plots
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a467318d24
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import sys
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import os
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import yaml
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import matplotlib.pyplot as plt
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import numpy as np
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def total_boxplot(DATA, creator = 'any', tester = 'any', simulation = "dummy simulation"):
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fig, ax = plt.subplots()
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data_to_plot = []
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labels = []
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title = f'Boxplot of scores in {simulation},'
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xlabel = ""
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colors_list = plt.colormaps['tab10'].colors
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if creator == tester == 'any':
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print(f"Warning: setting both creator and tester as 'any' plots only self testing!")
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title += f" self testing"
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xlabel = "self tester"
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for creator_name, data in DATA.items():
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if creator_name in data:
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data_to_plot.append(data[creator_name])
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labels.append(creator_name)
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elif creator == 'any':
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title += f" tester: {tester}"
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xlabel = "creator"
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for creator_name, data in DATA.items():
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if tester in data:
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data_to_plot.append(data[tester])
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#labels.append(f"{creator_name}-{tester}")
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labels.append(creator_name)
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elif tester == 'any':
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title += f" creator: {creator}"
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xlabel = "tester"
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if creator in DATA:
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for tester_name, data in DATA[creator].items():
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data_to_plot.append(data)
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#labels.append(f"{creator}-{tester}")
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labels.append(tester_name)
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if len(data_to_plot) == 0:
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print("No appropriate data!")
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return
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#print(len(data_to_plot), len(labels))
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elements = ax.boxplot(data_to_plot, patch_artist=True, tick_labels=labels)
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for i, patch in enumerate(elements['boxes']):
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patch.set_facecolor(colors_list[(i)%10])
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ax.grid()
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#ax.legend()
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ax.set(xlabel=xlabel, ylabel='Score')
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ax.set_title(title)
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def heat_map(DATA, criteria = np.median):
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names_to_nums = {name: num for num, name in enumerate(list(DATA.keys()))}
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values = np.zeros( (len(names_to_nums)+1, len(names_to_nums)+1) )
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testers = {}
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for creator, Data in DATA.items():
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total_creator = []
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for tester, data in Data.items():
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if not tester in testers:
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testers[tester] = []
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if creator in names_to_nums and tester in names_to_nums:
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creator_idx = names_to_nums[creator]
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tester_idx = names_to_nums[tester]
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values[creator_idx, tester_idx] = criteria(data)
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total_creator += data
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testers[tester] +=data
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values[creator_idx, len(names_to_nums)] = criteria(total_creator)
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for tester, data in testers.items():
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tester_idx = names_to_nums[tester]
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values[len(names_to_nums), tester_idx] = criteria(data)
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fig, ax = plt.subplots()
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im = ax.imshow(values, cmap='coolwarm')
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for i in range(values.shape[0]):
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for j in range(values.shape[1]):
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text = ax.text(j, i, round(values[i, j],1), ha="center", va="center", color="k")
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ax.set_xticks(range(len(DATA.keys())+1), labels=list(DATA.keys())+['mean'] )
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ax.set_yticks(range(len(DATA.keys())+1), labels=list(DATA.keys())+['mean'] )
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ax.set(xlabel='tester', ylabel='creator')
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ax.set_title("Cross-validation heatmap")
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def convert_score(data):
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score = data['score']
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Nsof = len(data['exted_sofs'])
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Ncol = len(data['collisions'])
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Ksof = data['k_params']['_k_sof']
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Khp = data['k_params']['_k_hp']
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Kch = data['k_params']['_k_charge']
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Khp_max = 100
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Kch_max = 100
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Kch_r = (score - Ksof*Nsof-Khp*(Khp_max-Ncol)/Khp_max) * Kch_max/Kch
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score_new = Ksof*Nsof*(Kch*Kch_r/Khp_max+Khp*(Khp_max-Ncol)/Khp_max)
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#print(type(score_new))
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return score_new
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if __name__ == '__main__':
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global_path = "/home/gestures6/Easy_sim/dummy_simulation/stats/"
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# 1. Name (Dima)
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# 2. Name-Name (Dima-Elisey)
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DATA = {} # Name of creator - {} - Name of tester
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for dirname in sorted(os.listdir(global_path)):
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dirpath = os.path.join(global_path, dirname)
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if os.path.isdir(dirpath) and not dirname.startswith('!'):
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data = []
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if not '-' in dirname:
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name = dirname
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if not name in DATA:
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DATA[name] = {}
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DATA[name][name] = data
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else:
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names = dirname.split('-')
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name1 = names[0]
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name2 = names[1]
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if not name1 in DATA:
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DATA[name1] = {}
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DATA[name1][name2] = data
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for filename in sorted(os.listdir(dirpath)):
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file_path = os.path.join(dirpath, filename)
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if file_path.endswith('.yaml'):
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with open(file_path, 'r', encoding='utf-8') as file:
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datafile = yaml.load(file, Loader = yaml.Loader)
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data.append(convert_score(datafile)) # TODO change score to new formula
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#data.append(datafile['score'])
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#for cr, data in DATA.items():
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#print(f"{cr}: {data}")
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total_boxplot(DATA, creator = 'any', tester = 'any')
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for name in DATA.keys():
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total_boxplot(DATA, creator = name, tester = 'any')
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total_boxplot(DATA, creator = 'any', tester = name)
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heat_map(DATA)
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plt.show()
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