Merge pull request #579 from niermann999/feat-generate-detfiles

ref: Cleanup in the python directories

.gitignore

@@ -1,3 +1,12 @@
+# data files
+/data/*.csv
+/data/*.cvf
+/data/*.json
+
+# local working directories
 /bin
 /build
+/run
 
+# python files
+**/__pycache__

tests/validation/python/run_file_checker.py → tests/validation/python/file_checker.py

@@ -4,16 +4,18 @@
 #
 # Mozilla Public License Version 2.0
 
+# detray json schema definitions
+from validation.json_schema import geometry_schema
+from validation.json_schema import homogeneous_material_schema
+from validation.json_schema import surface_grid_schema
+
+# python includes
 import argparse
 import json
 import os
 import sys
 from jsonschema import validate
 
-from json_schemas.geometry import geometry_schema
-from json_schemas.homogeneous_material import homogeneous_material_schema
-from json_schemas.surface_grids import surface_grid_schema
-
 def __main__():
 #----------------------------------------------------------------arg parsing
 

tests/validation/python/run_material_validation.py → tests/validation/python/material_validation.py

@@ -4,22 +4,17 @@
 #
 # Mozilla Public License Version 2.0
 
-import plot_material_scan
-from pyplot_factory import pyplot_factory
+# detray includes
+from validation import plot_material_scan as mat_plotter
+from validation import plt_factory
 
 # python includes
 import argparse
 import logging
-import numpy as np
 import pandas as pd
 import os
 import sys
 from datetime import datetime
-import matplotlib.pyplot as plt
-
-
-plt.rc('text', usetex=True)
-plt.rc('text.latex', preamble=r'\usepackage{amsmath}')
 
 
 def __main__():
@@ -106,16 +101,16 @@ def __main__():
 
     df = pd.read_csv(mat_scan_file)
 
-    plot_factory = pyplot_factory(outdir + "material_", logging)
+    plot_factory = plt_factory(outdir + "material_", logging)
 
 #------------------------------------------------------------------------run
 
     # The histograms are not re-weighted (if the rays are not evenly distributed
     # the material in some bins might be artificially high)!
-    plot_material_scan.X0_vs_eta_phi(df, detector_name, plot_factory, out_format)
-    plot_material_scan.L0_vs_eta_phi(df, detector_name, plot_factory, out_format)
-    plot_material_scan.X0_vs_eta(df, detector_name, plot_factory, out_format)
-    plot_material_scan.L0_vs_eta(df, detector_name, plot_factory, out_format)
+    mat_plotter.X0_vs_eta_phi(df, detector_name, plot_factory, out_format)
+    mat_plotter.L0_vs_eta_phi(df, detector_name, plot_factory, out_format)
+    mat_plotter.X0_vs_eta(df, detector_name, plot_factory, out_format)
+    mat_plotter.L0_vs_eta(df, detector_name, plot_factory, out_format)
 
 #-------------------------------------------------------------------------------
 

tests/validation/python/plotting/__init__.py

@@ -0,0 +1,4 @@
+
+from .plot_helpers import filter_data
+from .pyplot_factory import pyplot_factory
+from .pyplot_factory import legend_options, get_legend_options

tests/validation/python/run_ray_scan_validation.py → tests/validation/python/ray_scan_validation.py

@@ -4,8 +4,9 @@
 #
 # Mozilla Public License Version 2.0
 
-import plot_ray_scan
-from pyplot_factory import pyplot_factory
+# detray includes
+from validation import plot_ray_scan as scan_plotter
+from validation import plt_factory
 
 # python includes
 import argparse
@@ -15,11 +16,6 @@
 import os
 import sys
 from datetime import datetime
-import matplotlib.pyplot as plt
-
-
-plt.rc('text', usetex=True)
-plt.rc('text.latex', preamble=r'\usepackage{amsmath}')
 
 
 def __main__():
@@ -122,14 +118,14 @@ def __main__():
 
     df = pd.read_csv(ray_scan_file)
 
-    plot_factory = pyplot_factory(outdir + "geometry_", logging)
+    plot_factory = plt_factory(outdir + "geometry_", logging)
 
 #------------------------------------------------------------------------run
 
-    plot_ray_scan.intersection_points_xy(args, df, detector_name,
-                                         scan_type, plot_factory, out_format)
-    plot_ray_scan.intersection_points_rz(args, df, detector_name, scan_type,
-                                         plot_factory, out_format)
+    scan_plotter.intersection_points_xy(args, df, detector_name,
+                                        scan_type, plot_factory, out_format)
+    scan_plotter.intersection_points_rz(args, df, detector_name, scan_type,
+                                        plot_factory, out_format)
 
 #-------------------------------------------------------------------------------
 

tests/validation/python/validation/__init__.py

@@ -0,0 +1,3 @@
+
+import plotting as plotting
+import plotting.pyplot_factory as plt_factory

tests/validation/python/validation/json_schema/__init__.py

@@ -0,0 +1,4 @@
+
+from .geometry import geometry_schema
+from .homogeneous_material import homogeneous_material_schema
+from .surface_grids import surface_grid_schema

tests/validation/python/plot_material_scan.py → tests/validation/python/validation/plot_material_scan.py

@@ -4,12 +4,11 @@
 #
 # Mozilla Public License Version 2.0
 
-from pyplot_factory import get_legend_options
+from . import plotting
 
 # python includes
 import numpy as np
 import math
-import matplotlib.pyplot as plt
 
 
 """ Calculate edges of bins to plot the mateiral data """
@@ -105,7 +104,7 @@ def X0_vs_eta(df, detector, plotFactory,  out_format =  "pdf"):
 
     # Histogram bin edges
     xBinning, _ = get_n_bins(df)
-    lgd_ops = get_legend_options()
+    lgd_ops = plotting.get_legend_options()
     lgd_ops._replace(loc = 'upper center')
 
     hist_data = plotFactory.hist1D(
@@ -140,7 +139,7 @@ def L0_vs_eta(df, detector, plotFactory,  out_format =  "pdf"):
 
     # Histogram bin edges
     xBinning, _ = get_n_bins(df)
-    lgd_ops = get_legend_options()
+    lgd_ops = plotting.get_legend_options()
     lgd_ops._replace(loc = 'upper center')
 
     hist_data = plotFactory.hist1D(

tests/validation/python/plot_ray_scan.py → tests/validation/python/validation/plot_ray_scan.py

@@ -4,8 +4,7 @@
 #
 # Mozilla Public License Version 2.0
 
-import plot_helpers
-from pyplot_factory import legend_options
+from . import plotting
 
 # python includes
 import numpy as np
@@ -24,13 +23,13 @@ def intersection_points_xy(opts, df, detector, scan_type, plotFactory,  out_form
     portal_range = lambda data: ((data['z'] > min_z) & (data['z'] < max_z) & (data['type'] == 0))
     passive_range = lambda data: ((data['z'] > min_z) & (data['z'] < max_z) & (data['type'] == 2))
 
-    senstive_x, senstive_y = plot_helpers.filter_data(
+    senstive_x, senstive_y = plotting.filter_data(
                                                 data      = df,
                                                 filter    = sensitive_range,
                                                 variables = ['x', 'y'])
 
     # Plot the xy coordinates of the filtered intersections points
-    lgd_ops = legend_options('upper center', 4, 0.4, 0.005)
+    lgd_ops = plotting.legend_options('upper center', 4, 0.4, 0.005)
     hist_data = plotFactory.scatter(
                             figsize = (8, 8),
                             x       = senstive_x,
@@ -44,7 +43,7 @@ def intersection_points_xy(opts, df, detector, scan_type, plotFactory,  out_form
 
     # Portal surfaces
     if not opts.hide_portals:
-        portal_x, portal_y = plot_helpers.filter_data(
+        portal_x, portal_y = plotting.filter_data(
                                                 data      = df,
                                                 filter    = portal_range,
                                                 variables = ['x', 'y'])
@@ -54,7 +53,7 @@ def intersection_points_xy(opts, df, detector, scan_type, plotFactory,  out_form
 
     # Passive surfaces
     if not opts.hide_passives:
-        passive_x, passive_y = plot_helpers.filter_data(
+        passive_x, passive_y = plotting.filter_data(
                                                 data      = df,
                                                 filter    = passive_range,
                                                 variables = ['x', 'y'])
@@ -90,13 +89,13 @@ def intersection_points_rz(opts, df, detector, scan_type, plotFactory,  out_form
     portal_range = lambda data: (data['type'] == 0)
     passive_range = lambda data: (data['type'] == 2)
 
-    sensitive_x, sensitive_y, sensitive_z = plot_helpers.filter_data(
+    sensitive_x, sensitive_y, sensitive_z = plotting.filter_data(
                                                 data      = df,
                                                 filter    = sensitive_range,
                                                 variables = ['x', 'y', 'z'])
 
     # Plot the xy coordinates of the filtered intersections points
-    lgd_ops = legend_options('upper center', 4, 0.8, 0.005)
+    lgd_ops = plotting.legend_options('upper center', 4, 0.8, 0.005)
     hist_data = plotFactory.scatter(
                             figsize = (12, 6),
                             x      = sensitive_z,
@@ -110,7 +109,7 @@ def intersection_points_rz(opts, df, detector, scan_type, plotFactory,  out_form
 
     # Portal surfaces
     if not opts.hide_portals:
-        portal_x, portal_y, portal_z = plot_helpers.filter_data(
+        portal_x, portal_y, portal_z = plotting.filter_data(
                                                     data      = df,
                                                     filter    = portal_range,
                                                     variables = ['x', 'y', 'z'])
@@ -121,7 +120,7 @@ def intersection_points_rz(opts, df, detector, scan_type, plotFactory,  out_form
 
     # Passive surfaces
     if not opts.hide_passives:
-        passive_x, passive_y, passive_z = plot_helpers.filter_data(
+        passive_x, passive_y, passive_z = plotting.filter_data(
                                                     data      = df,
                                                     filter    = passive_range,
                                                     variables = ['x', 'y', 'z'])