R6289/plot_for_lamda_and_gamma.py
bc84d2395356workstation

plot_for_lamda_and_gamma.py
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			from matplotlib import pyplot as plt
			from mpl_toolkits.mplot3d import Axes3D
			import numpy as np

			fig1 = plt.figure(1)
			fig2 = plt.figure(2)
			ax = fig2.add_subplot(111, projection='3d')

			#for g in [900,1000,1100,1200]:
			for g in [10,100,1000]:
			#for l in [90,100,110,120]:
			for l in [100,1000,10000]:
			plt.figure(1)
			cY = np.loadtxt('/home/aymanns//Data_R57C10s/4_170609_fly1_001/results/l{}g{}/cY_Out2.dat'.format(l,g))
			plt.plot(cY,label='l={}, g={}'.format(l,g))
			#plt.figure(2)
			ng = np.loadtxt('/home/aymanns//Data_R57C10s/4_170609_fly1_001/results/l{}g{}/ng_Out2.dat'.format(l,g))
			ax.scatter(g,l,ng)
			ax.text(g,l,ng, str(ng))

			plt.figure(1)
			plt.legend()
			plt.xlabel('frames')
			plt.ylabel('correlation with mean')
			plt.savefig('correlation.pdf')
			plt.show()

			plt.figure(2)
			plt.xlabel('gamma')
			plt.ylabel('lambda')
			ax.set_zlabel('gradient of mean')
			plt.savefig('gradient.pdf')
			plt.show()