add drafts of listing files

open-atmos · Aug 1, 2023 · d07cb89 · d07cb89
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diff --git a/examples/paper_listings/fortran/CMakeLists.txt b/examples/paper_listings/fortran/CMakeLists.txt
@@ -0,0 +1,19 @@
+project(main LANGUAGES Fortran)
+add_executable(main
+  main.f90
+  $ENV{PARTMC_HOME}/src/spec_file.F90
+  $ENV{PARTMC_HOME}/src/spec_line.F90
+  $ENV{PARTMC_HOME}/src/util.F90
+  $ENV{PARTMC_HOME}/src/constants.F90
+  $ENV{PARTMC_HOME}/src/aero_data.F90
+  $ENV{PARTMC_HOME}/src/aero_mode.F90
+  $ENV{PARTMC_HOME}/src/aero_dist.F90
+  $ENV{PARTMC_HOME}/src/aero_state.F90
+  $ENV{PARTMC_HOME}/src/mpi.F90
+  $ENV{PARTMC_HOME}/src/fractal.F90
+  $ENV{PARTMC_HOME}/src/netcdf.F90
+)
+target_include_directories(
+  main
+  PRIVATE /home/slayoo/devel/PyPartMC/build/temp.linux-x86_64-3.10/_PyPartMC
+)
diff --git a/examples/paper_listings/fortran/aero_data.dat b/examples/paper_listings/fortran/aero_data.dat
@@ -0,0 +1,2 @@
+#     dens (kg/m^3)   ions in soln (1)    molec wght (kg/mole)   kappa (1)
+H2O            1000                0                   18d-3      0
diff --git a/examples/paper_listings/fortran/aero_dist.dat b/examples/paper_listings/fortran/aero_dist.dat
@@ -0,0 +1,15 @@
+mode_name mode_a
+mass_frac aero_mode_a_comp.dat
+diam_type geometric
+mode_type log_normal
+num_conc 9.0E+06  # (#/m^2)
+geom_mean_diam 8.64e-8  # (m)
+log10_geom_std_dev 0.28
+
+mode_name mode_b
+mass_frac aero_mode_b_comp.dat
+diam_type geometric
+mode_type log_normal
+num_conc 1.6E+08  # (#/m^2)
+geom_mean_diam 5e-8
+log10_geom_std_dev 0.24
diff --git a/examples/paper_listings/fortran/aero_mode_a_comp.dat b/examples/paper_listings/fortran/aero_mode_a_comp.dat
@@ -0,0 +1,3 @@
+#        proportion
+H2O             1
+
diff --git a/examples/paper_listings/fortran/aero_mode_b_comp.dat b/examples/paper_listings/fortran/aero_mode_b_comp.dat
@@ -0,0 +1,3 @@
+#        proportion
+H2O             1
+
diff --git a/examples/paper_listings/fortran/main.f90 b/examples/paper_listings/fortran/main.f90
@@ -0,0 +1,22 @@
+program main
+
+  use pmc_spec_file
+  use pmc_aero_data
+  use pmc_aero_mode
+  use pmc_aero_dist
+
+  type(spec_file_t) :: f_aero_data, f_aero_dist
+  type(aero_data_t) :: aero_data
+  type(aero_dist_t) :: aero_dist
+
+  call spec_file_open("aero_data.dat", f_aero_data)
+  call spec_file_read_aero_data(f_aero_data, aero_data)
+  call spec_file_close(f_aero_data)
+
+  call spec_file_open("aero_dist.dat", f_aero_dist)
+  call spec_file_read_aero_dist(f_aero_dist, aero_data, aero_dist)
+  call spec_file_close(f_aero_dist)
+
+  print*, aero_dist_total_num_conc(aero_dist)
+
+end
diff --git a/examples/paper_listings/julia/main.jl b/examples/paper_listings/julia/main.jl
@@ -0,0 +1,47 @@
+using Pkg
+Pkg.add("PyCall")
+
+using PyCall
+ppmc = pyimport("PyPartMC")
+
+si = ppmc["si"]
+
+aero_data = ppmc.AeroData((
+  #       (density, ions in solution, molecular weight, kappa)
+  Dict("OC" => (1000 * si.kg/si.m^3, 0, 1e-3 * si.kg/si.mol, 0.001)),
+  Dict("BC" => (1800 * si.kg/si.m^3, 0, 1e-3 * si.kg/si.mol, 0))
+))
+
+aero_dist = ppmc.AeroDist(aero_data, (
+  Dict( 
+    "cooking" => Dict(
+      "mass_frac" => (Dict("OC" => (1,)),),
+      "diam_type" => "geometric",
+      "mode_type" => "log_normal",
+      "num_conc" => 3200 / si.cm^3,
+      "geom_mean_diam" => 8.64 * si.nm,
+      "log10_geom_std_dev" => .28,
+    )
+  ),
+  Dict( 
+    "diesel" => Dict(
+      "mass_frac" => (Dict("OC" => (.3,)), Dict("BC" => (.7,))),
+      "diam_type" => "geometric",
+      "mode_type" => "log_normal",
+      "num_conc" => 2900 / si.m^3,
+      "geom_mean_diam" => 50 * si.nm,
+      "log10_geom_std_dev" => .24,
+    )
+  )
+))
+
+n_part = 100 
+seed = 44
+offset = 0 
+
+aero_state = ppmc.AeroState(n_part, aero_data)
+
+ppmc.rand_init(seed, offset)
+aero_state.dist_sample(aero_dist)
+
+print(sum(aero_state.masses))
diff --git a/examples/paper_listings/python/main.py b/examples/paper_listings/python/main.py
@@ -0,0 +1,49 @@
+import numpy as np
+
+import PyPartMC as ppmc
+from PyPartMC import si
+
+aero_data = ppmc.AeroData(
+    (
+        #      [density, ions in solution, molecular weight, kappa]
+        {"OC": [1000 * si.kg / si.m**3, 0, 1e-3 * si.kg / si.mol, 0.001]},
+        {"BC": [1800 * si.kg / si.m**3, 0, 1e-3 * si.kg / si.mol, 0]},
+    )
+)
+
+aero_dist = ppmc.AeroDist(
+    aero_data,
+    [
+        {
+            "cooking": {
+                "mass_frac": [{"OC": [1]}],
+                "diam_type": "geometric",
+                "mode_type": "log_normal",
+                "num_conc": 3200 / si.cm**3,
+                "geom_mean_diam": 8.64 * si.nm,
+                "log10_geom_std_dev": 0.28,
+            }
+        },
+        {
+            "diesel": {
+                "mass_frac": [{"OC": [0.3]}, {"BC": [0.7]}],
+                "diam_type": "geometric",
+                "mode_type": "log_normal",
+                "num_conc": 2900 / si.cm**3,
+                "geom_mean_diam": 50 * si.nm,
+                "log10_geom_std_dev": 0.24,
+            }
+        },
+    ],
+)
+
+n_part = 100
+seed = 44
+offset = 0
+
+aero_state = ppmc.AeroState(n_part, aero_data)
+
+ppmc.rand_init(seed, offset)
+aero_state.dist_sample(aero_dist)
+
+print(np.sum(aero_state.masses))