import numpy as np
from matplotlib import pyplot as plt
import matplotlib as mpl
import glob
def create_4_colorMap():
#colors= ['blue','cyan','green','pink','magenta','purple','gold','red']
colors= ['gray','yellow','orange','red']
discmap = mpl.colors.ListedColormap(colors)
return discmap
def create_8_colorMap():
#colors= ['blue','cyan','green','pink','magenta','purple','gold','red']
colors= ['blue','green','pink','magenta','orange','yellow','red', 'black']
discmap = mpl.colors.ListedColormap(colors)
return discmap
dismap_4 = create_4_colorMap()
npyRows = 128
npyCols = 128
plt.figure(figsize=(npyRows, npyCols), dpi=1)
plt_img=plt.imshow(np.random.rand(npyRows, npyCols), vmin=0, vmax=9, cmap=dismap_4, aspect="auto")
plt.axis('off')
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.subplots_adjust(top=1, bottom=0, right=1, left=0)
plt.margins(0,0)
#plt.colorbar()
def showNpy2dFacies(npy2dFile):
dat = np.load(npy2dFile)
print(npy2dFile)
#print(dat.shape)
plt.imshow(dat,vmin=0, vmax=3, cmap=dismap_4)
plt.savefig(npy2dFile.replace('.npy','.png'))
#plt.show()
#plt.close()
def showNpy2dSeis(npy2dFile):
dat = np.load(npy2dFile)
print(npy2dFile)
#print(dat.shape)
plt.imshow(dat, cmap='seismic')
plt.savefig(npy2dFile.replace('.npy','.png'))
#plt.show()
#plt.clf()
def showNpyFaciesBatch():
for i in range(1,1420):
npyFile="samples/facies_{0}.npy".format(i)
showNpy2dFacies(npyFile)
def showNpySeisBatch():
for i in range(750,1420):
npyFile="samples/seismic_{0}.npy".format(i)
showNpy2dSeis(npyFile)
if __name__ == "__main__":
#showNpyFaciesBatch()
showNpySeisBatch()