vector_plotting (not working correctly)

src/vector_ploting.py

@@ -0,0 +1,97 @@
+from numpy import *
+import math
+import matplotlib.pyplot as plt
+from sympy import im
+import sys
+import dictdatabase as ddb
+
+# t = linspace(0, 2*math.pi, 400)
+# a = sin(t)
+# b = cos(t)
+# c = a + b
+
+# plt.plot(t, a, 'r') # plotting t, a separately 
+# plt.plot(t, b, 'b') # plotting t, b separately 
+# plt.plot(t, c, 'g') # plotting t, c separately 
+# plt.show()
+
+import numpy as np
+import matplotlib
+import json
+import matplotlib.pyplot as plt
+import os
+
+
+def plot_eval_meassures(data, path, plot_color):
+
+    fig = plt.figure()
+    ax = plt.axes()
+
+    plt.xlabel("Recall")
+    plt.ylabel("Precision")
+
+    for i in range(0,len(data)):
+        P_vs_R = {}
+
+        for key in data[i]:
+            if key != "max":
+                P_vs_R[data[i][key]["P"]] = data[i][key]["R"]
+
+        P_vs_R = sorted(P_vs_R.items(), key=lambda x: x[1])
+
+        x = [P_vs_R[i][1]
+             for i in range(0, len(P_vs_R))]  # Recall
+        y = [P_vs_R[i][0] for i in range(0, len(P_vs_R))]  # Precision
+
+
+        ax.plot(x, y, color=plot_color[i])
+
+    if sys.platform.startswith('win'):
+        fig.savefig(path[0] + "\PR_plot.png")
+    elif sys.platform.startswith('linux'):
+        fig.savefig(path[0] + "/PR_plot.png")
+
+path = os.getcwd()
+
+models = ["BooleanModel", "VectorModel", "FuzzyModel"]
+corpus = [("cranfield", "orange"), ("vaswani", "plum"), 
+          ("cord19\\trec-covid\\round1", "turquoise") if sys.platform.startswith('win') else ("cord19/trec-covid/round1", "turquoise")]
+
+for model in models:
+    data_list = []
+    path_list = []
+    for corp in corpus:
+        if sys.platform.startswith('linux'):
+            if model != "FuzzyModel" or corp[0] != "cord19/trec-covid/round1":
+                temp = path.removesuffix("/src") + f'/ddb_storage/{model}/{corp[0]}'
+                path_list.append(temp)
+
+                with open(temp + "/k_Rank.json") as json_file:
+                    data = json.load(json_file)
+                    data_list.append(data)
+        elif sys.platform.startswith('win'):
+            if model != "FuzzyModel" or corp[0] != "cord19\\trec-covid\\round1":
+                temp = path.removesuffix("\src") + f'\ddb_storage\{model}\{corp[0]}'
+                path_list.append(temp)
+
+                with open(temp + "\k_Rank.json") as json_file:
+                    data = json.load(json_file)
+                    data_list.append(data)    
+    plot_eval_meassures(data_list, path_list, [corpus[0][1], corpus[1][1], corpus[2][1]])        
+
+# path1 = path + f'/ddb_storage/VectorModel/{corpus[0][0]}'
+
+# with open(path1 + "/k_Rank.json") as json_file:
+#     data1 = json.load(json_file)
+
+# path2 = path + f'/ddb_storage/VectorModel/{corpus[1][0]}'
+
+# with open(path2 + "/k_Rank.json") as json_file:
+#     data2 = json.load(json_file)
+
+# path3 = path + f'/ddb_storage/VectorModel/{corpus[2][0]}'
+
+# with open(path3 + "/k_Rank.json") as json_file:
+#     data3 = json.load(json_file)
+
+# plot_eval_meassures([data1, data2, data3], [path1, path2, path3], [corpus[0][1], corpus[1][1], corpus[2][1]])