/usr/share/pyshared/guiqwt/tests/image.py is in python-guiqwt 2.1.6-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 | # -*- coding: utf-8 -*-
#
# Copyright © 2009-2010 CEA
# Pierre Raybaut
# Licensed under the terms of the CECILL License
# (see guiqwt/__init__.py for details)
"""ImageDialog test"""
#FIXME: unexpected behavior when changing the xmin/xmax/ymin/ymax values in
# the image parameters (2nd tab: "Axes")
SHOW = True # Show test in GUI-based test launcher
import numpy as np
from guiqwt.plot import ImageDialog
from guiqwt.builder import make
def imshow( data ):
win = ImageDialog(edit=False, toolbar=True, wintitle="ImageDialog test",
options=dict(xlabel='Concentration', xunit='ppm'))
item = make.image(data)
plot = win.get_plot()
plot.add_item(item)
win.show()
win.exec_()
def compute_image(N=2000, grid=True):
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
np.cos(img, img) # inplace cosine
if not grid:
return 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 )
print img.dtype
return img
def compute_image_2():
N = 1000
T = np.uint16
TMAX = 32000
TMIN = 32000
S=5.
x = np.array(np.linspace(-5*S, 5*S, N), float)
img = np.zeros( (N, N), T )
x.shape = (1, N)
img += x**2
x.shape = (N, 1)
img += x**2
img = TMAX*np.cos(img/S)+TMIN
x.shape = (N,)
# dx = dy = x[1]-x[0]
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] = TMAX*m1+TMIN # (0,0)
img[:K, -K:] = TMAX*m2+TMIN # (0,N)
img[-K:, -K:] = TMAX*m3+TMIN # (N,N)
img[-K:, :K] = TMAX*m4+TMIN # (N,0)
#img = array( 30000*(img+1.1), uint16 )
return img
def compute_image_3():
"""Produces horizontal and vertical ramps"""
N = 1000
NK = 20
T = float
img = np.zeros( (N,N), T )
x = np.arange(N, dtype=float)
x.shape = (1,N)
DK = N/NK
for i in range(NK):
S = i+1
y = S*(x//S)
img[DK*i:DK*(i+1),:] = y
return img
def test():
"""Test"""
# -- Create QApplication
import guidata
_app = guidata.qapplication()
# --
imshow(compute_image())
if __name__ == "__main__":
test()
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