plots

bloxplot_stats.py

@@ -34,6 +34,8 @@ def plot(ax, path, color):
     ax.plot(range(1, len(scores)+1),scores, '.-', label=f"{path.split('/')[-1]}'s scores", color = color)
     ax.plot((1, len(scores)),(s_a(scores), s_a(scores)), '--', label=f"{path.split('/')[-1]}'s mean ({round(s_a(scores), 3)})", color = color)
     ax.plot((1, len(scores)),(mediana(scores), mediana(scores)), ':', label=f"{path.split('/')[-1]}'s mediana ({round(mediana(scores), 3)})", color = color)
+
+
 def boxplot(ax, path, color):
     scores =[]
 
@@ -52,6 +54,44 @@ def boxplot(ax, path, color):
 
 
 if __name__ == '__main__':
+
+    global_path = "/home/gestures/Easy_sim/dummy_simulation/stats/"
+    # 1. Name (Dima)
+    # 2. Name-Name (Dima-Elisey)
+
+    DATA = {} # Name of creator - {} - Name of tester
+
+    for dirname in sorted(os.listdir(global_path)):
+        dirpath = os.path.join(global_path, dirname)
+        if os.path.isdir(file_path):
+            data = []
+            if not dirname.contains('-'):
+                name = dirname
+                if not name is DATA:
+                    DATA[name] = {}
+                DATA[name][name] = data
+            else:
+                names = dirname.split('-')
+                name1 = names[0]
+                name2 = names[1]
+                if not name1 is DATA:
+                    DATA[name1] = {}
+                DATA[name1][name2] = data
+            for filename in sorted(os.listdir(dirpath)):
+                file_path = os.path.join(dirpath, filename)
+                if file_path.endswith('.yaml'):
+                    with open(file_path, 'r', encoding='utf-8') as file:
+                    datafile = yaml.load(file, Loader = yaml.Loader)
+                    # TODO change score to new formula
+                    data.append(datafile['score'])
+
+
+
+
+
+
+
+
     fig, ax = plt.subplots()
 
     boxplot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Dima", "limegreen")

fullplot_stats.py

@@ -0,0 +1,164 @@
+import sys
+import os
+import yaml
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def total_boxplot(DATA, creator = 'any', tester = 'any', simulation = "dummy simulation"):
+
+    fig, ax = plt.subplots()
+
+    data_to_plot = []
+    labels = []
+    title = f'Boxplot of scores in {simulation},'
+    xlabel = ""
+
+    colors_list = plt.colormaps['tab10'].colors
+
+    if creator == tester == 'any':
+        print(f"Warning: setting both creator and tester as 'any' plots only self testing!")
+        title += f" self testing"
+        xlabel = "self tester"
+        for creator_name, data in DATA.items():
+            if creator_name in data:
+                data_to_plot.append(data[creator_name])
+                labels.append(creator_name)
+
+    elif creator == 'any':
+        title += f" tester: {tester}"
+        xlabel = "creator"
+        for creator_name, data in DATA.items():
+            if tester in data:
+                data_to_plot.append(data[tester])
+                #labels.append(f"{creator_name}-{tester}")
+                labels.append(creator_name)
+
+    elif tester == 'any':
+        title += f" creator: {creator}"
+        xlabel = "tester"
+        if creator in DATA:
+            for tester_name, data in DATA[creator].items():
+                data_to_plot.append(data)
+                #labels.append(f"{creator}-{tester}")
+                labels.append(tester_name)
+
+
+    if len(data_to_plot) == 0:
+        print("No appropriate data!")
+        return
+
+
+    #print(len(data_to_plot), len(labels))
+    elements = ax.boxplot(data_to_plot, patch_artist=True, tick_labels=labels)
+    for i, patch in enumerate(elements['boxes']):
+        patch.set_facecolor(colors_list[(i)%10])
+
+    ax.grid()
+    #ax.legend()
+    ax.set(xlabel=xlabel, ylabel='Score')
+    ax.set_title(title)
+
+
+def heat_map(DATA, criteria = np.median):
+
+    names_to_nums = {name: num for num, name in enumerate(list(DATA.keys()))}
+    values = np.zeros( (len(names_to_nums)+1, len(names_to_nums)+1) )
+
+    testers = {}
+    for creator, Data in DATA.items():
+        total_creator = []
+        for tester, data in Data.items():
+            if not tester in testers:
+                testers[tester] = []
+            if creator in names_to_nums and tester in names_to_nums:
+                creator_idx = names_to_nums[creator]
+                tester_idx = names_to_nums[tester]
+                values[creator_idx, tester_idx] = criteria(data)
+                total_creator += data
+                testers[tester] +=data
+            values[creator_idx, len(names_to_nums)] = criteria(total_creator)
+
+    for tester, data in testers.items():
+        tester_idx = names_to_nums[tester]
+        values[len(names_to_nums), tester_idx] = criteria(data)
+
+    fig, ax = plt.subplots()
+    im = ax.imshow(values, cmap='coolwarm')
+
+    for i in range(values.shape[0]):
+        for j in range(values.shape[1]):
+            text = ax.text(j, i, round(values[i, j],1), ha="center", va="center", color="k")
+
+    ax.set_xticks(range(len(DATA.keys())+1), labels=list(DATA.keys())+['mean'] )
+    ax.set_yticks(range(len(DATA.keys())+1), labels=list(DATA.keys())+['mean'] )
+
+    ax.set(xlabel='tester', ylabel='creator')
+    ax.set_title("Cross-validation heatmap")
+
+
+def convert_score(data):
+
+    score = data['score']
+    Nsof = len(data['exted_sofs'])
+    Ncol = len(data['collisions'])
+    Ksof = data['k_params']['_k_sof']
+    Khp = data['k_params']['_k_hp']
+    Kch = data['k_params']['_k_charge']
+    Khp_max = 100
+    Kch_max = 100
+
+    Kch_r = (score - Ksof*Nsof-Khp*(Khp_max-Ncol)/Khp_max) * Kch_max/Kch
+
+    score_new = Ksof*Nsof*(Kch*Kch_r/Khp_max+Khp*(Khp_max-Ncol)/Khp_max)
+    #print(type(score_new))
+
+    return score_new
+
+if __name__ == '__main__':
+
+    global_path = "/home/gestures6/Easy_sim/dummy_simulation/stats/"
+    # 1. Name (Dima)
+    # 2. Name-Name (Dima-Elisey)
+
+    DATA = {} # Name of creator - {} - Name of tester
+
+    for dirname in sorted(os.listdir(global_path)):
+        dirpath = os.path.join(global_path, dirname)
+        if os.path.isdir(dirpath) and not dirname.startswith('!'):
+            data = []
+            if not '-' in dirname:
+                name = dirname
+                if not name in DATA:
+                    DATA[name] = {}
+                DATA[name][name] = data
+            else:
+                names = dirname.split('-')
+                name1 = names[0]
+                name2 = names[1]
+                if not name1 in DATA:
+                    DATA[name1] = {}
+                DATA[name1][name2] = data
+            for filename in sorted(os.listdir(dirpath)):
+                file_path = os.path.join(dirpath, filename)
+                if file_path.endswith('.yaml'):
+                    with open(file_path, 'r', encoding='utf-8') as file:
+                        datafile = yaml.load(file, Loader = yaml.Loader)
+                        data.append(convert_score(datafile)) # TODO change score to new formula
+                        #data.append(datafile['score'])
+
+
+    #for cr, data in DATA.items():
+        #print(f"{cr}: {data}")
+
+    total_boxplot(DATA, creator = 'any', tester = 'any')
+
+    for name in DATA.keys():
+
+        total_boxplot(DATA, creator = name, tester = 'any')
+        total_boxplot(DATA, creator = 'any', tester = name)
+
+    heat_map(DATA)
+
+    plt.show()
+