import glob

import h5py

import numpy as np

from matplotlib import pyplot as plt

import sys,os

from scipy.ndimage.morphology import grey_opening

import scipy as sp

flist = glob.glob('/home/rjonnal/data/Dropbox/Share/2g_aooct_data/Data/2016.04.12_2/*.hdf5')

for f in flist:

h5 = h5py.File(f)

offset_matrix = h5['model/z_offsets'][:]

goodness_matrix = h5['model/z_offset_goodness'][:]

om = offset_matrix[0,:,:]

oms = grey_opening(om,(1,15))

mode = sp.stats.mode(oms.ravel())[0][0]

mask = np.zeros(oms.shape)

lower_threshold = np.mean(oms)-2.0*np.std(oms)

upper_threshold = np.mean(oms)+2.0*np.std(oms)

cond = np.logical_and(foffset_matrix>lower_threshold,foffset_matrix<upper_threshold)

mask[np.where(cond)] = 1

plt.figure(figsize=(18,6))

clim = np.min(om),np.max(om)

plt.subplot(131)

plt.imshow(om,interpolation='none',clim=clim,cmap='gray')

plt.colorbar()

plt.subplot(132)

plt.imshow(oms,interpolation='none',clim=clim,cmap='gray')

plt.colorbar()

plt.subplot(133)

plt.imshow(om-oms,interpolation='none')

plt.colorbar()

plt.show()