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# -*- coding: utf-8 -*-
#
# Copyright © 2009-2010 CEA
# Pierre Raybaut
# Licensed under the terms of the CECILL License
# (see guiqwt/__init__.py for details)

"""Image with custom X/Y axes linear scales"""

SHOW = True # Show test in GUI-based test launcher

from guiqwt.plot import ImageDialog
from guiqwt.builder import make

import numpy as np

def imshow( x, y, data ):
    win = ImageDialog(edit=False, toolbar=True,
                      wintitle="Image with custom X/Y axes scales",
                      options=dict(xlabel="x (a.u.)", ylabel="y (a.u.)",
                                   yreverse=False))
    item = make.xyimage(x, y, data)
    plot = win.get_plot()
    plot.add_item(item)
    win.show()
    win.exec_()

def compute_image():
    N = 2000
    T = np.float32
    x = np.array(np.linspace(-5, 5, N), T)
    img = np.zeros( (N, N), T )
    x.shape = (1, N)
    img += x**2
    x.shape = (N, 1)
    img += x**2
    img = np.cos(img)
    x.shape = (N,)
    for k in range( -5, 5 ):
        i = x.searchsorted(k)
        if k < 0 :
            v = -1.1
        else:
            v = 1.1
        img[i, :] = v
        img[:, i] = v
    m1, m2, m3, m4 = -1.1, -0.3, 0.3, 1.1
    K = 100
    img[:K, :K] = m1     # (0,0)
    img[:K, -K:] = m2    # (0,N)
    img[-K:, -K:] = m3   # (N,N)
    img[-K:, :K] = m4    # (N,0)
    #img = array( 30000*(img+1.1), uint16 )
    img = img + np.random.normal(0., 0.05, size=(N,N))
    print img.dtype
    return x, (x+5)**0.6, img

def test():
    """Test"""
    # -- Create QApplication
    import guidata
    _app = guidata.qapplication()
    # --    
    imshow(*compute_image())

if __name__ == "__main__":
    test()