Merge pull request #694 from rhayes777/feature/version

bump to __version__ = 2023.3.21.5

autofit/__init__.py

@@ -109,4 +109,4 @@ def save_abc(pickler, obj):
 
 conf.instance.register(__file__)
 
-__version__ = "2023.3.21.3"
+__version__ = "2023.3.27.1"

autofit/config/general.yaml

@@ -3,6 +3,9 @@ analysis:
 hpc:
   hpc_mode: false                   # If True, use HPC mode, which disables GUI visualization, logging to screen and other settings which are not suited to running on a super computer.
   iterations_per_update: 5000       # The number of iterations between every update (visualization, results output, etc) in HPC mode.
+inversion:
+  check_reconstruction: true        # If True, the inversion's reconstruction is checked to ensure the solution of a meshs's mapper is not an invalid solution where the values are all the same.
+  reconstruction_vmax_factor: 0.5   # Plots of an Inversion's reconstruction use the reconstructed data's bright value multiplied by this factor.  
 model:
   ignore_prior_limits: false        # If ``True`` the limits applied to priors will be ignored, where limits set upper / lower limits. This stops PriorLimitException's from being raised.
 output:

requirements.txt

@@ -10,6 +10,6 @@ pyprojroot==0.2.0
 pyswarms==1.3.0
 h5py>=2.10.0
 SQLAlchemy==1.3.20
-scipy>=1.5.1
+scipy>=1.5.4,<=1.8.1
 astunparse==1.6.3
 xxhash==3.0.0

test_autofit/config/general.yaml

@@ -3,6 +3,9 @@ analysis:
 hpc:
   hpc_mode: false                   # If True, use HPC mode, which disables GUI visualization, logging to screen and other settings which are not suited to running on a super computer.
   iterations_per_update: 5000       # The number of iterations between every update (visualization, results output, etc) in HPC mode.
+inversion:
+  check_reconstruction: true        # If True, the inversion's reconstruction is checked to ensure the solution of a meshs's mapper is not an invalid solution where the values are all the same.
+  reconstruction_vmax_factor: 0.5   # Plots of an Inversion's reconstruction use the reconstructed data's bright value multiplied by this factor.  
 model:
   ignore_prior_limits: false        # If ``True`` the limits applied to priors will be ignored, where limits set upper / lower limits. This stops PriorLimitException's from being raised.
 output:
@@ -21,6 +24,7 @@ profiling:
   should_profile: false             # If True, the ``profile_log_likelihood_function()`` function of an analysis class is called throughout a model-fit, profiling run times.
   repeats: 1                        # The number of repeat function calls used to measure run-times when profiling.
 test:
-  check_preloads: false             # If True, perform a sanity check that the likelihood using preloads is identical to the likelihood not using preloads.
+  check_preloads: false
+  preloads_check_threshold: 0.1     # If the figure of merit of a fit with and without preloads is greater than this threshold, the check preload test fails and an exception raised for a model-fit.              # If True, perform a sanity check that the likelihood using preloads is identical to the likelihood not using preloads.
   exception_override: false
   parallel_profile: false