* rename histo to histogram

* add documentation for image export
* move validation to `Ingredient.py`

cellpack/autopack/Analysis.py

@@ -407,9 +407,9 @@ def grabResultFromTXT(self, n, doanalyze=False):
                     numpy.array(e3[2]),
                     delimiter=",",
                 )
-                self.histo(e3[0], ingrname + "_euler_X.png")
-                self.histo(e3[1], ingrname + "_euler_Y.png")
-                self.histo(e3[2], ingrname + "_euler_Z.png")
+                self.histogram(e3[0], ingrname + "_euler_X.png")
+                self.histogram(e3[1], ingrname + "_euler_Y.png")
+                self.histogram(e3[2], ingrname + "_euler_Z.png")
         return ingrpos, ingrrot
 
     # should take any type of list...
@@ -491,7 +491,7 @@ def rdf_3d(self, ingr):
             numpy.array(self.env.ingredient_positions[ingr.name]),
             delimiter=",",
         )
-        self.histo(distances, basename + ingr.name + "_histo.png")
+        self.histogram(distances, basename + ingr.name + "_histo.png")
         numpy.savetxt(
             basename + ingr.name + "_distances.csv",
             numpy.array(distances),
@@ -600,7 +600,7 @@ def rdf_2d(self, ingr):
             numpy.array(self.env.ingredient_positions[ingr.name]),
             delimiter=",",
         )
-        self.histo(distances, basename + ingr.name + "_histo.png")
+        self.histogram(distances, basename + ingr.name + "_histo.png")
         numpy.savetxt(
             basename + ingr.name + "_distances.csv",
             numpy.array(distances),
@@ -654,7 +654,7 @@ def plot_position_distribution_total(self, all_positions):
         pos_sph = self.cartesian_to_sph(pos_xyz)
         all_pos = numpy.hstack([pos_xyz, pos_sph])
         for ind, dim in enumerate(self.get_list_of_dims()):
-            self.histo(
+            self.histogram(
                 all_pos[:, ind],
                 self.figures_path
                 / f"all_ingredient_histo_{dim}_{self.env.basename}.png",
@@ -670,7 +670,7 @@ def plot_position_distribution(self, ingr):
         pos_sph = self.cartesian_to_sph(pos_xyz)
         all_pos = numpy.hstack([pos_xyz, pos_sph])
         for ind, dim in enumerate(self.get_list_of_dims()):
-            self.histo(
+            self.histogram(
                 all_pos[:, ind],
                 self.figures_path / f"{ingr.name}_histo_{dim}_{self.env.basename}.png",
                 title_str=ingr.name,
@@ -691,7 +691,7 @@ def plot_occurence_distribution(self, ingr):
             x_label="seed",
             y_label="occurrences",
         )
-        self.histo(
+        self.histogram(
             distances=numpy.array(occ),
             filename=self.figures_path
             / f"{ingr.name}_occurrence_{self.env.basename}_histo.png",
@@ -707,7 +707,7 @@ def plot_distance_distribution(self, all_ingredient_distances):
         for ingr_key, distances in all_ingredient_distances.items():
             if len(distances) <= 1:
                 continue
-            self.histo(
+            self.histogram(
                 distances=numpy.array(distances),
                 filename=self.figures_path
                 / f"{ingr_key}_pairwise_distances_{self.env.basename}.png",
@@ -1704,7 +1704,7 @@ def get_parametrized_representation(
 
         return all_spilr
 
-    def histo(self, distances, filename, title_str="", x_label="", y_label=""):
+    def histogram(self, distances, filename, title_str="", x_label="", y_label=""):
         plt.clf()
         # calculate histogram
         nbins = int(numpy.sqrt(len(distances)))
@@ -2584,7 +2584,7 @@ def doloop(
 
             # plot histograms for all combined distances
             if len(all_center_distance_array) > 1:
-                self.histo(
+                self.histogram(
                     all_center_distance_array,
                     self.figures_path
                     / f"all_ingredient_center_distances_{self.env.basename}.png",
@@ -2594,7 +2594,7 @@ def doloop(
                 )
 
             if len(all_center_distance_array) > 1:
-                self.histo(
+                self.histogram(
                     all_pairwise_distance_array,
                     self.figures_path
                     / f"all_ingredient_pairwise_distances_{self.env.basename}.png",
@@ -2605,21 +2605,21 @@ def doloop(
 
             # plot the angle
             if len(all_ingredient_angle_array) > 1:
-                self.histo(
+                self.histogram(
                     all_ingredient_angle_array[0],
                     self.figures_path / f"all_angles_X_{self.env.basename}.png",
                     title_str="all_ingredients",
                     x_label="angles X",
                     y_label="count",
                 )
-                self.histo(
+                self.histogram(
                     all_ingredient_angle_array[1],
                     self.figures_path / f"all_angles_Y_{self.env.basename}.png",
                     title_str="all_ingredients",
                     x_label="angles Y",
                     y_label="count",
                 )
-                self.histo(
+                self.histogram(
                     all_ingredient_angle_array[2],
                     self.figures_path / f"all_angles_Z_{self.env.basename}.png",
                     title_str="all_ingredients",

cellpack/autopack/Compartment.py

@@ -3131,6 +3131,14 @@ def create_voxelized_mask(
     ):
         """
         Creates a mask of the compartment voxelization
+
+        :param x_width: number of voxels in the x direction
+        :param y_width: number of voxels in the y direction
+        :param z_width: number of voxels in the z direction
+        :param center: center of the voxelization
+        :param voxel_size: size of the voxels
+        :param mesh_store: mesh store
+        :param hollow: if True, the mask will be hollow otherwise it will fill in the segmentation
         """
         if voxel_size is None:
             voxel_size = numpy.array([1, 1, 1], dtype=int)

cellpack/autopack/Environment.py

@@ -90,8 +90,6 @@
 from .trajectory import dcdTrajectory, molbTrajectory
 from .randomRot import RandomRot
 
-from cellpack.autopack.interface_objects.meta_enum import MetaEnum
-
 try:
     helper = autopack.helper
 except ImportError:
@@ -108,29 +106,6 @@
 verbose = 0
 
 
-class CountDistributions(MetaEnum):
-    "All available count distributions"
-    UNIFORM = "uniform"
-    NORMAL = "normal"
-    LIST = "list"
-
-
-class CountOptions(MetaEnum):
-    "All available count options"
-    MIN = "min"
-    MAX = "max"
-    MEAN = "mean"
-    STD = "std"
-    LIST_VALUES = "list_values"
-
-
-REQUIRED_COUNT_OPTIONS = {
-    CountDistributions.UNIFORM: [CountOptions.MIN, CountOptions.MAX],
-    CountDistributions.NORMAL: [CountOptions.MEAN, CountOptions.STD],
-    CountDistributions.LIST: [CountOptions.LIST_VALUES],
-}
-
-
 class Environment(CompartmentList):
     """
     The Environment class
@@ -340,35 +315,6 @@ def setSeed(self, seedNum):
         self.seed_set = True
         self.seed_used = SEED
 
-    @staticmethod
-    def validate_ingredient_info(ingredient_info):
-        """
-        Validates ingredient info and returns validated ingredient info
-        """
-        if "count" not in ingredient_info:
-            raise Exception("Ingredient info must contain a count")
-
-        if ingredient_info["count"] < 0:
-            raise Exception("Ingredient count must be greater than or equal to 0")
-
-        if "count_options" in ingredient_info:
-            count_options = ingredient_info["count_options"]
-            if "distribution" not in count_options:
-                raise Exception("Ingredient count options must contain a distribution")
-            if not CountDistributions.is_member(count_options["distribution"]):
-                raise Exception(
-                    f"{count_options['distribution']} is not a valid count distribution"
-                )
-            for required_option in REQUIRED_COUNT_OPTIONS.get(
-                count_options["distribution"], []
-            ):
-                if required_option not in count_options:
-                    raise Exception(
-                        f"Missing option '{required_option}' for {count_options['distribution']} distribution"
-                    )
-
-        return ingredient_info
-
     def _prep_ingredient_info(self, composition_info, ingredient_name=None):
         objects_dict = self.recipe_data["objects"]
         object_key = composition_info["object"]
@@ -379,7 +325,9 @@ def _prep_ingredient_info(self, composition_info, ingredient_name=None):
             ingredient_name if ingredient_name is not None else object_key
         )
         ingredient_info["object_name"] = object_key
-        ingredient_info = self.validate_ingredient_info(ingredient_info)
+        ingredient_info = ingredient.Ingredient.validate_ingredient_info(
+            ingredient_info
+        )
         return ingredient_info
 
     def _step_down(self, compartment_key, prev_compartment=None):

cellpack/autopack/ingredient/Ingredient.py

@@ -64,13 +64,37 @@
 from cellpack.autopack.upy.simularium.simularium_helper import simulariumHelper
 import cellpack.autopack as autopack
 from cellpack.autopack.ingredient.agent import Agent
+from cellpack.autopack.interface_objects.meta_enum import MetaEnum
 
 helper = autopack.helper
 reporthook = None
 if helper is not None:
     reporthook = helper.reporthook
 
 
+class CountDistributions(MetaEnum):
+    "All available count distributions"
+    UNIFORM = "uniform"
+    NORMAL = "normal"
+    LIST = "list"
+
+
+class CountOptions(MetaEnum):
+    "All available count options"
+    MIN = "min"
+    MAX = "max"
+    MEAN = "mean"
+    STD = "std"
+    LIST_VALUES = "list_values"
+
+
+REQUIRED_COUNT_OPTIONS = {
+    CountDistributions.UNIFORM: [CountOptions.MIN, CountOptions.MAX],
+    CountDistributions.NORMAL: [CountOptions.MEAN, CountOptions.STD],
+    CountDistributions.LIST: [CountOptions.LIST_VALUES],
+}
+
+
 class IngredientInstanceDrop:
     def __init__(self, ptId, position, rotation, ingredient, rb=None):
         self.ptId = ptId
@@ -336,6 +360,35 @@ def __init__(
         self.organism = ""
         # add tiling property ? as any ingredient coud tile as hexagon. It is just the packing type
 
+    @staticmethod
+    def validate_ingredient_info(ingredient_info):
+        """
+        Validates ingredient info and returns validated ingredient info
+        """
+        if "count" not in ingredient_info:
+            raise Exception("Ingredient info must contain a count")
+
+        if ingredient_info["count"] < 0:
+            raise Exception("Ingredient count must be greater than or equal to 0")
+
+        if "count_options" in ingredient_info:
+            count_options = ingredient_info["count_options"]
+            if "distribution" not in count_options:
+                raise Exception("Ingredient count options must contain a distribution")
+            if not CountDistributions.is_member(count_options["distribution"]):
+                raise Exception(
+                    f"{count_options['distribution']} is not a valid count distribution"
+                )
+            for required_option in REQUIRED_COUNT_OPTIONS.get(
+                count_options["distribution"], []
+            ):
+                if required_option not in count_options:
+                    raise Exception(
+                        f"Missing option '{required_option}' for {count_options['distribution']} distribution"
+                    )
+
+        return ingredient_info
+
     def reset(self):
         """reset the states of an ingredient"""
         self.counter = 0