Source code for pysptools.util.display

#
#------------------------------------------------------------------------------
# Copyright (c) 2013-2014, Christian Therien
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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#    http://www.apache.org/licenses/LICENSE-2.0
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#
# display.py - This file is part of the PySptools package.
#

import os.path as osp
import numpy as np
import matplotlib.pyplot as plt


[docs]def plot_linear_stretch(M, path, R, G, B, suffix=None): """ Plot a linear stretched RGB image. Parameters: M: `numpy array` A HSI cube (m x n x p). path: `string` The path where to put the plot. R: `int` A band number that will render the red color. G: `int` A band number that will render the green color. B: `int` A band number that will render the blue color. suffix: `string [default None]` Add a suffix to the file name. """ img = _linear_stretch(M, R, G, B) plt.ioff() if suffix == None: fout = osp.join(path, 'linear_stretch.png') else: fout = osp.join(path, 'linear_stretch_{0}.png'.format(suffix)) plt.imsave(fout, img) plt.close()
[docs]def display_linear_stretch(M, R, G, B, suffix=None): """ Display a linear stretched RGB image. Parameters: M: `numpy array` A HSI cube (m x n x p). R: `int` A band number that will render the red color. G: `int` A band number that will render the green color. B: `int` A band number that will render the blue color. suffix: `string [default None]` Add a suffix to the title. """ img = _linear_stretch(M, R, G, B) plt.imshow(img, interpolation='none') if suffix == None: plt.title('Linear Stretch') else: plt.title('Linear Stretch - {0}'.format(suffix)) plt.show() plt.close()
def _linear_stretch(data, R, G, B): """ Do a linear stretch. """ img = np.zeros((data.shape[0],data.shape[1],3), dtype=np.float) for i in range(data.shape[0]): for j in range(data.shape[1]): img[i,j] = data[i,j,R], data[i,j,G], data[i,j,B] d_R = np.max(img[:,:,0])-np.min(img[:,:,0]) min_R = np.min(img[:,:,0]) d_G = np.max(img[:,:,1])-np.min(img[:,:,1]) min_G = np.min(img[:,:,1]) d_B = np.max(img[:,:,2])-np.min(img[:,:,2]) min_B = np.min(img[:,:,2]) img1 = np.zeros((data.shape[0],data.shape[1],3), dtype=np.int8) for i in range(data.shape[0]): for j in range(data.shape[1]): img1[i,j] = (1-((img[i,j,0]-min_R)/d_R))*255, (1-((img[i,j,1]-min_G)/d_G))*255, (1-((img[i,j,2]-min_B)/d_B))*255 return img1 if __name__ == '__main__': import os.path as osp import pysptools.util as util data_path = '../data1' project_path = '../' result_path = osp.join(project_path, 'results') sample = '92AV3C.hdr' data_file = osp.join(data_path, sample) data, info = util.load_ENVI_file(data_file) plot_linear_stretch(data, result_path, 102, 85, 18, '1') plot_linear_stretch(data, result_path, 98, 86, 22, '2') plot_linear_stretch(data, result_path, 75, 34, 0, '3') plot_linear_stretch(data, result_path, 74, 46, 18, '4')