better correlation calculation

cov.py

@@ -1,5 +1,6 @@
 import numpy as np
 from matplotlib import pyplot as plt
+from matplotlib.axes import Axes
 
 from simulation_list import SimulationList
 
@@ -7,8 +8,9 @@ simulations = SimulationList.jsonlines_load()
 np.set_printoptions(linewidth=1000, edgeitems=4)
 
 x = simulations.as_matrix
-labels = ["$M$", "$wp$", "$wt$", "$\\gamma$", "$\\alpha$", "$v$", "water"]
-x[::, 0] = 10 ** x[::, 0]
+labels = ["impact angle $\\alpha$", " collision speed $v$", "projectile mass", "mass fraction $\\gamma$",
+          "target water fraction", "projectile water fraction"]
+matrixlabels = labels + ["water retention"]
 
 print(x)
 print(x.shape)
@@ -18,18 +20,27 @@ X = np.copy(x)
 X -= X.mean(axis=0)
 manual = np.dot(X.T, X.conj()) / (x.shape[0] - 1)
 assert np.allclose(manual, np.cov(x.T))
-print(corr)
+print(corr.shape)
 simple_cov = corr[-1, :-1]
 # plot correclation matrix
 plt.matshow(corr)
-plt.xticks(range(len(labels)), labels, rotation=90)
-plt.yticks(range(len(labels)), labels)
-plt.colorbar()
-plt.savefig("correlation.pdf",transparent=True)
-plt.show()
-# plt.close()
-plt.bar(range(len(simple_cov)), simple_cov)
+# plt.xticks(range(len(matrixlabels)), matrixlabels, rotation=90)
+# plt.yticks(range(len(matrixlabels)), matrixlabels)
+# plt.colorbar()
+# plt.savefig("correlation.pdf", transparent=True)
+# plt.tight_layout()
+# plt.show()
+plt.close()
+
+ax = plt.gca()  # type:Axes
+print(len(labels), len(simple_cov))
+print(simple_cov)
+plt.barh(range(len(simple_cov)), simple_cov)
 # ax.set_xticks(index + bar_width / 2)
-ax = plt.gca()
-ax.set_xticklabels(labels)
+ax.set_yticklabels([0] + labels)
+ax2 = ax.twinx()  # type:Axes
+ax2.set_yticklabels([0] + ["{:.2f}".format(a) for a in simple_cov])
+ax2.set_ylim(ax.get_ylim())
+plt.tight_layout()
+plt.savefig("../arbeit/images/cov.pdf")
 plt.show()