import pyqtgraph as pg
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_almost_equal
import pytest
np.random.seed(12345)
def testSolve3D():
p1 = np.array([[0,0,0,1],
[1,0,0,1],
[0,1,0,1],
[0,0,1,1]], dtype=float)
# transform points through random matrix
tr = np.random.normal(size=(4, 4))
tr[3] = (0,0,0,1)
p2 = np.dot(tr, p1.T).T[:,:3]
# solve to see if we can recover the transformation matrix.
tr2 = pg.solve3DTransform(p1, p2)
assert_array_almost_equal(tr[:3], tr2[:3])
def test_interpolateArray():
def interpolateArray(data, x):
result = pg.interpolateArray(data, x)
assert result.shape == x.shape[:-1] + data.shape[x.shape[-1]:]
return result
data = np.array([[ 1., 2., 4. ],
[ 10., 20., 40. ],
[ 100., 200., 400.]])
# test various x shapes
interpolateArray(data, np.ones((1,)))
interpolateArray(data, np.ones((2,)))
interpolateArray(data, np.ones((1, 1)))
interpolateArray(data, np.ones((1, 2)))
interpolateArray(data, np.ones((5, 1)))
interpolateArray(data, np.ones((5, 2)))
interpolateArray(data, np.ones((5, 5, 1)))
interpolateArray(data, np.ones((5, 5, 2)))
with pytest.raises(TypeError):
interpolateArray(data, np.ones((3,)))
with pytest.raises(TypeError):
interpolateArray(data, np.ones((1, 3,)))
with pytest.raises(TypeError):
interpolateArray(data, np.ones((5, 5, 3,)))
x = np.array([[ 0.3, 0.6],
[ 1. , 1. ],
[ 0.5, 1. ],
[ 0.5, 2.5],
[ 10. , 10. ]])
result = interpolateArray(data, x)
#import scipy.ndimage
#spresult = scipy.ndimage.map_coordinates(data, x.T, order=1)
spresult = np.array([ 5.92, 20. , 11. , 0. , 0. ]) # generated with the above line
assert_array_almost_equal(result, spresult)
# test mapping when x.shape[-1] < data.ndim
x = np.array([[ 0.3, 0],
[ 0.3, 1],
[ 0.3, 2]])
r1 = interpolateArray(data, x)
x = np.array([0.3]) # should broadcast across axis 1
r2 = interpolateArray(data, x)
assert_array_almost_equal(r1, r2)
# test mapping 2D array of locations
x = np.array([[[0.5, 0.5], [0.5, 1.0], [0.5, 1.5]],
[[1.5, 0.5], [1.5, 1.0], [1.5, 1.5]]])
r1 = interpolateArray(data, x)
#r2 = scipy.ndimage.map_coordinates(data, x.transpose(2,0,1), order=1)
r2 = np.array([[ 8.25, 11. , 16.5 ], # generated with the above line
[ 82.5 , 110. , 165. ]])
assert_array_almost_equal(r1, r2)
# test interpolate where data.ndim > x.shape[1]
data = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]) # 2x2x3
x = np.array([[1, 1], [0, 0.5], [5, 5]])
r1 = interpolateArray(data, x)
assert np.all(r1[0] == data[1, 1])
assert np.all(r1[1] == 0.5 * (data[0, 0] + data[0, 1]))
assert np.all(r1[2] == 0)
def test_subArray():
a = np.array([0, 0, 111, 112, 113, 0, 121, 122, 123, 0, 0, 0, 211, 212, 213, 0, 221, 222, 223, 0, 0, 0, 0])
b = pg.subArray(a, offset=2, shape=(2,2,3), stride=(10,4,1))
c = np.array([[[111,112,113], [121,122,123]], [[211,212,213], [221,222,223]]])
assert np.all(b == c)
# operate over first axis; broadcast over the rest
aa = np.vstack([a, a/100.]).T
cc = np.empty(c.shape + (2,))
cc[..., 0] = c
cc[..., 1] = c / 100.
bb = pg.subArray(aa, offset=2, shape=(2,2,3), stride=(10,4,1))
assert np.all(bb == cc)
def test_rescaleData():
dtypes = map(np.dtype, ('ubyte', 'uint16', 'byte', 'int16', 'int', 'float'))
for dtype1 in dtypes:
for dtype2 in dtypes:
data = (np.random.random(size=10) * 2**32 - 2**31).astype(dtype1)
for scale, offset in [(10, 0), (10., 0.), (1, -50), (0.2, 0.5), (0.001, 0)]:
if dtype2.kind in 'iu':
lim = np.iinfo(dtype2)
lim = lim.min, lim.max
else:
lim = (-np.inf, np.inf)
s1 = np.clip(float(scale) * (data-float(offset)), *lim).astype(dtype2)
s2 = pg.rescaleData(data, scale, offset, dtype2)
assert s1.dtype == s2.dtype
if dtype2.kind in 'iu':
assert np.all(s1 == s2)
else:
assert np.allclose(s1, s2)
def test_makeARGB():
# Many parameters to test here:
# * data dtype (ubyte, uint16, float, others)
# * data ndim (2 or 3)
# * levels (None, 1D, or 2D)
# * lut dtype
# * lut size
# * lut ndim (1 or 2)
# * useRGBA argument
# Need to check that all input values map to the correct output values, especially
# at and beyond the edges of the level range.
def checkArrays(a, b):
# because py.test output is difficult to read for arrays
if not np.all(a == b):
comp = []
for i in range(a.shape[0]):
if a.shape[1] > 1:
comp.append('[')
for j in range(a.shape[1]):
m = a[i,j] == b[i,j]
comp.append('%d,%d %s %s %s%s' %
(i, j, str(a[i,j]).ljust(15), str(b[i,j]).ljust(15),
m, ' ********' if not np.all(m) else ''))
if a.shape[1] > 1:
comp.append(']')
raise Exception("arrays do not match:\n%s" % '\n'.join(comp))
def checkImage(img, check, alpha, alphaCheck):
assert img.dtype == np.ubyte
assert alpha is alphaCheck
if alpha is False:
checkArrays(img[..., 3], 255)
if np.isscalar(check) or check.ndim == 3:
checkArrays(img[..., :3], check)
elif check.ndim == 2:
checkArrays(img[..., :3], check[..., np.newaxis])
elif check.ndim == 1:
checkArrays(img[..., :3], check[..., np.newaxis, np.newaxis])
else:
raise Exception('invalid check array ndim')
# uint8 data tests
im1 = np.arange(256).astype('ubyte').reshape(256, 1)
im2, alpha = pg.makeARGB(im1, levels=(0, 255))
checkImage(im2, im1, alpha, False)
im3, alpha = pg.makeARGB(im1, levels=(0.0, 255.0))
checkImage(im3, im1, alpha, False)
im4, alpha = pg.makeARGB(im1, levels=(255, 0))
checkImage(im4, 255-im1, alpha, False)
im5, alpha = pg.makeARGB(np.concatenate([im1]*3, axis=1), levels=[(0, 255), (0.0, 255.0), (255, 0)])
checkImage(im5, np.concatenate([im1, im1, 255-im1], axis=1), alpha, False)
im2, alpha = pg.makeARGB(im1, levels=(128,383))
checkImage(im2[:128], 0, alpha, False)
checkImage(im2[128:], im1[:128], alpha, False)
# uint8 data + uint8 LUT
lut = np.arange(256)[::-1].astype(np.uint8)
im2, alpha = pg.makeARGB(im1, lut=lut)
checkImage(im2, lut, alpha, False)
# lut larger than maxint
lut = np.arange(511).astype(np.uint8)
im2, alpha = pg.makeARGB(im1, lut=lut)
checkImage(im2, lut[::2], alpha, False)
# lut smaller than maxint
lut = np.arange(128).astype(np.uint8)
im2, alpha = pg.makeARGB(im1, lut=lut)
checkImage(im2, np.linspace(0, 127, 256).astype('ubyte'), alpha, False)
# lut + levels
lut = np.arange(256)[::-1].astype(np.uint8)
im2, alpha = pg.makeARGB(im1, lut=lut, levels=[-128, 384])
checkImage(im2, np.linspace(192, 65.5, 256).astype('ubyte'), alpha, False)
im2, alpha = pg.makeARGB(im1, lut=lut, levels=[64, 192])
checkImage(im2, np.clip(np.linspace(385.5, -126.5, 256), 0, 255).astype('ubyte'), alpha, False)
# uint8 data + uint16 LUT
lut = np.arange(4096)[::-1].astype(np.uint16) // 16
im2, alpha = pg.makeARGB(im1, lut=lut)
checkImage(im2, np.arange(256)[::-1].astype('ubyte'), alpha, False)
# uint8 data + float LUT
lut = np.linspace(10., 137., 256)
im2, alpha = pg.makeARGB(im1, lut=lut)
checkImage(im2, lut.astype('ubyte'), alpha, False)
# uint8 data + 2D LUT
lut = np.zeros((256, 3), dtype='ubyte')
lut[:,0] = np.arange(256)
lut[:,1] = np.arange(256)[::-1]
lut[:,2] = 7
im2, alpha = pg.makeARGB(im1, lut=lut)
checkImage(im2, lut[:,None,::-1], alpha, False)
# check useRGBA
im2, alpha = pg.makeARGB(im1, lut=lut, useRGBA=True)
checkImage(im2, lut[:,None,:], alpha, False)
# uint16 data tests
im1 = np.arange(0, 2**16, 256).astype('uint16')[:, None]
im2, alpha = pg.makeARGB(im1, levels=(512, 2**16))
checkImage(im2, np.clip(np.linspace(-2, 253, 256), 0, 255).astype('ubyte'), alpha, False)
lut = (np.arange(512, 2**16)[::-1] // 256).astype('ubyte')
im2, alpha = pg.makeARGB(im1, lut=lut, levels=(512, 2**16-256))
checkImage(im2, np.clip(np.linspace(257, 2, 256), 0, 255).astype('ubyte'), alpha, False)
lut = np.zeros(2**16, dtype='ubyte')
lut[1000:1256] = np.arange(256)
lut[1256:] = 255
im1 = np.arange(1000, 1256).astype('uint16')[:, None]
im2, alpha = pg.makeARGB(im1, lut=lut)
checkImage(im2, np.arange(256).astype('ubyte'), alpha, False)
# float data tests
im1 = np.linspace(1.0, 17.0, 256)[:, None]
im2, alpha = pg.makeARGB(im1, levels=(5.0, 13.0))
checkImage(im2, np.clip(np.linspace(-128, 383, 256), 0, 255).astype('ubyte'), alpha, False)
lut = (np.arange(1280)[::-1] // 10).astype('ubyte')
im2, alpha = pg.makeARGB(im1, lut=lut, levels=(1, 17))
checkImage(im2, np.linspace(127.5, 0, 256).astype('ubyte'), alpha, False)
# test sanity checks
class AssertExc(object):
def __init__(self, exc=Exception):
self.exc = exc
def __enter__(self):
return self
def __exit__(self, *args):
assert args[0] is self.exc, "Should have raised %s (got %s)" % (self.exc, args[0])
return True
with AssertExc(TypeError): # invalid image shape
pg.makeARGB(np.zeros((2,), dtype='float'))
with AssertExc(TypeError): # invalid image shape
pg.makeARGB(np.zeros((2,2,7), dtype='float'))
with AssertExc(): # float images require levels arg
pg.makeARGB(np.zeros((2,2), dtype='float'))
with AssertExc(): # bad levels arg
pg.makeARGB(np.zeros((2,2), dtype='float'), levels=[1])
with AssertExc(): # bad levels arg
pg.makeARGB(np.zeros((2,2), dtype='float'), levels=[1,2,3])
with AssertExc(): # can't mix 3-channel levels and LUT
pg.makeARGB(np.zeros((2,2)), lut=np.zeros((10,3), dtype='ubyte'), levels=[(0,1)]*3)
with AssertExc(): # multichannel levels must have same number of channels as image
pg.makeARGB(np.zeros((2,2,3), dtype='float'), levels=[(1,2)]*4)
with AssertExc(): # 3d levels not allowed
pg.makeARGB(np.zeros((2,2,3), dtype='float'), levels=np.zeros([3, 2, 2]))
if __name__ == '__main__':
test_interpolateArray()
