and_eol}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis + except IndexError: + ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge)}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis + elif r_exclusion: ns.cg_itp['exclusion'].append([int(bead_id)-1 for bead_id in sp_itp_line]) From 48f5c5f0b1021ebdb264aecc7ba7439c16fd5498 Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Tue, 15 Sep 2020 15:53:58 +0200 Subject: [PATCH 17/40] Added the options to write the VS in the itp output --- swarmcg/swarmCG.py | 37 +++++++++++++++++++------------------ 1 file changed, 19 insertions(+), 18 deletions(-) diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 35d8776..8aa2401 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -212,7 +212,7 @@ def verify_handled_functions(geom, func_obj, line_obj): def read_cg_itp_file(ns, itp_lines): print('Reading Coarse-Grained (CG) ITP file') - ns.cg_itp = {'moleculetype': {'molname': '', 'nrexcl': 0}, 'atoms': [], 'constraint': [], 'bond': [], 'angle': [], 'dihedral': [], 'exclusion': []} + ns.cg_itp = {'moleculetype': {'molname': '', 'nrexcl': 0}, 'atoms': [], 'constraint': [], 'bond': [], 'angle': [], 'dihedral': [], 'exclusion': [], 'virtual_sitesn': []} ns.nb_constraints, ns.nb_bonds, ns.nb_angles, ns.nb_dihedrals = -1, -1, -1, -1 for i in range(len(itp_lines)): @@ -391,9 +391,6 @@ def read_cg_itp_file(ns, itp_lines): elif r_virtual: # For user information we need to provide the number of VS. - # - # We need to take into account: the atom associated to the virtual site must be VT type - # # We need to define the function types for the VSn #Read VS index, and VS function, list_cg_atoms @@ -409,22 +406,17 @@ def read_cg_itp_file(ns, itp_lines): raise exceptions.MissformattedFile(msg) else: #Check if the bead is defined as VS - if not ns.cg_itp['atoms'][bead_id]['bead_type'] == 'VS': + if ns.cg_itp['atoms'][bead_id]['bead_type'] != 'VS': msg = ( "The virtual site {} should be defined with bead type" " VS".format(bead_id+1) ) raise exceptions.MissformattedFile(msg) #Function is in the function list - if not vs_type in config.handled_functions['virtual_sitesn']: - msg = ( - "The definition of the CG virtual sites {} uses a function which is" - " not defined in the code ({}). Please check the .itp file or use " - "one of the functions defined within SwarmCG.".format(bead_id,vs_type) - ) - raise exceptions.MissformattedFile(msg) + func = verify_handled_functions('virtual_sitesn', vs_type, i + 1) + - #The cg_atoms in list_cg_atoms + #The cg_atoms in list_cg_atoms, checking that the indexes are lower than the one of the VS for bid in cg_atomlist: if bid >= bead_id: msg = ( @@ -434,11 +426,8 @@ def read_cg_itp_file(ns, itp_lines): ) raise exceptions.MissformattedFile(msg) - try: - mass_and_eol = ' '.join(sp_itp_line[7:]) - ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge), 'mass_and_eol': mass_and_eol}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis - except IndexError: - ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge)}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis + ns.cg_itp['virutal_sitesn'].append({'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist) + elif r_exclusion: @@ -889,6 +878,18 @@ def print_cg_itp_file(itp_obj, out_path_itp, print_sections=['constraint', 'bond else: fp.write('{0:<4} {1:>4} {6:>2} {2:>6} {3:>6} {4:<4} {5:9.5f}\n'.format(itp_obj['atoms'][i]['bead_id']+1, itp_obj['atoms'][i]['bead_type'], itp_obj['atoms'][i]['residue'], itp_obj['atoms'][i]['atom'], i+1, itp_obj['atoms'][i]['charge'], itp_obj['atoms'][i]['resnr'])) + fp.write('\n\n[ ]\n') + fp.write('; id type resnr residue atom cgnr charge mass\n\n') + + if len(itp_obj['virtual_sitesn']) > 0: + fp.write('\n\n[ virtual_sitesn ]\n') + for i in range(len(itp_obj['virtual_sitesn'])): + + fp.write('{0:<4} {1:>4} {}\n'.format( + itp_obj['virtual_sitesn'][i]['bead_id'] + 1, + itp_obj['virtual_sitesn'][i]['vs_type']), + ' '.join([str(bid+1) for bid in itp_obj['virtual_sitesn'][i]['atom_list']])) + if 'constraint' in print_sections and 'constraint' in itp_obj and len(itp_obj['constraint']) > 0: fp.write('\n\n[ constraints ]\n') fp.write('; i j funct length\n') From 79b5518c7b065d51801b444f9245ea60b4f1b1d7 Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Wed, 16 Sep 2020 12:51:37 +0200 Subject: [PATCH 18/40] CG trajectory builder --- swarmcg/swarmCG.py | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 8aa2401..ed87ea3 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -1296,6 +1296,24 @@ def read_aa_traj(ns): return +def initialize_cg_traj(ns): + print('Building Coarse-Grained (CG) trajectory', flush=True) + with warnings.catch_warnings(): + warnings.filterwarnings("ignore", + category=ImportWarning) # ignore warning: "bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__" + ns.cg_universe2 = mda.Universe(ns.gro_input_basename, ns.gro_input_basename, in_memory=True, refresh_offsets=True, + guess_bonds=False) # setting guess_bonds=False disables angles, dihedrals and improper_dihedrals guessing, which is activated by default + #Here we need to extract the number of atoms, or a more refined method to extract only the elements on which we are interested + ns. + + # if len(ns.aa_universe.trajectory) > 20000: + # print(config.header_warning+'Your atomistic trajectory contains many frames, which increases computation time\nReasonably reducing the number of frames of your input AA trajectory won\'t affect results quality\n2k to 10k frames is usually enough, as long as behaviour and flexibility of your molecule are correctly described by your atomistic trajectory') + + return + +def map_aa2cg_traj(ns): + return + # use selected whole molecules as MDA atomgroups and make their coordinates whole, inplace, across the complete tAA rajectory def make_aa_traj_whole_for_selected_mols(ns): From 3e61eee62b8a2b75634c187c7e13e727a4918da1 Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Thu, 17 Sep 2020 16:09:00 +0200 Subject: [PATCH 19/40] Creation of the aa2cg_trajectory universe: need to fetch the atom mass in topology --- swarmcg/swarmCG.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index ed87ea3..bd7b7cf 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -1304,7 +1304,14 @@ def initialize_cg_traj(ns): ns.cg_universe2 = mda.Universe(ns.gro_input_basename, ns.gro_input_basename, in_memory=True, refresh_offsets=True, guess_bonds=False) # setting guess_bonds=False disables angles, dihedrals and improper_dihedrals guessing, which is activated by default #Here we need to extract the number of atoms, or a more refined method to extract only the elements on which we are interested - ns. + #We need to assume that the molecule we will study is located at the beginning of the file. This assumptions does not change much, as the atom names and weights can be taken from the itp file + sel = ns.cg_universe2.atoms[:len(ns.cg_itp['atoms'])] + #I generate a numpy array of the size np.zeros(len(ns.aa_universe.trajectory,len(ns.cg_itp['atoms']))) + coord = np.zeros((len(ns.aa_universe.trajectory),len(ns.cg_itp['atoms']),3)) + np.aa2cg_trajectory = mda.Merge(sel) + np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + + #Assigning to the new universe the masses related to the CG # if len(ns.aa_universe.trajectory) > 20000: # print(config.header_warning+'Your atomistic trajectory contains many frames, which increases computation time\nReasonably reducing the number of frames of your input AA trajectory won\'t affect results quality\n2k to 10k frames is usually enough, as long as behaviour and flexibility of your molecule are correctly described by your atomistic trajectory') From e59d5a71b83e00ef2673d1f45dca4f787e9c8102 Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Thu, 17 Sep 2020 19:27:18 +0200 Subject: [PATCH 20/40] Created a list for the masses associated to the atomtypes (ns.cg_atomtypes_mass) that must be used in case there is no definition of the atom mass in the itp file of the molecule we want to optimize via fetch_cg_mass_itp(ns) --- swarmcg/swarmCG.py | 49 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 49 insertions(+) diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index bd7b7cf..af63e3b 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -488,6 +488,51 @@ def read_cg_itp_file(ns, itp_lines): return +#This function reads the defaults masses associated to each atomtype loaded into the topology file +def fetch_cg_mass_itp(ns): + #Declaring the ns.cg_atomtypes = {} in order to retreive the mass of each particle whenever is missing by searching the type as arguments + ns.cg_atomtypes_mass = {} + #Parsing the topology file to find all the .itp included + list_itp = [] + with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename, 'r') as fp: + all_top_lines = fp.read().split('\n') + for line in all_top_lines: + if line.split()[0] == "#include": + #Reading the filename of the loaded .itps + aux = line.split()[1] + list_itp.append(aux[1:len(aux)-1]) + + #Reading all the atomtypes within each .itp found in the topology file + for itp_name in list_itp: + with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + itp_name, 'r') as fp: + itp_file = fp.read().split('\n') + + #Stripping all comments from the list of line + for i in range(len(itp_file)): + itp_file[i] = strip(itp_file[i],";") + + #Popping out all the empty lines + list_idx = [index for index, value in enumerate(itp_file) if value == ""] + list_idx.reverse() + for idx in list_idx: + itp_file.pop(idx) + + # Here a boolean checking if we are in a atomtypes section + bAtomTypes = False + + #The lines of the file should be now cleaned, therefore it is possible to skip all the checks to monitor empty lines + for line in itp_file: + words = line.split() + if bAtomTypes: + ns.cg_atomtypes_mass[words[0]] = float(words[1]) + + #Searching the atomtype keyword + if (words[0] == "[" and words[0] == "atomtypes" and words[0] == "]"): + bAtomTypes = True + elif words[0] == "[" and words[1] != "atomtypes": + bAtomTypes = False + + return # load CG beads from NDX-like file def read_ndx_atoms2beads(ns): @@ -1318,6 +1363,10 @@ def initialize_cg_traj(ns): return +#Strip the comments from the list +def strip(line,val): + return line[:line.find(val)] + def map_aa2cg_traj(ns): return From c3d10bb5dd12c01d9d22469dafa7c17d71ecab68 Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Mon, 21 Sep 2020 15:42:03 +0200 Subject: [PATCH 21/40] AA to CG trajectory conversion in map_aa2cg_traj(ns) --- swarmcg/optimize_model.py | 3 + swarmcg/swarmCG.py | 124 ++++++++++++++++++++++++++++++-------- 2 files changed, 102 insertions(+), 25 deletions(-) diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 9d01829..1e1a9aa 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -187,6 +187,9 @@ def run(ns): print() + #Loading the mass of the atom-tpyes in case they are needed + scg.fetch_cg_mass_itp(ns) + # read starting CG ITP file with open(ns.cg_itp_filename, 'r') as fp: itp_lines = fp.read().split('\n') diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index af63e3b..6bc2adb 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -212,7 +212,7 @@ def verify_handled_functions(geom, func_obj, line_obj): def read_cg_itp_file(ns, itp_lines): print('Reading Coarse-Grained (CG) ITP file') - ns.cg_itp = {'moleculetype': {'molname': '', 'nrexcl': 0}, 'atoms': [], 'constraint': [], 'bond': [], 'angle': [], 'dihedral': [], 'exclusion': [], 'virtual_sitesn': []} + ns.cg_itp = {'moleculetype': {'molname': '', 'nrexcl': 0}, 'atoms': [], 'constraint': [], 'bond': [], 'angle': [], 'dihedral': [], 'exclusion': [], 'virtual_sitesn': {}} ns.nb_constraints, ns.nb_bonds, ns.nb_angles, ns.nb_dihedrals = -1, -1, -1, -1 for i in range(len(itp_lines)): @@ -239,22 +239,42 @@ def read_cg_itp_file(ns, itp_lines): r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, False, False, False, False, False else: - sp_itp_line = itp_line.split() + #Stripping comments from the input line + aux_itp_line = strip(itp_line,";") + sp_itp_line = aux_itp_line.split() if r_moleculetype: ns.cg_itp['moleculetype']['molname'], ns.cg_itp['moleculetype']['nrexcl'] = sp_itp_line[0], int(sp_itp_line[1]) elif r_atoms: + if len(sp_itp_line) == 7: + bead_id, bead_type, resnr, residue, atom, cgnr, charge = sp_itp_line[:7] + # As the mass is not defined we look into its definition + try: + mass = ns.cg_atomtypes_mass[bead_type] + except: + msg = ( + "The bead_type {}, is not contained into the definition of the " + "force field file" + ).format(bead_type) + raise exceptions.MissformattedFile(msg) + + elif len(sp_itp_line) == 8: + bead_id, bead_type, resnr, residue, atom, cgnr, charge, mass = sp_itp_line[:8] + else: + # + msg = ( + "The atom description form the input itp file: \n\n {} \n\n" + "does not contain the correct number of input. Please insert " + "the following information: \n\n bead_id, bead_type, resnr, " + "residue, atom, cgnr, charge, [mass] \n\n".format(itp_line) + ) + raise exceptions.MissformattedFile(msg) + + #Assignment of the variables value + ns.cg_itp['atoms'].append({'bead_id': int(bead_id) - 1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue,'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge), 'mass': float(mass)}) - bead_id, bead_type, resnr, residue, atom, cgnr, charge = sp_itp_line[:7] - try: - mass_and_eol = ' '.join(sp_itp_line[7:]) - ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge), 'mass_and_eol': mass_and_eol}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis - except IndexError: - ns.cg_itp['atoms'].append({'bead_id': int(bead_id)-1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue, 'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge)}) # retrieve indexing from 0 for CG beads IDS for MDAnalysis - #Check if the atom index correspond to the length of the atoms list, - # if this check is passed it allow to do direct accesses within the list if not len(ns.cg_itp['atoms']) == int(bead_id): msg = ( "Swarm-CG handles .itp files with atoms indexed consecutively starting from 1.\n" @@ -426,7 +446,8 @@ def read_cg_itp_file(ns, itp_lines): ) raise exceptions.MissformattedFile(msg) - ns.cg_itp['virutal_sitesn'].append({'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist) + # ns.cg_itp['virutal_sitesn'].append({'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist}) + ns.cg_itp['virutal_sitesn'][bead_id] = {'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist} elif r_exclusion: @@ -1343,20 +1364,32 @@ def read_aa_traj(ns): def initialize_cg_traj(ns): print('Building Coarse-Grained (CG) trajectory', flush=True) - with warnings.catch_warnings(): - warnings.filterwarnings("ignore", - category=ImportWarning) # ignore warning: "bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__" - ns.cg_universe2 = mda.Universe(ns.gro_input_basename, ns.gro_input_basename, in_memory=True, refresh_offsets=True, - guess_bonds=False) # setting guess_bonds=False disables angles, dihedrals and improper_dihedrals guessing, which is activated by default - #Here we need to extract the number of atoms, or a more refined method to extract only the elements on which we are interested - #We need to assume that the molecule we will study is located at the beginning of the file. This assumptions does not change much, as the atom names and weights can be taken from the itp file - sel = ns.cg_universe2.atoms[:len(ns.cg_itp['atoms'])] - #I generate a numpy array of the size np.zeros(len(ns.aa_universe.trajectory,len(ns.cg_itp['atoms']))) - coord = np.zeros((len(ns.aa_universe.trajectory),len(ns.cg_itp['atoms']),3)) - np.aa2cg_trajectory = mda.Merge(sel) - np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) - - #Assigning to the new universe the masses related to the CG + # with warnings.catch_warnings(): + # warnings.filterwarnings("ignore", + # category=ImportWarning) # ignore warning: "bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__" + # ns.cg_universe2 = mda.Universe(ns.gro_input_basename, ns.gro_input_basename, in_memory=True, refresh_offsets=True, + # guess_bonds=False) # setting guess_bonds=False disables angles, dihedrals and improper_dihedrals guessing, which is activated by default + # Here we need to extract the number of atoms, or a more refined method to extract only the elements on which we are interested + # We need to assume that the molecule we will study is located at the beginning of the file. This assumptions does not change much, as the atom names and weights can be taken from the itp file + # sel = ns.cg_universe2.atoms[:len(ns.cg_itp['atoms'])] + # I generate a numpy array of the size np.zeros(len(ns.aa_universe.trajectory,len(ns.cg_itp['atoms']))) + # coord = np.zeros((len(ns.aa_universe.trajectory),len(ns.cg_itp['atoms']),3)) + # np.aa2cg_trajectory = mda.Merge(sel) + # np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + masses = np.array([val['mass'] for val in ns.cg_itp['atoms']]) + names = np.array([val['atom'] for val in ns.cg_itp['atoms']]) + resname = np.array([val['residue'] for val in ns.cg_itp['atoms']]) + resid = np.array([val['resnr'] for val in ns.cg_itp['atoms']]) + nr = len(list(set([val['resnr'] for val in ns.cg_itp['atoms']]))) + np.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']), nr, resindex=resid, trajectory=True) + np.aa2cg_trajectory.add_TopologyAttr('masses') + np.aa2cg_trajectory._topology.masses.values = np.array(masses) + np.aa2cg_trajectory.add_TopologyAttr('name') + np.aa2cg_trajectory._topology.names.values = names + np.aa2cg_trajectory.add_TopologyAttr('resnames') + np.aa2cg_trajectory._topology.resnames.values = resname + +#Assigning to the new universe the masses related to the CG # if len(ns.aa_universe.trajectory) > 20000: # print(config.header_warning+'Your atomistic trajectory contains many frames, which increases computation time\nReasonably reducing the number of frames of your input AA trajectory won\'t affect results quality\n2k to 10k frames is usually enough, as long as behaviour and flexibility of your molecule are correctly described by your atomistic trajectory') @@ -1368,6 +1401,44 @@ def strip(line,val): return line[:line.find(val)] def map_aa2cg_traj(ns): + # for i in range(len(ns.aa_universe.trajectory)): + # I will estimate the coordinates of each bead within all the frames using the iterator of mda and the function center_of_mass() + coord = np.zeros((len(ns.aa_universe.trajectory), len(ns.cg_itp['atoms']), 3)) + for j in range(len(ns.cg_itp['atoms'])): + #Check if the atomtype of the cg is related to a VS + if ns.cg_itp['atoms'][j]['bead_type'] != 'VS': + #The bead is not a VS therefore must be evaluated starting from the AA + la = ns.all_beads[j]['atoms_id'] + sel = ns.aa_universe.atoms[la] + traj = [] + for fr in ns.aa_universe.trajectory: + traj.append(sel.center_of_mass()) + coord[:,j,:] = np.array(traj) + + + np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + + for j in range(len(ns.cg_itp['atoms'])): + if ns.cg_itp['atoms'][j]['bead_type'] == 'VS': + #The bead is a VS, therefore must be evaluated from the coordinates of the previous atoms + # [val['atom_list'] for val in ns.cg_itp['virutal_sitesn'] if val['bead_id'] == j][0] + la = ns.cg_itp['virutal_sitesn'][j]['atom_list'] + # VS_TYPE = 1 -> Center of Geometry + # VS_TYPE = 2 -> Center of Mass + # VS_TYPE = 3 -> Center of Weights (for each atom a weight must be given in the definition of the VS) + traj = [] + sel = ns.aa2cg_trajectory.atoms[la] + if ns.cg_itp['virutal_sitesn'][j]['vs_type'] == 1: + for fr in ns.aa2cg_trajectory.trajectory: + traj.append(sel.center_of_geometry()) + elif ns.cg_itp['virutal_sitesn'][j]['vs_type'] == 2: + for fr in ns.aa2cg_trajectory.trajectory: + traj.append(sel.center_of_mass()) + + coord[:, j, :] = np.array(traj) + #Final CG-coordinates + np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + return # use selected whole molecules as MDA atomgroups and make their coordinates whole, inplace, across the complete tAA rajectory @@ -1844,6 +1915,9 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False row_wise_ranges = {} row_wise_ranges['max_range_constraints'], row_wise_ranges['max_range_bonds'], row_wise_ranges['max_range_angles'], row_wise_ranges['max_range_dihedrals'] = 0, 0, 0, 0 + #Loading the mass of the atom-tpyes in case they are needed + fetch_cg_mass_itp() + # read ITP file to extract bonds, angles and dihedrals to compare OR get it from the optimization script to avoid re-reading trajectory + calculating hists at each execution # for reading ITP, groups are created by separating bonds/angles/etc lines by a return (\n) or a comment (;) if manual_mode: From 13de889df4e2a77c650c26ae1573e7aa52e3528f Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Mon, 21 Sep 2020 17:15:41 +0200 Subject: [PATCH 22/40] new aa2cg distribution estimation and call of the conversion --- swarmcg/config.py | 2 +- swarmcg/optimize_model.py | 7 +++++++ swarmcg/swarmCG.py | 36 +++++++++++++++++------------------- 3 files changed, 25 insertions(+), 20 deletions(-) diff --git a/swarmcg/config.py b/swarmcg/config.py index ba9248e..2940186 100644 --- a/swarmcg/config.py +++ b/swarmcg/config.py @@ -67,7 +67,7 @@ 'angle': [1, 2], 'dihedral': [1, 2, 4], 'dihedral_with_mult': [1, 4] - 'virtual_sitesn': [1] + 'virtual_sitesn': [1,2] # these functions use 3 parameters, the last one being multiplicity (if it's omitted gromacs will use 1 by default, we reproduce this behavior) } diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 1e1a9aa..d9863ae 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -264,6 +264,13 @@ def run(ns): # for each CG bead, create atom groups for trajectory geoms calculation using mass and atom weights across beads scg.get_beads_MDA_atomgroups(ns) + # mapping the trajectory aa2cg + print('Initializing the mapped trajectory') + scg.initialize_cg_traj(ns) + print('Mapping the trajectory from AA to CG representation') + scg.map_aa2cg_traj(ns) + + ns.gyr_aa_mapped, ns.gyr_aa_mapped_std = None, None # will be computed one single time with model evaluation script ns.sasa_aa_mapped, ns.sasa_aa_mapped_std = None, None # will be computed one single time with model evaluation script diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 6bc2adb..0231eda 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -186,6 +186,7 @@ def load_aa_data(ns): # check if functions present in CG ITP file can be used by this program, if not we throw an error +# Definitions containted in config.py def verify_handled_functions(geom, func_obj, line_obj): try: @@ -433,7 +434,7 @@ def read_cg_itp_file(ns, itp_lines): ) raise exceptions.MissformattedFile(msg) #Function is in the function list - func = verify_handled_functions('virtual_sitesn', vs_type, i + 1) + func = verify_handled_functions('virtual_sitesn', vs_type, i) #The cg_atoms in list_cg_atoms, checking that the indexes are lower than the one of the VS @@ -1497,17 +1498,15 @@ def create_bins_and_dist_matrices(ns, constraints=True): # calculate bonds distribution from AA trajectory def get_AA_bonds_distrib(ns, beads_ids, grp_type, grp_nb): - bond_values = np.empty(len(ns.aa_universe.trajectory) * len(beads_ids)) + bond_values = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2 = beads_ids[i] # print('bead_id_1:', bead_id_1, 'using atoms:', ns.mda_beads_atom_grps[bead_id_1].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_1]) # print('bead_id_2:', bead_id_2, 'using atoms:', ns.mda_beads_atom_grps[bead_id_2].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_2]) # print() frame_nb = 0 - for _ in ns.aa_universe.trajectory: - pos_1 = ns.mda_beads_atom_grps[bead_id_1].center(ns.mda_weights_atom_grps[bead_id_1], pbc=None, compound='group') # no need for PBC handling, trajectories were made wholes for the molecule - pos_2 = ns.mda_beads_atom_grps[bead_id_2].center(ns.mda_weights_atom_grps[bead_id_2], pbc=None, compound='group') - bond_values[len(ns.aa_universe.trajectory)*i+frame_nb] = mda.lib.distances.calc_bonds(pos_1, pos_2, backend=ns.mda_backend, box=None) / 10 # retrieve nm + for _ in ns.aa2cg_trajectory.trajectory: + bond_values[len(ns.aa2cg_trajectory.trajectory)*i+frame_nb] = mda.lib.distances.calc_bonds(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm frame_nb += 1 bond_avg_init = round(np.average(bond_values), 3) @@ -1565,15 +1564,12 @@ def get_AA_bonds_distrib(ns, beads_ids, grp_type, grp_nb): # calculate angles distribution from AA trajectory def get_AA_angles_distrib(ns, beads_ids): - angle_values_rad = np.empty(len(ns.aa_universe.trajectory) * len(beads_ids)) + angle_values_rad = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3 = beads_ids[i] frame_nb = 0 - for _ in ns.aa_universe.trajectory: - pos_1 = ns.mda_beads_atom_grps[bead_id_1].center(ns.mda_weights_atom_grps[bead_id_1], pbc=None, compound='group') # no need for PBC handling, trajectories were made wholes for the molecule - pos_2 = ns.mda_beads_atom_grps[bead_id_2].center(ns.mda_weights_atom_grps[bead_id_2], pbc=None, compound='group') - pos_3 = ns.mda_beads_atom_grps[bead_id_3].center(ns.mda_weights_atom_grps[bead_id_3], pbc=None, compound='group') - angle_values_rad[len(ns.aa_universe.trajectory)*i+frame_nb] = mda.lib.distances.calc_angles(pos_1, pos_2, pos_3, backend=ns.mda_backend, box=None) + for _ in ns.aa2cg_trajectory.trajectory: + angle_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+frame_nb] = mda.lib.distances.calc_angles(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, backend=ns.mda_backend, box=None) frame_nb += 1 angle_values_deg = np.rad2deg(angle_values_rad) @@ -1586,16 +1582,12 @@ def get_AA_angles_distrib(ns, beads_ids): # calculate dihedrals distribution from AA trajectory def get_AA_dihedrals_distrib(ns, beads_ids): - dihedral_values_rad = np.empty(len(ns.aa_universe.trajectory) * len(beads_ids)) + dihedral_values_rad = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3, bead_id_4 = beads_ids[i] frame_nb = 0 - for _ in ns.aa_universe.trajectory: - pos_1 = ns.mda_beads_atom_grps[bead_id_1].center(ns.mda_weights_atom_grps[bead_id_1], pbc=None, compound='group') # no need for PBC handling, trajectories were made wholes for the molecule - pos_2 = ns.mda_beads_atom_grps[bead_id_2].center(ns.mda_weights_atom_grps[bead_id_2], pbc=None, compound='group') - pos_3 = ns.mda_beads_atom_grps[bead_id_3].center(ns.mda_weights_atom_grps[bead_id_3], pbc=None, compound='group') - pos_4 = ns.mda_beads_atom_grps[bead_id_4].center(ns.mda_weights_atom_grps[bead_id_4], pbc=None, compound='group') - dihedral_values_rad[len(ns.aa_universe.trajectory)*i+frame_nb] = mda.lib.distances.calc_dihedrals(pos_1, pos_2, pos_3, pos_4, backend=ns.mda_backend, box=None) + for _ in ns.aa2cg_trajectory.trajectory: + dihedral_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+frame_nb] = mda.lib.distances.calc_dihedrals(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, ns.aa2cg_trajectory.atoms[bead_id_4].position, backend=ns.mda_backend, box=None) frame_nb += 1 dihedral_values_deg = np.rad2deg(dihedral_values_rad) @@ -1945,6 +1937,12 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False # for each CG bead, create atom groups for trajectory geoms calculation using mass and atom weights across beads get_beads_MDA_atomgroups(ns) + # mapping the trajectory aa2cg + print('Initializing the mapped trajectory') + scg.initialize_cg_traj(ns) + print('Mapping the trajectory from AA to CG representation') + scg.map_aa2cg_traj(ns) + if ns.atom_only: compute_Rg(ns, traj_type='AA') print() From da781818b8aef84368edf106b3a1a2c9b512ef3d Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Wed, 23 Sep 2020 12:13:45 +0200 Subject: [PATCH 23/40] Code working on evaluate_model (VS not tested) --- G1_DATA/cg_model.itp | 56 ++++---- G1_DATA/martini_v2.0_PEO_PS_CNP.itp | 4 + swarmcg/__init__.py | 2 +- swarmcg/analyze_optimization.py | 2 + swarmcg/config.py | 6 +- swarmcg/evaluate_model.py | 12 +- swarmcg/optimize_model.py | 2 + swarmcg/swarmCG.py | 197 ++++++++++++++++------------ 8 files changed, 164 insertions(+), 117 deletions(-) diff --git a/G1_DATA/cg_model.itp b/G1_DATA/cg_model.itp index c7c2461..1b765d5 100644 --- a/G1_DATA/cg_model.itp +++ b/G1_DATA/cg_model.itp @@ -7,31 +7,32 @@ G1 1 ; id type resnr residue atom cgnr charge 1 N0 1 G1 A1 1 0.00000 -2 N0 2 G1 A2 2 0.00000 -3 Nda 3 G1 A3 3 0.00000 -4 N0 4 G1 A4 4 0.00000 -5 Nda 5 G1 A5 5 0.00000 -6 Qd 6 G1 A6 6 1.00000 -7 Nda 7 G1 A7 7 0.00000 -8 Qd 8 G1 A8 8 1.00000 -9 Nda 9 G1 A9 9 0.00000 -10 N0 10 G1 A10 10 0.00000 -11 Nda 11 G1 A11 11 0.00000 -12 Qd 12 G1 A12 12 1.00000 -13 Nda 13 G1 A13 13 0.00000 -14 Qd 14 G1 A14 14 1.00000 -15 Nda 15 G1 A15 15 0.00000 -16 N0 16 G1 A16 16 0.00000 -17 Nda 17 G1 A17 17 0.00000 -18 Qd 18 G1 A18 18 1.00000 -19 Nda 19 G1 A19 19 0.00000 -20 Qd 20 G1 A20 20 1.00000 -21 Nda 21 G1 A21 21 0.00000 -22 N0 22 G1 A22 22 0.00000 -23 Nda 23 G1 A23 23 0.00000 -24 Qd 24 G1 A24 24 1.00000 -25 Nda 25 G1 A25 25 0.00000 -26 Qd 26 G1 A26 26 1.00000 +2 N0 1 G1 A2 2 0.00000 +3 Nda 1 G1 A3 3 0.00000 +4 N0 1 G1 A4 4 0.00000 +5 Nda 1 G1 A5 5 0.00000 +6 Qd 1 G1 A6 6 1.00000 +7 Nda 1 G1 A7 7 0.00000 +8 Qd 1 G1 A8 8 1.00000 +9 Nda 1 G1 A9 9 0.00000 +10 N0 1 G1 A10 10 0.00000 +11 Nda 1 G1 A11 11 0.00000 +12 Qd 1 G1 A12 12 1.00000 +13 Nda 1 G1 A13 13 0.00000 +14 Qd 1 G1 A14 14 1.00000 +15 Nda 1 G1 A15 15 0.00000 +16 N0 1 G1 A16 16 0.00000 +17 Nda 1 G1 A17 17 0.00000 +18 Qd 1 G1 A18 18 1.00000 +19 Nda 1 G1 A19 19 0.00000 +20 Qd 1 G1 A20 20 1.00000 +21 Nda 1 G1 A21 21 0.00000 +22 N0 1 G1 A22 22 0.00000 +23 Nda 1 G1 A23 23 0.00000 +24 Qd 1 G1 A24 24 1.00000 +25 Nda 1 G1 A25 25 0.00000 +26 Qd 1 G1 A26 26 1.00000 +27 VS 1 G1 VVV 27 1.00000 [ bonds ] @@ -70,6 +71,9 @@ G1 1 23 24 1 0 0 ; B4 25 26 1 0 0 ; B4 +; bond VS + 1 27 1 0 0 ; B4 + [ angles ] ; i j k funct angle force.c. @@ -114,3 +118,5 @@ G1 1 22 23 24 2 180 0 ; A5 22 25 26 2 180 0 ; A5 +[ virtual_sitesn ] +27 2 10 11 12 diff --git a/G1_DATA/martini_v2.0_PEO_PS_CNP.itp b/G1_DATA/martini_v2.0_PEO_PS_CNP.itp index a101b30..e6ff3be 100644 --- a/G1_DATA/martini_v2.0_PEO_PS_CNP.itp +++ b/G1_DATA/martini_v2.0_PEO_PS_CNP.itp @@ -120,6 +120,10 @@ SCY 45.0 0.000 A 0.0 0.0 ; backbone bead ; PEO and CiEj surfactants EO 45.0 0.000 A 0.0 0.0 +; VS +VS 0.0 0.000 V 0.0 0.0 + + [ nonbond_params ] diff --git a/swarmcg/__init__.py b/swarmcg/__init__.py index 218644a..d6830a1 100644 --- a/swarmcg/__init__.py +++ b/swarmcg/__init__.py @@ -1 +1 @@ -__version__ = 'v1.1.2' \ No newline at end of file +__version__ = '1.1.2T' diff --git a/swarmcg/analyze_optimization.py b/swarmcg/analyze_optimization.py index 3e8185b..a8a36d4 100644 --- a/swarmcg/analyze_optimization.py +++ b/swarmcg/analyze_optimization.py @@ -662,3 +662,5 @@ def main(): run(ns) +if __name__ == "__main__": + main() diff --git a/swarmcg/config.py b/swarmcg/config.py index 2940186..d02dd13 100644 --- a/swarmcg/config.py +++ b/swarmcg/config.py @@ -62,12 +62,12 @@ # TODO: handle dihedral function 9 correctly so that different potentials can be stacked # TODO: for the same beads -- this is the primary purpose of function 9 !! handled_functions = { - 'contraint': [1], + 'constraint': [1], 'bond': [1], 'angle': [1, 2], 'dihedral': [1, 2, 4], - 'dihedral_with_mult': [1, 4] - 'virtual_sitesn': [1,2] + 'dihedral_with_mult': [1, 4], + 'virtual_sitesn': [1,2], # these functions use 3 parameters, the last one being multiplicity (if it's omitted gromacs will use 1 by default, we reproduce this behavior) } diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index 0d99ab8..c502f39 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -25,6 +25,10 @@ def run(ns): # TODO: make it possible to feed a delta for Rg in case the model has scaling ? + # get basenames for simulation files + ns.cg_itp_basename = os.path.basename(ns.cg_itp_filename) + ns.top_input_basename = os.path.basename(ns.top_input_filename) + ns.molname_in = None # TODO: arguments that exist only in the scope of optimization (useless for manual model evaluation) -- but this could be modified to be allowed to evaluate models in mixed membranes, averaging distribs for given molecule name only ns.gyr_aa_mapped, ns.gyr_aa_mapped_std = None, None # ns.sasa_aa_mapped, ns.sasa_aa_mapped_std = None, None @@ -128,6 +132,9 @@ def main(): help='XTC file of your CG trajectory (omit for solo AA inspection)', type=str, default=config.metavar_cg_traj, metavar=' ' + scg.par_wrap(config.metavar_cg_traj)) + required_args.add_argument('-cg_top', dest='top_input_filename', + help='TOP file used for iterative simulation', type=str, + default='system.top', metavar=' (system.top)') # required_args.add_argument('-figmolname', dest='figmolname', help='TODO REMOVE', type=str, required=True) # TODO: remove, this was just for figures optional_args = args_parser.add_argument_group(bullet + 'CG MODEL SCALING') @@ -201,4 +208,7 @@ def main(): print('Working directory:', os.getcwd()) print('Command line:', input_cmdline) - run(ns) \ No newline at end of file + run(ns) + +if __name__ == "__main__": + main() diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index d9863ae..463b409 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -745,3 +745,5 @@ def main(): run(ns) +if __name__ == "__main__": + main() diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 0231eda..e150c90 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -241,7 +241,7 @@ def read_cg_itp_file(ns, itp_lines): else: #Stripping comments from the input line - aux_itp_line = strip(itp_line,";") + aux_itp_line = strip_comment(itp_line,";") sp_itp_line = aux_itp_line.split() if r_moleculetype: @@ -427,7 +427,7 @@ def read_cg_itp_file(ns, itp_lines): raise exceptions.MissformattedFile(msg) else: #Check if the bead is defined as VS - if ns.cg_itp['atoms'][bead_id]['bead_type'] != 'VS': + if ns.cg_itp['atoms'][bead_id]['bead_type'] != 'VS': msg = ( "The virtual site {} should be defined with bead type" " VS".format(bead_id+1) @@ -447,8 +447,8 @@ def read_cg_itp_file(ns, itp_lines): ) raise exceptions.MissformattedFile(msg) - # ns.cg_itp['virutal_sitesn'].append({'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist}) - ns.cg_itp['virutal_sitesn'][bead_id] = {'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist} + # ns.cg_itp['virtual_sitesn'].append({'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist}) + ns.cg_itp['virtual_sitesn'][bead_id] = {'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist} elif r_exclusion: @@ -459,12 +459,13 @@ def read_cg_itp_file(ns, itp_lines): # TODO: make these messages more clear and CORRECT for the dihedral function handling -- also explain this is the current Opti.CG implementation, function 9 might come in next version # TODO: check what kind of error or processing is done when a correct line is duplicated within a group ?? probably it goes on in a bad way - msg = ( - f"In the provided CG ITP file {geom} have been grouped, but {geom} group " - f"{str(grp_geom + 1)} holds lines that have different parameters. Parameters should be " - f"identical within a group, only CG beads IDs should differ. " - f"Please correct the CG ITP file and separate groups using a blank or commented line" - ) + +# msg = ( +# f"In the provided CG ITP file {geom} have been grouped, but {geom} group " +# f"{str(grp_geom + 1)} holds lines that have different parameters. Parameters should be " +# f"identical within a group, only CG beads IDs should differ. " +# f"Please correct the CG ITP file and separate groups using a blank or commented line" +# ) for geom in ['constraint']: # constraints only for grp_geom in range(len(ns.cg_itp[geom])): for var in ['funct', 'value']: @@ -510,14 +511,33 @@ def read_cg_itp_file(ns, itp_lines): return +def pop_empty_lines(file): + # Popping out all the empty lines + list_idx = [value for value in range(len(file)) if file[value] == ''] + list_idx.reverse() + for idx in list_idx: + file.pop(idx) + + return + #This function reads the defaults masses associated to each atomtype loaded into the topology file def fetch_cg_mass_itp(ns): #Declaring the ns.cg_atomtypes = {} in order to retreive the mass of each particle whenever is missing by searching the type as arguments ns.cg_atomtypes_mass = {} #Parsing the topology file to find all the .itp included list_itp = [] - with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename, 'r') as fp: - all_top_lines = fp.read().split('\n') + + # Checking if the namespaces contains the folder specs. + # This is done to distinguish between optimize and evaluate models + if hasattr(ns,'exec_folder') and hasattr(config,'input_sim_files_dirname'): + with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename, 'r') as fp: + all_top_lines = fp.read().split('\n') + else: + with open( ns.top_input_basename, 'r') as fp: + all_top_lines = fp.read().split('\n') + + pop_empty_lines(all_top_lines) + for line in all_top_lines: if line.split()[0] == "#include": #Reading the filename of the loaded .itps @@ -526,15 +546,20 @@ def fetch_cg_mass_itp(ns): #Reading all the atomtypes within each .itp found in the topology file for itp_name in list_itp: - with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + itp_name, 'r') as fp: - itp_file = fp.read().split('\n') + if hasattr(ns, 'exec_folder') and hasattr(config, 'input_sim_files_dirname'): + with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + itp_name, 'r') as fp: + itp_file = fp.read().split('\n') + else: + with open(itp_name, 'r') as fp: + itp_file = fp.read().split('\n') + #Stripping all comments from the list of line for i in range(len(itp_file)): - itp_file[i] = strip(itp_file[i],";") + itp_file[i] = strip_comment(itp_file[i],";") #Popping out all the empty lines - list_idx = [index for index, value in enumerate(itp_file) if value == ""] + list_idx = [value for value in range(len(itp_file)) if itp_file[value] == ''] list_idx.reverse() for idx in list_idx: itp_file.pop(idx) @@ -544,15 +569,20 @@ def fetch_cg_mass_itp(ns): #The lines of the file should be now cleaned, therefore it is possible to skip all the checks to monitor empty lines for line in itp_file: - words = line.split() - if bAtomTypes: - ns.cg_atomtypes_mass[words[0]] = float(words[1]) + if len(line.split()) != 0: + words = line.split() + #Searching the atomtype keyword + if words[0] == "[": + if words[1] == "atomtypes": + bAtomTypes = True + elif words[1] != "atomtypes": + bAtomTypes = False + continue + if bAtomTypes: + ns.cg_atomtypes_mass[words[0]] = float(words[1]) + else: + break - #Searching the atomtype keyword - if (words[0] == "[" and words[0] == "atomtypes" and words[0] == "]"): - bAtomTypes = True - elif words[0] == "[" and words[1] != "atomtypes": - bAtomTypes = False return @@ -674,17 +704,15 @@ def compute_Rg(ns, traj_type): elif traj_type == 'AA_mapped': gyr_aa_mapped = np.empty(len(ns.aa_universe.trajectory)) - frame_nb = 0 total_mass = sum([ns.cg_universe.atoms[bead_id].mass for bead_id in range(len(ns.cg_itp['atoms']))]) beads_masses = np.array([np.array([ns.cg_universe.atoms[bead_id].mass]) for bead_id in range(len(ns.cg_itp['atoms']))]) # print('BEADS MASSES CG for Rg calculation AA-mapped:\n', beads_masses) - for _ in ns.aa_universe.trajectory: + for ts in ns.aa_universe.trajectory: mapped_pos = np.array([ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None, compound='group') for bead_id in range(len(ns.cg_itp['atoms']))]) com = np.sum(beads_masses * mapped_pos, axis=0) / total_mass mapped_pos_dist_com = mda.lib.distances.distance_array(com, mapped_pos, backend=ns.mda_backend) - gyr_aa_mapped[frame_nb] = np.sqrt(np.sum(beads_masses.reshape(1,len(beads_masses)) * np.power(mapped_pos_dist_com, 2)) / total_mass) - frame_nb += 1 + gyr_aa_mapped[ts.frame] = np.sqrt(np.sum(beads_masses.reshape(1,len(beads_masses)) * np.power(mapped_pos_dist_com, 2)) / total_mass) ns.gyr_aa_mapped = round(np.average(gyr_aa_mapped)/10 + ns.aa_rg_offset, 3) # retrieve nm ns.gyr_aa_mapped_std = round(np.std(gyr_aa_mapped)/10, 3) # retrieve nm @@ -1375,20 +1403,24 @@ def initialize_cg_traj(ns): # sel = ns.cg_universe2.atoms[:len(ns.cg_itp['atoms'])] # I generate a numpy array of the size np.zeros(len(ns.aa_universe.trajectory,len(ns.cg_itp['atoms']))) # coord = np.zeros((len(ns.aa_universe.trajectory),len(ns.cg_itp['atoms']),3)) - # np.aa2cg_trajectory = mda.Merge(sel) - # np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + # ns.aa2cg_trajectory = mda.Merge(sel) + # ns.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) masses = np.array([val['mass'] for val in ns.cg_itp['atoms']]) names = np.array([val['atom'] for val in ns.cg_itp['atoms']]) resname = np.array([val['residue'] for val in ns.cg_itp['atoms']]) resid = np.array([val['resnr'] for val in ns.cg_itp['atoms']]) nr = len(list(set([val['resnr'] for val in ns.cg_itp['atoms']]))) - np.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']), nr, resindex=resid, trajectory=True) - np.aa2cg_trajectory.add_TopologyAttr('masses') - np.aa2cg_trajectory._topology.masses.values = np.array(masses) - np.aa2cg_trajectory.add_TopologyAttr('name') - np.aa2cg_trajectory._topology.names.values = names - np.aa2cg_trajectory.add_TopologyAttr('resnames') - np.aa2cg_trajectory._topology.resnames.values = resname + print(list(set([val['resnr'] for val in ns.cg_itp['atoms']]))) + print(nr) + ns.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']),n_residues=nr,atom_resindex=resid,n_segments=1,residue_segindex=np.ones(nr), trajectory=True) + # ns.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']), 1,n_residues=nr,atom_resindex=resid,n_segments=1,residue_segindex=np.ones(nr), trajectory=True) + # ns.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']), nr, resindex=resid, trajectory=True) + ns.aa2cg_trajectory.add_TopologyAttr('masses') + ns.aa2cg_trajectory._topology.masses.values = np.array(masses) + ns.aa2cg_trajectory.add_TopologyAttr('name') + ns.aa2cg_trajectory._topology.names.values = names + ns.aa2cg_trajectory.add_TopologyAttr('resnames') + ns.aa2cg_trajectory._topology.resnames.values = resname #Assigning to the new universe the masses related to the CG @@ -1398,47 +1430,50 @@ def initialize_cg_traj(ns): return #Strip the comments from the list -def strip(line,val): - return line[:line.find(val)] +def strip_comment(line,val): + if line.find(val) >= 0: + return line[:line.find(val)] + else: + return line + def map_aa2cg_traj(ns): # for i in range(len(ns.aa_universe.trajectory)): # I will estimate the coordinates of each bead within all the frames using the iterator of mda and the function center_of_mass() coord = np.zeros((len(ns.aa_universe.trajectory), len(ns.cg_itp['atoms']), 3)) - for j in range(len(ns.cg_itp['atoms'])): + for bead_id in range(len(ns.cg_itp['atoms'])): #Check if the atomtype of the cg is related to a VS - if ns.cg_itp['atoms'][j]['bead_type'] != 'VS': + if ns.cg_itp['atoms'][bead_id]['bead_type'] != 'VS': #The bead is not a VS therefore must be evaluated starting from the AA - la = ns.all_beads[j]['atoms_id'] - sel = ns.aa_universe.atoms[la] - traj = [] - for fr in ns.aa_universe.trajectory: - traj.append(sel.center_of_mass()) - coord[:,j,:] = np.array(traj) + traj = np.empty((len(ns.aa_universe.trajectory),3)) + for ts in ns.aa_universe.trajectory: + # print(ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None, + # compound='group')) + traj[ts.frame] = ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None,compound='group') # no need for PBC handling, trajectories were made wholes for the molecule + coord[:,bead_id,:] = traj - np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + ns.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) for j in range(len(ns.cg_itp['atoms'])): if ns.cg_itp['atoms'][j]['bead_type'] == 'VS': #The bead is a VS, therefore must be evaluated from the coordinates of the previous atoms - # [val['atom_list'] for val in ns.cg_itp['virutal_sitesn'] if val['bead_id'] == j][0] - la = ns.cg_itp['virutal_sitesn'][j]['atom_list'] + la = ns.cg_itp['virtual_sitesn'][j]['atom_list'] # VS_TYPE = 1 -> Center of Geometry # VS_TYPE = 2 -> Center of Mass # VS_TYPE = 3 -> Center of Weights (for each atom a weight must be given in the definition of the VS) - traj = [] + traj = np.empty((len(ns.aa_universe.trajectory),3)) sel = ns.aa2cg_trajectory.atoms[la] - if ns.cg_itp['virutal_sitesn'][j]['vs_type'] == 1: - for fr in ns.aa2cg_trajectory.trajectory: - traj.append(sel.center_of_geometry()) - elif ns.cg_itp['virutal_sitesn'][j]['vs_type'] == 2: - for fr in ns.aa2cg_trajectory.trajectory: - traj.append(sel.center_of_mass()) - - coord[:, j, :] = np.array(traj) + if ns.cg_itp['virtual_sitesn'][j]['vs_type'] == 1: + for ts in ns.aa2cg_trajectory.trajectory: + traj[ts.frame] = sel.center_of_geometry(pbc=None) + elif ns.cg_itp['virtual_sitesn'][j]['vs_type'] == 2: + for ts in ns.aa2cg_trajectory.trajectory: + traj[ts.frame] = sel.center_of_mass(pbc=None) + + coord[:, j, :] = traj #Final CG-coordinates - np.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + ns.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) return @@ -1504,10 +1539,8 @@ def get_AA_bonds_distrib(ns, beads_ids, grp_type, grp_nb): # print('bead_id_1:', bead_id_1, 'using atoms:', ns.mda_beads_atom_grps[bead_id_1].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_1]) # print('bead_id_2:', bead_id_2, 'using atoms:', ns.mda_beads_atom_grps[bead_id_2].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_2]) # print() - frame_nb = 0 - for _ in ns.aa2cg_trajectory.trajectory: - bond_values[len(ns.aa2cg_trajectory.trajectory)*i+frame_nb] = mda.lib.distances.calc_bonds(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm - frame_nb += 1 + for ts in ns.aa2cg_trajectory.trajectory: + bond_values[len(ns.aa2cg_trajectory.trajectory)*i+ts.frame] = mda.lib.distances.calc_bonds(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm bond_avg_init = round(np.average(bond_values), 3) @@ -1567,10 +1600,8 @@ def get_AA_angles_distrib(ns, beads_ids): angle_values_rad = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3 = beads_ids[i] - frame_nb = 0 - for _ in ns.aa2cg_trajectory.trajectory: - angle_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+frame_nb] = mda.lib.distances.calc_angles(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, backend=ns.mda_backend, box=None) - frame_nb += 1 + for ts in ns.aa2cg_trajectory.trajectory: + angle_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+ts.frame] = mda.lib.distances.calc_angles(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, backend=ns.mda_backend, box=None) angle_values_deg = np.rad2deg(angle_values_rad) angle_avg = round(np.mean(angle_values_deg), 3) @@ -1585,10 +1616,8 @@ def get_AA_dihedrals_distrib(ns, beads_ids): dihedral_values_rad = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3, bead_id_4 = beads_ids[i] - frame_nb = 0 - for _ in ns.aa2cg_trajectory.trajectory: - dihedral_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+frame_nb] = mda.lib.distances.calc_dihedrals(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, ns.aa2cg_trajectory.atoms[bead_id_4].position, backend=ns.mda_backend, box=None) - frame_nb += 1 + for ts in ns.aa2cg_trajectory.trajectory: + dihedral_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+ts.frame] = mda.lib.distances.calc_dihedrals(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, ns.aa2cg_trajectory.atoms[bead_id_4].position, backend=ns.mda_backend, box=None) dihedral_values_deg = np.rad2deg(dihedral_values_rad) dihedral_avg = round(np.mean(dihedral_values_deg), 3) @@ -1603,10 +1632,8 @@ def get_CG_bonds_distrib(ns, beads_ids, grp_type): bond_values = np.empty(len(ns.cg_universe.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2 = beads_ids[i] - frame_nb = 0 - for _ in ns.cg_universe.trajectory: # no need for PBC handling, trajectories were made wholes for the molecule - bond_values[len(ns.cg_universe.trajectory)*i+frame_nb] = mda.lib.distances.calc_bonds(ns.cg_universe.atoms[bead_id_1].position, ns.cg_universe.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm - frame_nb += 1 + for ts in ns.cg_universe.trajectory: # no need for PBC handling, trajectories were made wholes for the molecule + bond_values[len(ns.cg_universe.trajectory)*i+ts.frame] = mda.lib.distances.calc_bonds(ns.cg_universe.atoms[bead_id_1].position, ns.cg_universe.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm bond_avg = round(np.mean(bond_values), 3) if grp_type == 'constraint': @@ -1623,10 +1650,8 @@ def get_CG_angles_distrib(ns, beads_ids): angle_values_rad = np.empty(len(ns.cg_universe.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3 = beads_ids[i] - frame_nb = 0 - for _ in ns.cg_universe.trajectory: # no need for PBC handling, trajectories were made wholes for the molecule - angle_values_rad[len(ns.cg_universe.trajectory)*i+frame_nb] = mda.lib.distances.calc_angles(ns.cg_universe.atoms[bead_id_1].position, ns.cg_universe.atoms[bead_id_2].position, ns.cg_universe.atoms[bead_id_3].position, backend=ns.mda_backend, box=None) - frame_nb += 1 + for ts in ns.cg_universe.trajectory: # no need for PBC handling, trajectories were made wholes for the molecule + angle_values_rad[len(ns.cg_universe.trajectory)*i+ts.frame] = mda.lib.distances.calc_angles(ns.cg_universe.atoms[bead_id_1].position, ns.cg_universe.atoms[bead_id_2].position, ns.cg_universe.atoms[bead_id_3].position, backend=ns.mda_backend, box=None) angle_values_deg = np.rad2deg(angle_values_rad) # get group average and histogram non-null values for comparison and display @@ -1642,10 +1667,8 @@ def get_CG_dihedrals_distrib(ns, beads_ids): dihedral_values_rad = np.empty(len(ns.cg_universe.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3, bead_id_4 = beads_ids[i] - frame_nb = 0 - for _ in ns.cg_universe.trajectory: # no need for PBC handling, trajectories were made wholes for the molecule - dihedral_values_rad[len(ns.cg_universe.trajectory)*i+frame_nb] = mda.lib.distances.calc_dihedrals(ns.cg_universe.atoms[bead_id_1].position, ns.cg_universe.atoms[bead_id_2].position, ns.cg_universe.atoms[bead_id_3].position, ns.cg_universe.atoms[bead_id_4].position, backend=ns.mda_backend, box=None) - frame_nb += 1 + for ts in ns.cg_universe.trajectory: # no need for PBC handling, trajectories were made wholes for the molecule + dihedral_values_rad[len(ns.cg_universe.trajectory)*i+ts.frame] = mda.lib.distances.calc_dihedrals(ns.cg_universe.atoms[bead_id_1].position, ns.cg_universe.atoms[bead_id_2].position, ns.cg_universe.atoms[bead_id_3].position, ns.cg_universe.atoms[bead_id_4].position, backend=ns.mda_backend, box=None) dihedral_values_deg = np.rad2deg(dihedral_values_rad) # get group average and histogram non-null values for comparison and display @@ -1908,7 +1931,7 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False row_wise_ranges['max_range_constraints'], row_wise_ranges['max_range_bonds'], row_wise_ranges['max_range_angles'], row_wise_ranges['max_range_dihedrals'] = 0, 0, 0, 0 #Loading the mass of the atom-tpyes in case they are needed - fetch_cg_mass_itp() + fetch_cg_mass_itp(ns) # read ITP file to extract bonds, angles and dihedrals to compare OR get it from the optimization script to avoid re-reading trajectory + calculating hists at each execution # for reading ITP, groups are created by separating bonds/angles/etc lines by a return (\n) or a comment (;) @@ -1939,9 +1962,9 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False # mapping the trajectory aa2cg print('Initializing the mapped trajectory') - scg.initialize_cg_traj(ns) + initialize_cg_traj(ns) print('Mapping the trajectory from AA to CG representation') - scg.map_aa2cg_traj(ns) + map_aa2cg_traj(ns) if ns.atom_only: compute_Rg(ns, traj_type='AA') From 1f624f5282d417c4dc5edb0285da5336544b874f Mon Sep 17 00:00:00 2001 From: fiskissimo Date: Wed, 23 Sep 2020 17:11:41 +0200 Subject: [PATCH 24/40] MOT-CG handling VS_n --- G1_DATA/start_conf.gro | 3 ++- G1_DATA/system.top | 2 +- swarmcg/optimize_model.py | 21 +++++++++--------- swarmcg/swarmCG.py | 45 +++++++++++++++++++++------------------ 4 files changed, 38 insertions(+), 33 deletions(-) diff --git a/G1_DATA/start_conf.gro b/G1_DATA/start_conf.gro index 2999091..93198e8 100644 --- a/G1_DATA/start_conf.gro +++ b/G1_DATA/start_conf.gro @@ -1,5 +1,5 @@ g1_GMX.gro created by acpype (Rev: 10101) on Thu Sep 12 17:34:03 2019 t= 0.00000 step= 0 - 1281 + 1282 1PG1 N1 1 2.936 2.913 2.508 1PG1 C2 2 2.896 2.600 2.705 1PG1 H7 3 3.134 3.247 2.318 @@ -26,6 +26,7 @@ g1_GMX.gro created by acpype (Rev: 10101) on Thu Sep 12 17:34:03 2019 t= 0.000 1PG1 H9 24 2.384 3.105 3.680 1PG1 H11 25 3.353 3.308 3.377 1PG1 N7 26 3.705 3.490 3.432 + 1PG1 N7 26 3.705 3.490 3.432 2W W 27 0.084 3.595 3.359 3W W 28 0.460 2.488 2.882 4W W 29 3.165 2.218 0.652 diff --git a/G1_DATA/system.top b/G1_DATA/system.top index dc8a43f..16c9bb8 100644 --- a/G1_DATA/system.top +++ b/G1_DATA/system.top @@ -11,4 +11,4 @@ G1 (PAMAM) in water ; Compound #mols G1 1 W 1247 -CL- 8 +CL- 8 \ No newline at end of file diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 463b409..81c7223 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -88,16 +88,17 @@ def run(ns): arg_entry = user_provided_filenames[i] if not os.path.isfile(arg_entries[arg_entry]): data_folder_path = ns.input_folder+'/'+arg_entries[arg_entry] - if ns.input_folder != '.' and os.path.isfile(data_folder_path): - arg_entries[arg_entry] = data_folder_path - else: - if ns.input_folder == '': - data_folder_path = arg_entries[arg_entry] - msg = ( - f"Cannot find file for argument - {args_names[i]} " - f"(expected at location: {data_folder_path})" - ) - raise FileNotFoundError(msg) + if ns.input_folder != '.' and os.path.isfile(data_folder_path): + arg_entries[arg_entry] = data_folder_path + else: + if ns.input_folder == '': + data_folder_path = arg_entries[arg_entry] + print(data_folder_path) + msg = ( + 'Cannot find file for argument - {} ' + '(expected at location: {})'.format(args_names[i],data_folder_path) + ) + raise FileNotFoundError(msg) # check that gromacs alias is correct with open(os.devnull, 'w') as devnull: diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index e150c90..0853d21 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -214,6 +214,8 @@ def read_cg_itp_file(ns, itp_lines): print('Reading Coarse-Grained (CG) ITP file') ns.cg_itp = {'moleculetype': {'molname': '', 'nrexcl': 0}, 'atoms': [], 'constraint': [], 'bond': [], 'angle': [], 'dihedral': [], 'exclusion': [], 'virtual_sitesn': {}} + ns.real_beads_ids = [] + ns.vs_beads_ids = [] ns.nb_constraints, ns.nb_bonds, ns.nb_angles, ns.nb_dihedrals = -1, -1, -1, -1 for i in range(len(itp_lines)): @@ -273,6 +275,12 @@ def read_cg_itp_file(ns, itp_lines): ) raise exceptions.MissformattedFile(msg) + #Making real beads and vs list of ids + if bead_type == 'VS': + ns.vs_beads_ids.append(int(bead_id) - 1) + else: + ns.real_beads_ids.append(int(bead_id) - 1) + #Assignment of the variables value ns.cg_itp['atoms'].append({'bead_id': int(bead_id) - 1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue,'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge), 'mass': float(mass)}) @@ -415,7 +423,7 @@ def read_cg_itp_file(ns, itp_lines): # We need to define the function types for the VSn #Read VS index, and VS function, list_cg_atoms - bead_id, vs_type, cg_atomlist = int(sp_itp_line[0])-1, sp_itp_line[1], [int(bid)-1 for bid in sp_itp_line[2:]] + bead_id, vs_type, cg_atomlist = int(sp_itp_line[0])-1, int(sp_itp_line[1]), [int(bid)-1 for bid in sp_itp_line[2:]] #Check if the bead is defined in the atom list @@ -529,11 +537,13 @@ def fetch_cg_mass_itp(ns): # Checking if the namespaces contains the folder specs. # This is done to distinguish between optimize and evaluate models - if hasattr(ns,'exec_folder') and hasattr(config,'input_sim_files_dirname'): + print(os.getcwd()) + if hasattr(ns,'exec_folder') or hasattr(config,'input_sim_files_dirname'): + print(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename) with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename, 'r') as fp: all_top_lines = fp.read().split('\n') else: - with open( ns.top_input_basename, 'r') as fp: + with open(ns.top_input_basename, 'r') as fp: all_top_lines = fp.read().split('\n') pop_empty_lines(all_top_lines) @@ -707,11 +717,10 @@ def compute_Rg(ns, traj_type): total_mass = sum([ns.cg_universe.atoms[bead_id].mass for bead_id in range(len(ns.cg_itp['atoms']))]) beads_masses = np.array([np.array([ns.cg_universe.atoms[bead_id].mass]) for bead_id in range(len(ns.cg_itp['atoms']))]) # print('BEADS MASSES CG for Rg calculation AA-mapped:\n', beads_masses) - - for ts in ns.aa_universe.trajectory: - mapped_pos = np.array([ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None, compound='group') for bead_id in range(len(ns.cg_itp['atoms']))]) - com = np.sum(beads_masses * mapped_pos, axis=0) / total_mass - mapped_pos_dist_com = mda.lib.distances.distance_array(com, mapped_pos, backend=ns.mda_backend) + for ts in ns.aa2cg_trajectory.trajectory: + # mapped_pos = np.array([ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None, compound='group') for bead_id in range(len(ns.cg_itp['atoms']))]) + com = np.sum(beads_masses * ts.positions, axis=0) / total_mass + mapped_pos_dist_com = mda.lib.distances.distance_array(com, ts.positions, backend=ns.mda_backend) gyr_aa_mapped[ts.frame] = np.sqrt(np.sum(beads_masses.reshape(1,len(beads_masses)) * np.power(mapped_pos_dist_com, 2)) / total_mass) ns.gyr_aa_mapped = round(np.average(gyr_aa_mapped)/10 + ns.aa_rg_offset, 3) # retrieve nm ns.gyr_aa_mapped_std = round(np.std(gyr_aa_mapped)/10, 3) # retrieve nm @@ -973,17 +982,13 @@ def print_cg_itp_file(itp_obj, out_path_itp, print_sections=['constraint', 'bond else: fp.write('{0:<4} {1:>4} {6:>2} {2:>6} {3:>6} {4:<4} {5:9.5f}\n'.format(itp_obj['atoms'][i]['bead_id']+1, itp_obj['atoms'][i]['bead_type'], itp_obj['atoms'][i]['residue'], itp_obj['atoms'][i]['atom'], i+1, itp_obj['atoms'][i]['charge'], itp_obj['atoms'][i]['resnr'])) - fp.write('\n\n[ ]\n') - fp.write('; id type resnr residue atom cgnr charge mass\n\n') + # fp.write('\n\n[ ]\n') + # fp.write('; id type resnr residue atom cgnr charge mass\n\n') if len(itp_obj['virtual_sitesn']) > 0: fp.write('\n\n[ virtual_sitesn ]\n') - for i in range(len(itp_obj['virtual_sitesn'])): - - fp.write('{0:<4} {1:>4} {}\n'.format( - itp_obj['virtual_sitesn'][i]['bead_id'] + 1, - itp_obj['virtual_sitesn'][i]['vs_type']), - ' '.join([str(bid+1) for bid in itp_obj['virtual_sitesn'][i]['atom_list']])) + for vsite in itp_obj['virtual_sitesn']: + fp.write('{} {} {}\n'.format(str(itp_obj['virtual_sitesn'][vsite]['bead_id'] + 1), str(itp_obj['virtual_sitesn'][vsite]['vs_type']), ' '.join([str(bid+1) for bid in itp_obj['virtual_sitesn'][vsite]['atom_list']]))) if 'constraint' in print_sections and 'constraint' in itp_obj and len(itp_obj['constraint']) > 0: fp.write('\n\n[ constraints ]\n') @@ -1538,7 +1543,7 @@ def get_AA_bonds_distrib(ns, beads_ids, grp_type, grp_nb): bead_id_1, bead_id_2 = beads_ids[i] # print('bead_id_1:', bead_id_1, 'using atoms:', ns.mda_beads_atom_grps[bead_id_1].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_1]) # print('bead_id_2:', bead_id_2, 'using atoms:', ns.mda_beads_atom_grps[bead_id_2].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_2]) - # print() + # print(beads_ids[i]) for ts in ns.aa2cg_trajectory.trajectory: bond_values[len(ns.aa2cg_trajectory.trajectory)*i+ts.frame] = mda.lib.distances.calc_bonds(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm @@ -1930,8 +1935,6 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False row_wise_ranges = {} row_wise_ranges['max_range_constraints'], row_wise_ranges['max_range_bonds'], row_wise_ranges['max_range_angles'], row_wise_ranges['max_range_dihedrals'] = 0, 0, 0, 0 - #Loading the mass of the atom-tpyes in case they are needed - fetch_cg_mass_itp(ns) # read ITP file to extract bonds, angles and dihedrals to compare OR get it from the optimization script to avoid re-reading trajectory + calculating hists at each execution # for reading ITP, groups are created by separating bonds/angles/etc lines by a return (\n) or a comment (;) @@ -1946,8 +1949,8 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False msg = "Cannot read CG ITP, it seems you provided a binary file." raise exceptions.MissformattedFile(msg) - # if we do not have reference already from the optimization procedure - if manual_mode: + # Loading the mass of the atom-tpyes in case they are needed + fetch_cg_mass_itp(ns) # read AA traj + find atom bonds connectivity and atom types (to differentiate heavy/hydrogens) print() From 163721e0f09758eda3175451d153f63779b7b6dc Mon Sep 17 00:00:00 2001 From: CharlyEmpereurMot Date: Thu, 24 Sep 2020 08:18:42 +0200 Subject: [PATCH 25/40] ongoing --- G1_DATA/cg_model.itp | 7 +- swarmcg/evaluate_model.py | 28 +- swarmcg/optimize_model.py | 7 +- swarmcg/shared/exceptions.py | 7 +- swarmcg/shared/styling.py | 4 +- .../{shared => simulations}/vs_functions.py | 0 swarmcg/swarmCG.py | 378 ++++++++---------- tests/data/cg_model.itp | 139 +++++++ 8 files changed, 338 insertions(+), 232 deletions(-) rename swarmcg/{shared => simulations}/vs_functions.py (100%) create mode 100644 tests/data/cg_model.itp diff --git a/G1_DATA/cg_model.itp b/G1_DATA/cg_model.itp index 1b765d5..8147237 100644 --- a/G1_DATA/cg_model.itp +++ b/G1_DATA/cg_model.itp @@ -32,7 +32,6 @@ G1 1 24 Qd 1 G1 A24 24 1.00000 25 Nda 1 G1 A25 25 0.00000 26 Qd 1 G1 A26 26 1.00000 -27 VS 1 G1 VVV 27 1.00000 [ bonds ] @@ -71,9 +70,6 @@ G1 1 23 24 1 0 0 ; B4 25 26 1 0 0 ; B4 -; bond VS - 1 27 1 0 0 ; B4 - [ angles ] ; i j k funct angle force.c. @@ -118,5 +114,4 @@ G1 1 22 23 24 2 180 0 ; A5 22 25 26 2 180 0 ; A5 -[ virtual_sitesn ] -27 2 10 11 12 + diff --git a/swarmcg/evaluate_model.py b/swarmcg/evaluate_model.py index c502f39..025b823 100644 --- a/swarmcg/evaluate_model.py +++ b/swarmcg/evaluate_model.py @@ -21,13 +21,13 @@ def run(ns): from numpy import VisibleDeprecationWarning - warnings.filterwarnings("ignore", category=VisibleDeprecationWarning) # filter MDAnalysis + numpy deprecation stuff that is annoying + warnings.filterwarnings("ignore", category=VisibleDeprecationWarning) # filter MDAnalysis + numpy deprecation stuff that is annoying # TODO: make it possible to feed a delta for Rg in case the model has scaling ? # get basenames for simulation files ns.cg_itp_basename = os.path.basename(ns.cg_itp_filename) - ns.top_input_basename = os.path.basename(ns.top_input_filename) + # ns.top_input_basename = os.path.basename(ns.top_input_filename) ns.molname_in = None # TODO: arguments that exist only in the scope of optimization (useless for manual model evaluation) -- but this could be modified to be allowed to evaluate models in mixed membranes, averaging distribs for given molecule name only ns.gyr_aa_mapped, ns.gyr_aa_mapped_std = None, None @@ -40,23 +40,26 @@ def run(ns): # TODO: factorize all checks and put them in global lib if not os.path.isfile(ns.aa_tpr_filename): msg = ( - "Cannot find coordinate file of the atomistic simulation" - "(GRO, PDB, or other trajectory formats supported by MDAnalysis)" + f"Cannot find topology file of the atomistic simulation at location: {ns.aa_tpr_filename}\n" + f"(TPR or other portable topology formats supported by MDAnalysis)" ) raise exceptions.MissingCoordinateFile(msg) if not os.path.isfile(ns.aa_traj_filename): msg = ( - "Cannot find trajectory file of the atomistic simulation" - "(XTC, TRR, or other trajectory formats supported by MDAnalysis)" + f"Cannot find trajectory file of the atomistic simulation at location: {ns.aa_traj_filename}\n" + f"(XTC, TRR, or other trajectory formats supported by MDAnalysis)" ) raise exceptions.MissingTrajectoryFile(msg) if not os.path.isfile(ns.cg_map_filename): - msg = "Cannot find CG beads mapping file (NDX-like file format)" + msg = ( + f"Cannot find CG beads mapping file at location: {ns.cg_map_filename}\n" + f"(NDX-like file format)" + ) raise exceptions.MissingIndexFile(msg) if not os.path.isfile(ns.cg_itp_filename): - msg = "Cannot find ITP file of the CG model" + msg = f"Cannot find ITP file of the CG model at location: {ns.cg_itp_filename}" raise exceptions.MissingItpFile(msg) # check bonds scaling arguments conflicts @@ -132,10 +135,9 @@ def main(): help='XTC file of your CG trajectory (omit for solo AA inspection)', type=str, default=config.metavar_cg_traj, metavar=' ' + scg.par_wrap(config.metavar_cg_traj)) - required_args.add_argument('-cg_top', dest='top_input_filename', - help='TOP file used for iterative simulation', type=str, - default='system.top', metavar=' (system.top)') - # required_args.add_argument('-figmolname', dest='figmolname', help='TODO REMOVE', type=str, required=True) # TODO: remove, this was just for figures + # required_args.add_argument('-cg_top', dest='top_input_filename', + # help='TOP file used for iterative simulation', type=str, + # default='system.top', metavar=' (system.top)') optional_args = args_parser.add_argument_group(bullet + 'CG MODEL SCALING') # optional_args.add_argument('-nb_threads', dest='nb_threads', help='number of threads to use', type=int, default=1, metavar='1') # TODO: does NOT work properly -- modif MDAnalysis code with OpenMP num_threads(n) in the pragma @@ -204,6 +206,8 @@ def main(): # arguments handling, display command line if help or no arguments provided ns = args_parser.parse_args() + # ns.in_dir = "." + # TODO UNSURE: currently it is not allowed to feed arg -in_dir in evaluate_model, like it is the case in optimize_model, but for path handling we still need to define ns.in_dir = "." input_cmdline = ' '.join(map(cmd_quote, sys.argv)) print('Working directory:', os.getcwd()) print('Command line:', input_cmdline) diff --git a/swarmcg/optimize_model.py b/swarmcg/optimize_model.py index 81c7223..88d6f7f 100644 --- a/swarmcg/optimize_model.py +++ b/swarmcg/optimize_model.py @@ -189,13 +189,10 @@ def run(ns): print() #Loading the mass of the atom-tpyes in case they are needed - scg.fetch_cg_mass_itp(ns) + # scg.fetch_cg_mass_itp(ns) # read starting CG ITP file - with open(ns.cg_itp_filename, 'r') as fp: - itp_lines = fp.read().split('\n') - itp_lines = [itp_line.strip() for itp_line in itp_lines] - scg.read_cg_itp_file(ns, itp_lines) # loads ITP object that contains our reference atomistic data -- won't ever be modified during execution + scg.read_cg_itp_file(ns) # loads ITP object that contains our reference atomistic data -- won't ever be modified during execution # touch results files to be appended to later with open(ns.exec_folder+'/'+config.opti_perf_recap_file, 'w') as fp: diff --git a/swarmcg/shared/exceptions.py b/swarmcg/shared/exceptions.py index b5ab8d8..dfcd721 100644 --- a/swarmcg/shared/exceptions.py +++ b/swarmcg/shared/exceptions.py @@ -1,7 +1,10 @@ +from .styling import sep + header_error = "\n-- ! ERROR ! --\n" header_warning = "\n-- ! WARNING ! --\n" -header_gmx_error = "\n GMX ERROR MSG\n'+sep+'\n\n" +header_gmx_error = "\n GMX ERROR MSG\n" + sep + "\n\n" +# TODO: disable showing exceptions traceback for distributing to users ? maybe there is a way we can keep it active for our dev purpose though ? class BaseError(Exception): """ @@ -47,7 +50,7 @@ class OptimisationResultsError(BaseError): pass -class MissingInputFileError(BaseError): +class MissingCoordinateFile(BaseError): pass diff --git a/swarmcg/shared/styling.py b/swarmcg/shared/styling.py index 3dd2f09..87fe62a 100644 --- a/swarmcg/shared/styling.py +++ b/swarmcg/shared/styling.py @@ -23,12 +23,12 @@ def header_package(module_line): | Swarm-CG is distributed under the terms of the MIT License. | | | | Feedback, questions and bug reports are welcome at: | -| {config.github_url}/issues | +| {config.github_url}/issues | | | | If you found Swarm-CG useful in your research, please cite: | | Swarm-CG: Automatic parametrization of bonded terms in CG models | | of simple to complex molecules via FST-PSO | -| Empereur-mot C., Pesce L., Bochicchio D., Perego C., Pavan G.M. ChemRxiv 2020 | +| Empereur-mot C., Pesce L., Doni G., Bochicchio D., Perego C., Pavan G.M. ChemRxiv 2020 | | | | Swarm-CG relies on FST-PSO: | | Fuzzy Self-Tuning PSO: A settings-free algorithm for global optimization | diff --git a/swarmcg/shared/vs_functions.py b/swarmcg/simulations/vs_functions.py similarity index 100% rename from swarmcg/shared/vs_functions.py rename to swarmcg/simulations/vs_functions.py diff --git a/swarmcg/swarmCG.py b/swarmcg/swarmCG.py index 0853d21..cbcb92c 100644 --- a/swarmcg/swarmCG.py +++ b/swarmcg/swarmCG.py @@ -210,14 +210,22 @@ def verify_handled_functions(geom, func_obj, line_obj): # read coarse-grain ITP -def read_cg_itp_file(ns, itp_lines): +def read_cg_itp_file(ns): print('Reading Coarse-Grained (CG) ITP file') ns.cg_itp = {'moleculetype': {'molname': '', 'nrexcl': 0}, 'atoms': [], 'constraint': [], 'bond': [], 'angle': [], 'dihedral': [], 'exclusion': [], 'virtual_sitesn': {}} - ns.real_beads_ids = [] - ns.vs_beads_ids = [] + # ns.real_beads_ids, ns.vs_beads_ids = [], [] ns.nb_constraints, ns.nb_bonds, ns.nb_angles, ns.nb_dihedrals = -1, -1, -1, -1 + with open(ns.cg_itp_filename, 'r') as fp: + try: + itp_lines = fp.read().split('\n') + itp_lines = [itp_line.strip() for itp_line in itp_lines] + process_scaling_str(ns) + except UnicodeDecodeError: + msg = "Cannot read CG ITP, it seems you provided a binary file." + raise exceptions.MissformattedFile(msg) + for i in range(len(itp_lines)): itp_line = itp_lines[i] if itp_line != '' and not itp_line.startswith(';'): @@ -242,28 +250,28 @@ def read_cg_itp_file(ns, itp_lines): r_moleculetype, r_atoms, r_constraints, r_bonds, r_angles, r_dihedrals, r_exclusion, r_virtual = False, False, False, False, False, False, False, False else: - #Stripping comments from the input line - aux_itp_line = strip_comment(itp_line,";") - sp_itp_line = aux_itp_line.split() + sp_itp_line = itp_line.split() if r_moleculetype: ns.cg_itp['moleculetype']['molname'], ns.cg_itp['moleculetype']['nrexcl'] = sp_itp_line[0], int(sp_itp_line[1]) elif r_atoms: - if len(sp_itp_line) == 7: + + if len(sp_itp_line) == 7: # in case masses are ABSENT bead_id, bead_type, resnr, residue, atom, cgnr, charge = sp_itp_line[:7] + + # TODO: get masses from TPR + mass = 0 + # As the mass is not defined we look into its definition - try: - mass = ns.cg_atomtypes_mass[bead_type] - except: - msg = ( - "The bead_type {}, is not contained into the definition of the " - "force field file" - ).format(bead_type) - raise exceptions.MissformattedFile(msg) + # try: + # mass = ns.cg_atomtypes_mass[bead_type] + # except: + # msg = f"The bead type {bead_type} is not defined in the force field file(s)" + # raise exceptions.MissformattedFile(msg) - elif len(sp_itp_line) == 8: + elif len(sp_itp_line) == 8: # in case masses are PRESENT bead_id, bead_type, resnr, residue, atom, cgnr, charge, mass = sp_itp_line[:8] else: # @@ -275,13 +283,13 @@ def read_cg_itp_file(ns, itp_lines): ) raise exceptions.MissformattedFile(msg) - #Making real beads and vs list of ids - if bead_type == 'VS': - ns.vs_beads_ids.append(int(bead_id) - 1) - else: - ns.real_beads_ids.append(int(bead_id) - 1) + # making real beads and vs list of ids + # if bead_type == 'VS': + # ns.vs_beads_ids.append(int(bead_id) - 1) + # else: + # ns.real_beads_ids.append(int(bead_id) - 1) - #Assignment of the variables value + # assignment of the variables value ns.cg_itp['atoms'].append({'bead_id': int(bead_id) - 1, 'bead_type': bead_type, 'resnr': int(resnr), 'residue': residue,'atom': atom, 'cgnr': int(cgnr), 'charge': float(charge), 'mass': float(mass)}) if not len(ns.cg_itp['atoms']) == int(bead_id): @@ -419,46 +427,34 @@ def read_cg_itp_file(ns, itp_lines): ns.cg_itp['dihedral'][ns.nb_dihedrals]['plt_id'].append('') elif r_virtual: - # For user information we need to provide the number of VS. - # We need to define the function types for the VSn + # TODO: For user information we need to provide the number of VS. + # TODO: We need to define the function types for the VSn - #Read VS index, and VS function, list_cg_atoms + # Read VS index, and VS function, list_cg_atoms bead_id, vs_type, cg_atomlist = int(sp_itp_line[0])-1, int(sp_itp_line[1]), [int(bid)-1 for bid in sp_itp_line[2:]] - - #Check if the bead is defined in the atom list - if bead_id >= len(ns.cg_itp['atoms']): - msg = ( - "The bead index definition of the CG virtual sites {} in not defined" - " within in the atomlist".format(bead_id) - ) - raise exceptions.MissformattedFile(msg) - else: - #Check if the bead is defined as VS - if ns.cg_itp['atoms'][bead_id]['bead_type'] != 'VS': + # Check if the bead is defined in the atom list + for bid in cg_atomlist + [bead_id]: + if bid >= len(ns.cg_itp['atoms']): msg = ( - "The virtual site {} should be defined with bead type" - " VS".format(bead_id+1) + f"The virtual sites definition(s) make use of index {bid}, which exceeds the number of " + f"beads and virtual sites defined" ) raise exceptions.MissformattedFile(msg) - #Function is in the function list - func = verify_handled_functions('virtual_sitesn', vs_type, i) - - - #The cg_atoms in list_cg_atoms, checking that the indexes are lower than the one of the VS - for bid in cg_atomlist: - if bid >= bead_id: + else: + # check if the bead is defined as VS (= must start with letter small "v" by MARTINI convention) + if not ns.cg_itp['atoms'][bead_id]['bead_type'].startswith('v'): msg = ( - "The definition of the CG virtual sites {} includes atoms that " - "either they are not in the list or their index comes after the " - "index is higher than the one of the virtual site.".format(bead_id) + f'CG bead number {bead_id+1} is referenced to as a virtual site, but its bead type ' + f'does NOT start with letter "v"' ) raise exceptions.MissformattedFile(msg) + func = verify_handled_functions('virtual_sitesn', vs_type, i) + # ns.cg_itp['virtual_sitesn'].append({'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist}) ns.cg_itp['virtual_sitesn'][bead_id] = {'bead_id': bead_id, 'vs_type': vs_type, 'atom_list': cg_atomlist} - elif r_exclusion: ns.cg_itp['exclusion'].append([int(bead_id)-1 for bead_id in sp_itp_line]) @@ -519,6 +515,7 @@ def read_cg_itp_file(ns, itp_lines): return + def pop_empty_lines(file): # Popping out all the empty lines list_idx = [value for value in range(len(file)) if file[value] == ''] @@ -528,73 +525,73 @@ def pop_empty_lines(file): return -#This function reads the defaults masses associated to each atomtype loaded into the topology file -def fetch_cg_mass_itp(ns): - #Declaring the ns.cg_atomtypes = {} in order to retreive the mass of each particle whenever is missing by searching the type as arguments - ns.cg_atomtypes_mass = {} - #Parsing the topology file to find all the .itp included - list_itp = [] - - # Checking if the namespaces contains the folder specs. - # This is done to distinguish between optimize and evaluate models - print(os.getcwd()) - if hasattr(ns,'exec_folder') or hasattr(config,'input_sim_files_dirname'): - print(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename) - with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename, 'r') as fp: - all_top_lines = fp.read().split('\n') - else: - with open(ns.top_input_basename, 'r') as fp: - all_top_lines = fp.read().split('\n') - - pop_empty_lines(all_top_lines) - - for line in all_top_lines: - if line.split()[0] == "#include": - #Reading the filename of the loaded .itps - aux = line.split()[1] - list_itp.append(aux[1:len(aux)-1]) - - #Reading all the atomtypes within each .itp found in the topology file - for itp_name in list_itp: - if hasattr(ns, 'exec_folder') and hasattr(config, 'input_sim_files_dirname'): - with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + itp_name, 'r') as fp: - itp_file = fp.read().split('\n') - else: - with open(itp_name, 'r') as fp: - itp_file = fp.read().split('\n') - - - #Stripping all comments from the list of line - for i in range(len(itp_file)): - itp_file[i] = strip_comment(itp_file[i],";") - - #Popping out all the empty lines - list_idx = [value for value in range(len(itp_file)) if itp_file[value] == ''] - list_idx.reverse() - for idx in list_idx: - itp_file.pop(idx) - - # Here a boolean checking if we are in a atomtypes section - bAtomTypes = False - - #The lines of the file should be now cleaned, therefore it is possible to skip all the checks to monitor empty lines - for line in itp_file: - if len(line.split()) != 0: - words = line.split() - #Searching the atomtype keyword - if words[0] == "[": - if words[1] == "atomtypes": - bAtomTypes = True - elif words[1] != "atomtypes": - bAtomTypes = False - continue - if bAtomTypes: - ns.cg_atomtypes_mass[words[0]] = float(words[1]) - else: - break - - - return +# #This function reads the defaults masses associated to each atomtype loaded into the topology file +# def fetch_cg_mass_itp(ns): +# #Declaring the ns.cg_atomtypes = {} in order to retreive the mass of each particle whenever is missing by searching the type as arguments +# ns.cg_atomtypes_mass = {} +# #Parsing the topology file to find all the .itp included +# list_itp = [] +# +# # Checking if the namespaces contains the folder specs. +# # This is done to distinguish between optimize and evaluate models +# print(os.getcwd()) +# if hasattr(ns,'exec_folder') or hasattr(config,'input_sim_files_dirname'): +# print(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename) +# with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + ns.top_input_basename, 'r') as fp: +# all_top_lines = fp.read().split('\n') +# else: +# with open(ns.top_input_basename, 'r') as fp: +# all_top_lines = fp.read().split('\n') +# +# pop_empty_lines(all_top_lines) +# +# for line in all_top_lines: +# if line.split()[0] == "#include": +# #Reading the filename of the loaded .itps +# aux = line.split()[1] +# list_itp.append(aux[1:len(aux)-1]) +# +# #Reading all the atomtypes within each .itp found in the topology file +# for itp_name in list_itp: +# if hasattr(ns, 'exec_folder') and hasattr(config, 'input_sim_files_dirname'): +# with open(ns.exec_folder + '/' + config.input_sim_files_dirname + '/' + itp_name, 'r') as fp: +# itp_file = fp.read().split('\n') +# else: +# with open(itp_name, 'r') as fp: +# itp_file = fp.read().split('\n') +# +# +# #Stripping all comments from the list of line +# for i in range(len(itp_file)): +# itp_file[i] = strip_comment(itp_file[i],";") +# +# #Popping out all the empty lines +# list_idx = [value for value in range(len(itp_file)) if itp_file[value] == ''] +# list_idx.reverse() +# for idx in list_idx: +# itp_file.pop(idx) +# +# # Here a boolean checking if we are in a atomtypes section +# bAtomTypes = False +# +# #The lines of the file should be now cleaned, therefore it is possible to skip all the checks to monitor empty lines +# for line in itp_file: +# if len(line.split()) != 0: +# words = line.split() +# #Searching the atomtype keyword +# if words[0] == "[": +# if words[1] == "atomtypes": +# bAtomTypes = True +# elif words[1] != "atomtypes": +# bAtomTypes = False +# continue +# if bAtomTypes: +# ns.cg_atomtypes_mass[words[0]] = float(words[1]) +# else: +# break +# +# +# return # load CG beads from NDX-like file def read_ndx_atoms2beads(ns): @@ -717,8 +714,7 @@ def compute_Rg(ns, traj_type): total_mass = sum([ns.cg_universe.atoms[bead_id].mass for bead_id in range(len(ns.cg_itp['atoms']))]) beads_masses = np.array([np.array([ns.cg_universe.atoms[bead_id].mass]) for bead_id in range(len(ns.cg_itp['atoms']))]) # print('BEADS MASSES CG for Rg calculation AA-mapped:\n', beads_masses) - for ts in ns.aa2cg_trajectory.trajectory: - # mapped_pos = np.array([ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None, compound='group') for bead_id in range(len(ns.cg_itp['atoms']))]) + for ts in ns.aa2cg_universe.trajectory: com = np.sum(beads_masses * ts.positions, axis=0) / total_mass mapped_pos_dist_com = mda.lib.distances.distance_array(com, ts.positions, backend=ns.mda_backend) gyr_aa_mapped[ts.frame] = np.sqrt(np.sum(beads_masses.reshape(1,len(beads_masses)) * np.power(mapped_pos_dist_com, 2)) / total_mass) @@ -976,15 +972,13 @@ def print_cg_itp_file(itp_obj, out_path_itp, print_sections=['constraint', 'bond fp.write('; id type resnr residue atom cgnr charge mass\n\n') for i in range(len(itp_obj['atoms'])): - + + # TODO: remove mass and EOL, it's not used if 'mass_and_eol' in itp_obj['atoms'][i]: fp.write('{0:<4} {1:>4} {6:>2} {2:>6} {3:>6} {4:<4} {5:9.5f} {7}\n'.format(itp_obj['atoms'][i]['bead_id']+1, itp_obj['atoms'][i]['bead_type'], itp_obj['atoms'][i]['residue'], itp_obj['atoms'][i]['atom'], i+1, itp_obj['atoms'][i]['charge'], itp_obj['atoms'][i]['resnr'], itp_obj['atoms'][i]['mass_and_eol'])) else: fp.write('{0:<4} {1:>4} {6:>2} {2:>6} {3:>6} {4:<4} {5:9.5f}\n'.format(itp_obj['atoms'][i]['bead_id']+1, itp_obj['atoms'][i]['bead_type'], itp_obj['atoms'][i]['residue'], itp_obj['atoms'][i]['atom'], i+1, itp_obj['atoms'][i]['charge'], itp_obj['atoms'][i]['resnr'])) - # fp.write('\n\n[ ]\n') - # fp.write('; id type resnr residue atom cgnr charge mass\n\n') - if len(itp_obj['virtual_sitesn']) > 0: fp.write('\n\n[ virtual_sitesn ]\n') for vsite in itp_obj['virtual_sitesn']: @@ -997,7 +991,7 @@ def print_cg_itp_file(itp_obj, out_path_itp, print_sections=['constraint', 'bond for j in range(len(itp_obj['constraint'])): constraint_type = itp_obj['constraint'][j]['geom_type'] - fp.write('\n; constraint type '+constraint_type+'\n') # do NOT change this comment format, functions read_cg_itp depends on it + fp.write('\n; constraint type '+constraint_type+'\n') grp_val = itp_obj['constraint'][j]['value'] for i in range(len(itp_obj['constraint'][j]['beads'])): @@ -1010,7 +1004,7 @@ def print_cg_itp_file(itp_obj, out_path_itp, print_sections=['constraint', 'bond for j in range(len(itp_obj['bond'])): bond_type = itp_obj['bond'][j]['geom_type'] - fp.write('\n; bond type '+bond_type+'\n') # do NOT change this comment format, functions read_cg_itp depends on it + fp.write('\n; bond type '+bond_type+'\n') grp_val, grp_fct = itp_obj['bond'][j]['value'], itp_obj['bond'][j]['fct'] for i in range(len(itp_obj['bond'][j]['beads'])): @@ -1023,7 +1017,7 @@ def print_cg_itp_file(itp_obj, out_path_itp, print_sections=['constraint', 'bond for j in range(len(itp_obj['angle'])): angle_type = itp_obj['angle'][j]['geom_type'] - fp.write('\n; angle type '+angle_type+'\n') # do NOT change this comment format, functions read_cg_itp depends on it + fp.write('\n; angle type '+angle_type+'\n') grp_val, grp_fct = itp_obj['angle'][j]['value'], itp_obj['angle'][j]['fct'] for i in range(len(itp_obj['angle'][j]['beads'])): @@ -1036,7 +1030,7 @@ def print_cg_itp_file(itp_obj, out_path_itp, print_sections=['constraint', 'bond for j in range(len(itp_obj['dihedral'])): dihedral_type = itp_obj['dihedral'][j]['geom_type'] - fp.write('\n; dihedral type '+dihedral_type+'\n') # do NOT change this comment format, functions read_cg_itp depends on it + fp.write('\n; dihedral type '+dihedral_type+'\n') grp_val, grp_fct = itp_obj['dihedral'][j]['value'], itp_obj['dihedral'][j]['fct'] for i in range(len(itp_obj['dihedral'][j]['beads'])): @@ -1397,37 +1391,23 @@ def read_aa_traj(ns): def initialize_cg_traj(ns): - print('Building Coarse-Grained (CG) trajectory', flush=True) - # with warnings.catch_warnings(): - # warnings.filterwarnings("ignore", - # category=ImportWarning) # ignore warning: "bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__" - # ns.cg_universe2 = mda.Universe(ns.gro_input_basename, ns.gro_input_basename, in_memory=True, refresh_offsets=True, - # guess_bonds=False) # setting guess_bonds=False disables angles, dihedrals and improper_dihedrals guessing, which is activated by default - # Here we need to extract the number of atoms, or a more refined method to extract only the elements on which we are interested - # We need to assume that the molecule we will study is located at the beginning of the file. This assumptions does not change much, as the atom names and weights can be taken from the itp file - # sel = ns.cg_universe2.atoms[:len(ns.cg_itp['atoms'])] - # I generate a numpy array of the size np.zeros(len(ns.aa_universe.trajectory,len(ns.cg_itp['atoms']))) - # coord = np.zeros((len(ns.aa_universe.trajectory),len(ns.cg_itp['atoms']),3)) - # ns.aa2cg_trajectory = mda.Merge(sel) - # ns.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + masses = np.array([val['mass'] for val in ns.cg_itp['atoms']]) names = np.array([val['atom'] for val in ns.cg_itp['atoms']]) resname = np.array([val['residue'] for val in ns.cg_itp['atoms']]) resid = np.array([val['resnr'] for val in ns.cg_itp['atoms']]) nr = len(list(set([val['resnr'] for val in ns.cg_itp['atoms']]))) - print(list(set([val['resnr'] for val in ns.cg_itp['atoms']]))) - print(nr) - ns.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']),n_residues=nr,atom_resindex=resid,n_segments=1,residue_segindex=np.ones(nr), trajectory=True) - # ns.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']), 1,n_residues=nr,atom_resindex=resid,n_segments=1,residue_segindex=np.ones(nr), trajectory=True) - # ns.aa2cg_trajectory = mda.Universe.empty(len(ns.cg_itp['atoms']), nr, resindex=resid, trajectory=True) - ns.aa2cg_trajectory.add_TopologyAttr('masses') - ns.aa2cg_trajectory._topology.masses.values = np.array(masses) - ns.aa2cg_trajectory.add_TopologyAttr('name') - ns.aa2cg_trajectory._topology.names.values = names - ns.aa2cg_trajectory.add_TopologyAttr('resnames') - ns.aa2cg_trajectory._topology.resnames.values = resname - -#Assigning to the new universe the masses related to the CG + # print(list(set([val['resnr'] for val in ns.cg_itp['atoms']]))) + # print(nr) + ns.aa2cg_universe = mda.Universe.empty(len(ns.cg_itp['atoms']), n_residues=nr, atom_resindex=resid, n_segments=1, residue_segindex=np.ones(nr), trajectory=True) + # ns.aa2cg_universe = mda.Universe.empty(len(ns.cg_itp['atoms']), 1,n_residues=nr,atom_resindex=resid,n_segments=1,residue_segindex=np.ones(nr), trajectory=True) + # ns.aa2cg_universe = mda.Universe.empty(len(ns.cg_itp['atoms']), nr, resindex=resid, trajectory=True) + ns.aa2cg_universe.add_TopologyAttr('masses') + ns.aa2cg_universe._topology.masses.values = np.array(masses) + ns.aa2cg_universe.add_TopologyAttr('name') + ns.aa2cg_universe._topology.names.values = names + ns.aa2cg_universe.add_TopologyAttr('resnames') + ns.aa2cg_universe._topology.resnames.values = resname # if len(ns.aa_universe.trajectory) > 20000: # print(config.header_warning+'Your atomistic trajectory contains many frames, which increases computation time\nReasonably reducing the number of frames of your input AA trajectory won\'t affect results quality\n2k to 10k frames is usually enough, as long as behaviour and flexibility of your molecule are correctly described by your atomistic trajectory') @@ -1443,55 +1423,53 @@ def strip_comment(line,val): def map_aa2cg_traj(ns): - # for i in range(len(ns.aa_universe.trajectory)): - # I will estimate the coordinates of each bead within all the frames using the iterator of mda and the function center_of_mass() + + # regular beads are mapped using center of mass of groups of atoms coord = np.zeros((len(ns.aa_universe.trajectory), len(ns.cg_itp['atoms']), 3)) for bead_id in range(len(ns.cg_itp['atoms'])): - #Check if the atomtype of the cg is related to a VS - if ns.cg_itp['atoms'][bead_id]['bead_type'] != 'VS': - #The bead is not a VS therefore must be evaluated starting from the AA - traj = np.empty((len(ns.aa_universe.trajectory),3)) + if not ns.cg_itp['atoms'][bead_id]['bead_type'].startswith('v'): # bead is NOT a virtual site + traj = np.empty((len(ns.aa_universe.trajectory), 3)) for ts in ns.aa_universe.trajectory: - # print(ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None, - # compound='group')) - traj[ts.frame] = ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None,compound='group') # no need for PBC handling, trajectories were made wholes for the molecule - coord[:,bead_id,:] = traj + traj[ts.frame] = ns.mda_beads_atom_grps[bead_id].center(ns.mda_weights_atom_grps[bead_id], pbc=None, compound='group') # no need for PBC handling, trajectories were made wholes for the molecule + coord[:, bead_id, :] = traj + ns.aa2cg_universe.load_new(coord, format=mda.coordinates.memory.MemoryReader) - ns.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) - - for j in range(len(ns.cg_itp['atoms'])): - if ns.cg_itp['atoms'][j]['bead_type'] == 'VS': - #The bead is a VS, therefore must be evaluated from the coordinates of the previous atoms - la = ns.cg_itp['virtual_sitesn'][j]['atom_list'] + # virtual sites are mapped using previously defined regular beads positions and appropriate virtual sites functions + for bead_id in range(len(ns.cg_itp['atoms'])): + if ns.cg_itp['atoms'][bead_id]['bead_type'].startswith('v'): + la = ns.cg_itp['virtual_sitesn'][bead_id]['atom_list'] # VS_TYPE = 1 -> Center of Geometry # VS_TYPE = 2 -> Center of Mass # VS_TYPE = 3 -> Center of Weights (for each atom a weight must be given in the definition of the VS) - traj = np.empty((len(ns.aa_universe.trajectory),3)) - sel = ns.aa2cg_trajectory.atoms[la] - if ns.cg_itp['virtual_sitesn'][j]['vs_type'] == 1: - for ts in ns.aa2cg_trajectory.trajectory: + traj = np.empty((len(ns.aa2cg_universe.trajectory), 3)) + sel = ns.aa2cg_universe.atoms[la] + + if ns.cg_itp['virtual_sitesn'][bead_id]['vs_type'] == 1: + for ts in ns.aa2cg_universe.trajectory: traj[ts.frame] = sel.center_of_geometry(pbc=None) - elif ns.cg_itp['virtual_sitesn'][j]['vs_type'] == 2: - for ts in ns.aa2cg_trajectory.trajectory: + + # TODO: Here there wil be a RunTimeWarning: Divide by 0 if function 2 is used exclusively with VS because there will be no masses + # TODO: actually for function 2 we should verify AND ENFORCE that all beads should have masses != 0 + elif ns.cg_itp['virtual_sitesn'][bead_id]['vs_type'] == 2: + for ts in ns.aa2cg_universe.trajectory: traj[ts.frame] = sel.center_of_mass(pbc=None) - coord[:, j, :] = traj - #Final CG-coordinates - ns.aa2cg_trajectory.load_new(coord, format=mda.coordinates.memory.MemoryReader) + coord[:, bead_id, :] = traj + + # Final CG-coordinates + ns.aa2cg_universe.load_new(coord, format=mda.coordinates.memory.MemoryReader) return + # use selected whole molecules as MDA atomgroups and make their coordinates whole, inplace, across the complete tAA rajectory def make_aa_traj_whole_for_selected_mols(ns): # TODO: add an option to NOT read the PBC in case user would feed a trajectory that is already OK and their trajectory does NOT contain PBC/BOX size info across trajectory (this was an issue I encountered with Davide B3T traj GRO) - # try: for _ in ns.aa_universe.trajectory: for aa_mol in ns.all_aa_mols: mda.lib.mdamath.make_whole(aa_mol, inplace=True) - # except ValueError as e: - # print(e) return @@ -1538,14 +1516,11 @@ def create_bins_and_dist_matrices(ns, constraints=True): # calculate bonds distribution from AA trajectory def get_AA_bonds_distrib(ns, beads_ids, grp_type, grp_nb): - bond_values = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) + bond_values = np.empty(len(ns.aa2cg_universe.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2 = beads_ids[i] - # print('bead_id_1:', bead_id_1, 'using atoms:', ns.mda_beads_atom_grps[bead_id_1].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_1]) - # print('bead_id_2:', bead_id_2, 'using atoms:', ns.mda_beads_atom_grps[bead_id_2].atoms, 'with weights:', ns.mda_weights_atom_grps[bead_id_2]) - # print(beads_ids[i]) - for ts in ns.aa2cg_trajectory.trajectory: - bond_values[len(ns.aa2cg_trajectory.trajectory)*i+ts.frame] = mda.lib.distances.calc_bonds(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm + for ts in ns.aa2cg_universe.trajectory: + bond_values[len(ns.aa2cg_universe.trajectory)*i+ts.frame] = mda.lib.distances.calc_bonds(ns.aa2cg_universe.atoms[bead_id_1].position, ns.aa2cg_universe.atoms[bead_id_2].position, backend=ns.mda_backend, box=None) / 10 # retrieved nm bond_avg_init = round(np.average(bond_values), 3) @@ -1602,11 +1577,11 @@ def get_AA_bonds_distrib(ns, beads_ids, grp_type, grp_nb): # calculate angles distribution from AA trajectory def get_AA_angles_distrib(ns, beads_ids): - angle_values_rad = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) + angle_values_rad = np.empty(len(ns.aa2cg_universe.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3 = beads_ids[i] - for ts in ns.aa2cg_trajectory.trajectory: - angle_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+ts.frame] = mda.lib.distances.calc_angles(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, backend=ns.mda_backend, box=None) + for ts in ns.aa2cg_universe.trajectory: + angle_values_rad[len(ns.aa2cg_universe.trajectory)*i+ts.frame] = mda.lib.distances.calc_angles(ns.aa2cg_universe.atoms[bead_id_1].position, ns.aa2cg_universe.atoms[bead_id_2].position, ns.aa2cg_universe.atoms[bead_id_3].position, backend=ns.mda_backend, box=None) angle_values_deg = np.rad2deg(angle_values_rad) angle_avg = round(np.mean(angle_values_deg), 3) @@ -1618,11 +1593,11 @@ def get_AA_angles_distrib(ns, beads_ids): # calculate dihedrals distribution from AA trajectory def get_AA_dihedrals_distrib(ns, beads_ids): - dihedral_values_rad = np.empty(len(ns.aa2cg_trajectory.trajectory) * len(beads_ids)) + dihedral_values_rad = np.empty(len(ns.aa2cg_universe.trajectory) * len(beads_ids)) for i in range(len(beads_ids)): bead_id_1, bead_id_2, bead_id_3, bead_id_4 = beads_ids[i] - for ts in ns.aa2cg_trajectory.trajectory: - dihedral_values_rad[len(ns.aa2cg_trajectory.trajectory)*i+ts.frame] = mda.lib.distances.calc_dihedrals(ns.aa2cg_trajectory.atoms[bead_id_1].position, ns.aa2cg_trajectory.atoms[bead_id_2].position, ns.aa2cg_trajectory.atoms[bead_id_3].position, ns.aa2cg_trajectory.atoms[bead_id_4].position, backend=ns.mda_backend, box=None) + for ts in ns.aa2cg_universe.trajectory: + dihedral_values_rad[len(ns.aa2cg_universe.trajectory)*i+ts.frame] = mda.lib.distances.calc_dihedrals(ns.aa2cg_universe.atoms[bead_id_1].position, ns.aa2cg_universe.atoms[bead_id_2].position, ns.aa2cg_universe.atoms[bead_id_3].position, ns.aa2cg_universe.atoms[bead_id_4].position, backend=ns.mda_backend, box=None) dihedral_values_deg = np.rad2deg(dihedral_values_rad) dihedral_avg = round(np.mean(dihedral_values_deg), 3) @@ -1939,18 +1914,11 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False # read ITP file to extract bonds, angles and dihedrals to compare OR get it from the optimization script to avoid re-reading trajectory + calculating hists at each execution # for reading ITP, groups are created by separating bonds/angles/etc lines by a return (\n) or a comment (;) if manual_mode: - with open(ns.cg_itp_filename, 'r') as fp: - try: - itp_lines = fp.read().split('\n') - itp_lines = [itp_line.strip() for itp_line in itp_lines] - read_cg_itp_file(ns, itp_lines) - process_scaling_str(ns) - except UnicodeDecodeError: - msg = "Cannot read CG ITP, it seems you provided a binary file." - raise exceptions.MissformattedFile(msg) + + read_cg_itp_file(ns) # Loading the mass of the atom-tpyes in case they are needed - fetch_cg_mass_itp(ns) + # fetch_cg_mass_itp(ns) # read AA traj + find atom bonds connectivity and atom types (to differentiate heavy/hydrogens) print() @@ -1964,9 +1932,9 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False get_beads_MDA_atomgroups(ns) # mapping the trajectory aa2cg - print('Initializing the mapped trajectory') - initialize_cg_traj(ns) + print() print('Mapping the trajectory from AA to CG representation') + initialize_cg_traj(ns) map_aa2cg_traj(ns) if ns.atom_only: @@ -1983,7 +1951,7 @@ def compare_models(ns, manual_mode=True, ignore_dihedrals=False, calc_sasa=False # select the whole molecule as an MDA atomgroup and make its coordinates whole, inplace, across the complete trajectory cg_mol = mda.AtomGroup([bead_id for bead_id in ns.all_beads], ns.cg_universe) - for _ in ns.cg_universe.trajectory: # did not help + for _ in ns.cg_universe.trajectory: mda.lib.mdamath.make_whole(cg_mol, inplace=True) # this requires CG data for mapping -- especially, masses are taken from the CG TPR but the CG ITP is also used atm diff --git a/tests/data/cg_model.itp b/tests/data/cg_model.itp new file mode 100644 index 0000000..0db7a69 --- /dev/null +++ b/tests/data/cg_model.itp @@ -0,0 +1,139 @@ +; This file can replace the one in directory /G1_DATA for testing purposes +; and can be made more "complicated" notably for: +; +; -- Adding virtual sites and testing functions +; -- Verifying behavior with different residue names (might be an issue while mapping trajectory to CG) +; -- Checking if virtual sites can be defined in the middle of the [ atoms ] without crashing everything +; (NOT sure this is allowed by MARTINI convention though) +; -- Verify we allow to have 2x [ atoms ] sections for regular/vs beads (this is allowed in MARTINI format) + + +[ moleculetype ] +; molname nrexcl +G1 1 + + +[ atoms ] +; id type resnr residue atom cgnr charge + +1 N0 1 G1 A1 1 0.00000 +2 N0 1 G1 A2 2 0.00000 +3 Nda 1 G1 A3 3 0.00000 +4 N0 1 G1 A4 4 0.00000 +5 Nda 1 G1 A5 5 0.00000 +6 Qd 1 G1 A6 6 1.00000 +7 Nda 1 G1 A7 7 0.00000 +8 Qd 1 G1 A8 8 1.00000 +9 Nda 1 G1 A9 9 0.00000 +10 N0 1 G1 A10 10 0.00000 +11 Nda 1 G1 A11 11 0.00000 +12 Qd 1 G1 A12 12 1.00000 +13 Nda 1 G1 A13 13 0.00000 +14 Qd 1 G1 A14 14 1.00000 +15 Nda 1 G1 A15 15 0.00000 +16 N0 1 G1 A16 16 0.00000 +17 Nda 1 G1 A17 17 0.00000 +18 Qd 1 G1 A18 18 1.00000 +19 Nda 1 G1 A19 19 0.00000 +20 Qd 1 G1 A20 20 1.00000 +21 Nda 1 G1 A21 21 0.00000 +22 N0 1 G1 A22 22 0.00000 +23 Nda 1 G1 A23 23 0.00000 +24 Qd 1 G1 A24 24 1.00000 +25 Nda 1 G1 A25 25 0.00000 +26 Qd 1 G1 A26 26 1.00000 +27 vT 1 G1 A27 27 0.00000 +28 vT 1 G1 A28 28 0.00000 +29 vT 1 G1 A29 29 0.00000 +30 vT 1 G1 A30 30 0.00000 + + +[ bonds ] +; i j funct length force.c. + +; bond group 1 + 1 2 1 0 0 ; B1 + +; bond group 2 + 1 3 1 0 0 ; B2 + 1 9 1 0 0 ; B2 + 2 15 1 0 0 ; B2 + 2 21 1 0 0 ; B2 + 4 5 1 0 0 ; B2 + 4 7 1 0 0 ; B2 + 10 11 1 0 0 ; B2 + 10 13 1 0 0 ; B2 + 16 17 1 0 0 ; B2 + 16 19 1 0 0 ; B2 + 22 23 1 0 0 ; B2 + 22 25 1 0 0 ; B2 + +; bond group 3 + 3 4 1 0 0 ; B3 + 9 10 1 0 0 ; B3 + 15 16 1 0 0 ; B3 + 21 22 1 0 0 ; B3 + +; bond group 4 + 5 6 1 0 0 ; B4 + 7 8 1 0 0 ; B4 + 11 12 1 0 0 ; B4 + 13 14 1 0 0 ; B4 + 17 18 1 0 0 ; B4 + 19 20 1 0 0 ; B4 + 23 24 1 0 0 ; B4 + 25 26 1 0 0 ; B4 + +; bond group 5 + 1 27 1 0 0 ; B5 + + +[ angles ] +; i j k funct angle force.c. + +; angle group 1 + 1 2 15 2 120 0 ; A1 + 1 2 21 2 120 0 ; A1 + 2 1 3 2 120 0 ; A1 + 2 1 9 2 120 0 ; A1 + +; angle group 2 + 1 3 4 2 180 0 ; A2 + 1 9 10 2 180 0 ; A2 + 2 15 16 2 180 0 ; A2 + 2 21 22 2 180 0 ; A2 + +; angle group 3 + 3 1 9 2 120 0 ; A3 + 15 2 21 2 120 0 ; A3 + 5 4 7 2 120 0 ; A3 + 11 10 13 2 120 0 ; A3 + 17 16 19 2 120 0 ; A3 + 25 22 23 2 120 0 ; A3 + +; angle group 4 + 3 4 5 2 120 0 ; A4 + 3 4 7 2 120 0 ; A4 + 9 10 11 2 120 0 ; A4 + 9 10 13 2 120 0 ; A4 + 15 16 17 2 120 0 ; A4 + 15 16 19 2 120 0 ; A4 + 21 22 23 2 120 0 ; A4 + 21 22 25 2 120 0 ; A4 + +; angle group 5 + 4 5 6 2 180 0 ; A5 + 4 7 8 2 180 0 ; A5 + 10 11 12 2 180 0 ; A5 + 10 13 14 2 180 0 ; A5 + 16 17 18 2 180 0 ; A5 + 16 19 20 2 180 0 ; A5 + 22 23 24 2 180 0 ; A5 + 22 25 26 2 180 0 ; A5 + +[ virtual_sitesn ] +27 1 5 6 7 8 +28 1 11 12 13 14 +29 1 17 18 19 20 +30 1 23 24 25 26 + From 23f133f0cbd2d4aa14725f8bca09f4a5f13c47df Mon Sep 17 00:00:00 2001 From: CharlyE Date: Sun, 27 Sep 2020 11:03:33 +0200 Subject: [PATCH 26/40] Added VS functions + Fixed BI --- .gitignore | 3 + G1_DATA/cg_topol.tpr | Bin 0 -> 38176 bytes G1_DATA/cg_traj.xtc | Bin 0 -> 9599344 bytes G1_DATA/martini_v2.0_PEO_PS_CNP.itp | 4 +- G1_DATA/system.top | 2 +- swarmcg/__init__.py | 2 +- swarmcg/config.py | 67 +- swarmcg/evaluate_model.py | 31 +- swarmcg/optimize_model.py | 137 +--- swarmcg/shared/styling.py | 4 +- swarmcg/shared/utils.py | 11 +- swarmcg/simulations/vs_functions.py | 153 +++- swarmcg/swarmCG.py | 1088 ++++++++++----------------- tests/data/cg_model.itp | 9 +- 14 files changed, 677 insertions(+), 834 deletions(-) create mode 100644 G1_DATA/cg_topol.tpr create mode 100644 G1_DATA/cg_traj.xtc diff --git a/.gitignore b/.gitignore index 66482ec..36915ff 100644 --- a/.gitignore +++ b/.gitignore @@ -99,3 +99,6 @@ ENV/ .pytest_cache/ # data +/distributions.png +/G1_DATA/.aa_traj.xtc_offsets.npz +/G1_DATA/.cg_traj.xtc_offsets.npz diff --git a/G1_DATA/cg_topol.tpr b/G1_DATA/cg_topol.tpr new file mode 100644 index 0000000000000000000000000000000000000000..0ce7463db15b85fe1484cc213e7a81909d230ac1 GIT binary patch literal 38176 zcmeFZXS5X6w*F1dIp>^nPP^Bt+T@&b1_8-P1_fc0bIv&@5fMQVx)z9{Ai;o&h>9qv zn8kqE_xBX^Is1Rcd(ORY828idF=}^pcXh3`W_ac^=Uly$BuSDvNs=U)IyY+Hp;?>O zMXFV)TBlMC-bs=q1;-;C`8d*Wq#iSH_`rT+2XdM+DSvdt9;gUi zSFd%AH(h`K`S{n@|NP|t_N+bcCg(`jwr2SG{qy_lxqn_g(fidBomUOdwdUll2lUg6 z@cPyR!uRi=hi^Z4zsf(~Z;)uL28qUMkZ7z1iN

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