bar plots

code/line_plots.py

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+import os
+
+from experiment import Experiment
+# noinspection PyUnresolvedReferences
+from soup import Soup
+
+from argparse import ArgumentParser
+import numpy as np
+
+import plotly as pl
+import plotly.graph_objs as go
+
+import colorlover as cl
+
+import dill
+
+from sklearn.manifold.t_sne import TSNE, PCA
+
+
+def build_args():
+    arg_parser = ArgumentParser()
+    arg_parser.add_argument('-i', '--in_file', nargs=1, type=str)
+    arg_parser.add_argument('-o', '--out_file', nargs='?', default='out', type=str)
+    return arg_parser.parse_args()
+
+
+def line_plot(names_exp_tuple, filename='lineplot'):
+
+    names, line_dict_list = names_exp_tuple
+
+    names = "Weightwise Neural Network"
+
+    data = []
+    base_scale = cl.scales['10']['div']['RdYlGn']
+    scale = cl.interp(base_scale, len(line_dict_list) + 1)  # Map color scale to N bins
+    for ld_id, line_dict in enumerate(line_dict_list):
+        trace = go.Scatter(
+            x=line_dict['xs'],
+            y=line_dict['ys'],
+            # mode='lines',
+            name=names,
+            line=dict(color=scale[ld_id]),
+        )
+
+        data.append(trace)
+
+    layout = dict(title='{} Weight Wise Mixed '.format(''),
+                  # height=800, width=800, margin=dict(l=0, r=0, t=0, b=0)
+                  )
+
+    fig = go.Figure(data=data, layout=layout)
+    pl.offline.plot(fig, auto_open=True, filename=filename)
+    pass
+
+
+def search_and_apply(absolut_file_or_folder, plotting_function, files_to_look_for=[]):
+    if os.path.isdir(absolut_file_or_folder):
+        for sub_file_or_folder in os.scandir(absolut_file_or_folder):
+            search_and_apply(sub_file_or_folder.path, plotting_function, files_to_look_for=files_to_look_for)
+    elif absolut_file_or_folder.endswith('.dill'):
+        file_or_folder = os.path.split(absolut_file_or_folder)[-1]
+        if file_or_folder in files_to_look_for and not os.path.exists('{}.html'.format(absolut_file_or_folder[:-5])):
+            print('Apply Plotting function "{func}" on file "{file}"'.format(func=plotting_function.__name__,
+                                                                             file=absolut_file_or_folder)
+                  )
+            with open(absolut_file_or_folder, 'rb') as in_f:
+                exp = dill.load(in_f)
+
+            names_dill_location = os.path.join(*os.path.split(absolut_file_or_folder)[:-1], 'all_names.dill')
+            with open(names_dill_location, 'rb') as in_f:
+                names = dill.load(in_f)
+
+            try:
+                plotting_function((names, exp), filename='{}.html'.format(absolut_file_or_folder[:-5]))
+            except ValueError:
+                pass
+            except AttributeError:
+                pass
+        else:
+            # This was either another FilyType or Plot.html alerady exists.
+            pass
+
+
+if __name__ == '__main__':
+    args = build_args()
+    in_file = args.in_file[0]
+    out_file = args.out_file
+
+    search_and_apply(in_file, line_plot, ["all_data.dill"])
+