+import numpy as np
+import matplotlib.pyplot as plt
+IMAGEDIR = "report/pics/"
+
+def generateHistograms(X, header):
+ global IMAGEDIR
+ for i, c in enumerate(X.T):
+ plt.hist(c)
+ plt.savefig(IMAGEDIR + header[i] + "-hist.pdf")
+ plt.clf()
+
+def generateScatterPlot(X, Y, header):
+ global IMAGEDIR
+ for i, feature in enumerate(X.T):
+ values = np.unique(feature)
+ values = np.sort(values)
+ geomean = []
+ for value in values:
+ a =Y[np.where(feature == value)]
+ a = np.array(map(lambda x : x**(1.0/len(a)), a))
+ geomean.append(a.prod())
+ plt.plot(feature, Y, 'r.')
+ for ii in range(0, len(geomean)-1):
+ print(values[ii:ii + 2])
+ print(geomean[ii:ii + 2])
+ plt.plot(values[ii:ii + 2], geomean[ii:ii + 2], 'bo-')
+ plt.savefig(IMAGEDIR + header[i] + "-scat.pdf")
+ plt.clf()
+
+def plot(data, header):
+ global IMAGEDIR
+ header=header[6:-1]
+ data = np.array(data)
+ X = data[:, 6:-4]
+ X[X==''] = '-1'
+ X = X.astype(np.float)
+ Y = data[:, -2]
+ Y = Y.astype(np.float)
+ generateHistograms(X, header)
+ generateScatterPlot(X, Y, header)
+
+
+
+