def test_cythonSP_vs_fit2d(self):
"""
Compare cython splitPixel with results of fit2d
"""
logger.info(self.ai.__repr__())
pos = self.ai.cornerArray(self.data.shape)
t0 = time.time()
logger.info("in test_cythonSP_vs_fit2d Before SP")
tth, I = self.ai.xrpd_splitPixel(self.data,
len(self.fit2d),
self.tmpfiles["cythonSP"],
correctSolidAngle=False)
logger.info("in test_cythonSP_vs_fit2d Before")
t1 = time.time() - t0
# logger.info(tth)
# logger.info(I)
rwp = Rwp((tth, I), self.fit2d.T)
logger.info("Rwp cythonSP(t=%.3fs)/fit2d = %.3f" % (t1, rwp))
if logger.getEffectiveLevel() == logging.DEBUG:
logger.info("Plotting results")
fig = pylab.figure()
fig.suptitle('CythonSP Histogram vs Fit2D: Rwp=%.3f' % rwp)
sp = fig.add_subplot(111)
sp.plot(self.fit2d.T[0], self.fit2d.T[1], "-b", label='fit2d')
sp.plot(tth, I, "-r", label="cython")
handles, labels = sp.get_legend_handles_labels()
fig.legend(handles, labels)
fig.show()
input("Press enter to quit")
assert rwp < 11
def test_cython_vs_numpy(self):
"""
Compare cython histogram with numpy histogram
"""
# logger.info(self.ai.__repr__())
data = self.data
tth_np, I_np = self.ai.xrpd_numpy(data,
len(self.fit2d),
correctSolidAngle=False)
tth_cy, I_cy = self.ai.xrpd_cython(data,
len(self.fit2d),
correctSolidAngle=False)
logger.info("before xrpd_splitPixel")
tth_sp, I_sp = self.ai.xrpd_splitPixel(data,
len(self.fit2d),
correctSolidAngle=False)
logger.info("After xrpd_splitPixel")
rwp = Rwp((tth_cy, I_cy), (tth_np, I_np))
logger.info("Rwp = %.3f" % rwp)
if logger.getEffectiveLevel() == logging.DEBUG:
logging.info("Plotting results")
fig = pylab.figure()
fig.suptitle('Numpy Histogram vs Cython: Rwp=%.3f' % rwp)
sp = fig.add_subplot(111)
sp.plot(self.fit2d.T[0], self.fit2d.T[1], "-y", label='fit2d')
sp.plot(tth_np, I_np, "-b", label='numpy')
sp.plot(tth_cy, I_cy , "-r", label="cython")
sp.plot(tth_sp, I_sp , "-g", label="SplitPixel")
handles, labels = sp.get_legend_handles_labels()
fig.legend(handles, labels)
fig.show()
input("Press enter to quit")
assert rwp < 3
def test_cython_vs_numpy(self):
"""
Compare cython histogram with numpy histogram
"""
# logger.info(self.ai.__repr__())
data = self.data
tth_np, I_np = self.ai.xrpd_numpy(data,
len(self.fit2d),
correctSolidAngle=False)
tth_cy, I_cy = self.ai.xrpd_cython(data,
len(self.fit2d),
correctSolidAngle=False)
logger.info("before xrpd_splitPixel")
tth_sp, I_sp = self.ai.xrpd_splitPixel(data,
len(self.fit2d),
correctSolidAngle=False)
logger.info("After xrpd_splitPixel")
rwp = Rwp((tth_cy, I_cy), (tth_np, I_np))
logger.info("Rwp = %.3f" % rwp)
if logger.getEffectiveLevel() == logging.DEBUG:
logging.info("Plotting results")
fig = pylab.figure()
fig.suptitle('Numpy Histogram vs Cython: Rwp=%.3f' % rwp)
sp = fig.add_subplot(111)
sp.plot(self.fit2d.T[0], self.fit2d.T[1], "-y", label='fit2d')
sp.plot(tth_np, I_np, "-b", label='numpy')
sp.plot(tth_cy, I_cy, "-r", label="cython")
sp.plot(tth_sp, I_sp, "-g", label="SplitPixel")
handles, labels = sp.get_legend_handles_labels()
fig.legend(handles, labels)
fig.show()
input("Press enter to quit")
assert rwp < 3
def test_cython_vs_fit2d(self):
"""
Compare cython histogram with results of fit2d
"""
# logger.info(self.ai.__repr__())
tth, I = self.ai.xrpd_cython(self.data,
len(self.fit2d),
self.tmpfiles["cython"],
correctSolidAngle=False,
pixelSize=None)
# logger.info(tth)
# logger.info(I)
rwp = Rwp((tth, I), self.fit2d.T)
logger.info("Rwp cython/fit2d = %.3f" % rwp)
if logger.getEffectiveLevel() == logging.DEBUG:
logger.info("Plotting results")
fig = pylab.figure()
fig.suptitle('Cython Histogram vs Fit2D: Rwp=%.3f' % rwp)
sp = fig.add_subplot(111)
sp.plot(self.fit2d.T[0], self.fit2d.T[1], "-b", label='fit2d')
sp.plot(tth, I, "-r", label="cython")
handles, labels = sp.get_legend_handles_labels()
fig.legend(handles, labels)
fig.show()
input("Press enter to quit")
assert rwp < 11
def test_cythonSP_vs_fit2d(self):
"""
Compare cython splitPixel with results of fit2d
"""
logger.info(self.ai.__repr__())
pos = self.ai.cornerArray(self.data.shape)
t0 = time.time()
logger.info("in test_cythonSP_vs_fit2d Before SP")
tth, I = self.ai.xrpd_splitPixel(self.data,
len(self.fit2d),
self.tmpfiles["cythonSP"],
correctSolidAngle=False)
logger.info("in test_cythonSP_vs_fit2d Before")
t1 = time.time() - t0
# logger.info(tth)
# logger.info(I)
rwp = Rwp((tth, I), self.fit2d.T)
logger.info("Rwp cythonSP(t=%.3fs)/fit2d = %.3f" % (t1, rwp))
if logger.getEffectiveLevel() == logging.DEBUG:
logger.info("Plotting results")
fig = pylab.figure()
fig.suptitle('CythonSP Histogram vs Fit2D: Rwp=%.3f' % rwp)
sp = fig.add_subplot(111)
sp.plot(self.fit2d.T[0], self.fit2d.T[1], "-b", label='fit2d')
sp.plot(tth, I, "-r", label="cython")
handles, labels = sp.get_legend_handles_labels()
fig.legend(handles, labels)
fig.show()
input("Press enter to quit")
assert rwp < 11
def diff_img(ref, obt, comment=""):
"""
Highlight the difference in images
"""
assert ref.shape == obt.shape
delta = abs(obt - ref)
if delta.max() > 0:
from pyFAI.gui_utils import pyplot as plt
fig = plt.figure()
ax1 = fig.add_subplot(2, 2, 1)
ax2 = fig.add_subplot(2, 2, 2)
ax3 = fig.add_subplot(2, 2, 3)
im_ref = ax1.imshow(ref)
plt.colorbar(im_ref)
ax1.set_title("%s ref" % comment)
im_obt = ax2.imshow(obt)
plt.colorbar(im_obt)
ax2.set_title("%s obt" % comment)
im_delta = ax3.imshow(delta)
plt.colorbar(im_delta)
ax3.set_title("delta")
imax = delta.argmax()
x = imax % ref.shape[-1]
y = imax // ref.shape[-1]
ax3.plot([x], [y], "o", scalex=False, scaley=False)
fig.show()
from pyFAI.utils import input
input()
def diff_img(ref, obt, comment=""):
"""
Highlight the difference in images
"""
assert ref.shape == obt.shape
delta = abs(obt - ref)
if delta.max() > 0:
from pyFAI.gui_utils import pyplot as plt
fig = plt.figure()
ax1 = fig.add_subplot(2, 2, 1)
ax2 = fig.add_subplot(2, 2, 2)
ax3 = fig.add_subplot(2, 2, 3)
im_ref = ax1.imshow(ref)
plt.colorbar(im_ref)
ax1.set_title("%s ref" % comment)
im_obt = ax2.imshow(obt)
plt.colorbar(im_obt)
ax2.set_title("%s obt" % comment)
im_delta = ax3.imshow(delta)
plt.colorbar(im_delta)
ax3.set_title("delta")
imax = delta.argmax()
x = imax % ref.shape[-1]
y = imax // ref.shape[-1]
ax3.plot([x], [y], "o", scalex=False, scaley=False)
fig.show()
from pyFAI.utils import input
input()
def test_splitBBox(self):
data = numpy.ones((2000, 2000), dtype="float64")
ai = AzimuthalIntegrator(0.1, 1e-2, 1e-2, pixel1=1e-5, pixel2=1e-5)
I = ai.xrpd2_splitBBox(data, 2048, 2048, correctSolidAngle=False, dummy=-1.0)[0]
# I = ai.xrpd2(data, 2048, 2048, correctSolidAngle=False, dummy= -1.0)
if logger.getEffectiveLevel() == logging.DEBUG:
logging.info("Plotting results")
fig = pylab.figure()
fig.suptitle('cacking of a flat image: SplitBBox')
sp = fig.add_subplot(111)
sp.imshow(I, interpolation="nearest")
fig.show()
input("Press enter to quit")
I[I == -1.0] = 1.0
assert abs(I.min() - 1.0) < self.epsilon
assert abs(I.max() - 1.0) < self.epsilon
def diff_crv(ref, obt, comment=""):
"""
Highlight the difference in vectors
"""
assert ref.shape == obt.shape
delta = abs(obt - ref)
if delta.max() > 0:
from pyFAI.gui_utils import pyplot as plt
fig = plt.figure()
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(1, 2, 2)
im_ref = ax1.plot(ref, label="%s ref" % comment)
im_obt = ax1.plot(obt, label="%s obt" % comment)
im_delta = ax2.plot(delta, label="delta")
fig.show()
from pyFAI.utils import input
input()
def diff_crv(ref, obt, comment=""):
"""
Highlight the difference in vectors
"""
assert ref.shape == obt.shape
delta = abs(obt - ref)
if delta.max() > 0:
from pyFAI.gui_utils import pyplot as plt
fig = plt.figure()
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(1, 2, 2)
im_ref = ax1.plot(ref, label="%s ref" % comment)
im_obt = ax1.plot(obt, label="%s obt" % comment)
im_delta = ax2.plot(delta, label="delta")
fig.show()
from pyFAI.utils import input
input()
def test_splitBBox(self):
data = numpy.ones((2000, 2000), dtype="float64")
ai = AzimuthalIntegrator(0.1, 1e-2, 1e-2, pixel1=1e-5, pixel2=1e-5)
I = ai.xrpd2_splitBBox(data, 2048, 2048, correctSolidAngle=False, dummy=-1.0)[0]
# I = ai.xrpd2(data, 2048, 2048, correctSolidAngle=False, dummy= -1.0)
if logger.getEffectiveLevel() == logging.DEBUG:
logging.info("Plotting results")
fig = pylab.figure()
fig.suptitle('cacking of a flat image: SplitBBox')
sp = fig.add_subplot(111)
sp.imshow(I, interpolation="nearest")
fig.show()
input("Press enter to quit")
I[I == -1.0] = 1.0
assert abs(I.min() - 1.0) < self.epsilon
assert abs(I.max() - 1.0) < self.epsilon
def test_numpy_vs_fit2d(self):
"""
Compare numpy histogram with results of fit2d
"""
# logger.info(self.ai.__repr__())
tth, I = self.ai.xrpd_numpy(self.data,
len(self.fit2d), self.tmpfiles["numpy"], correctSolidAngle=False)
rwp = Rwp((tth, I), self.fit2d.T)
logger.info("Rwp numpy/fit2d = %.3f" % rwp)
if logger.getEffectiveLevel() == logging.DEBUG:
logger.info("Plotting results")
fig = pylab.figure()
fig.suptitle('Numpy Histogram vs Fit2D: Rwp=%.3f' % rwp)
sp = fig.add_subplot(111)
sp.plot(self.fit2d.T[0], self.fit2d.T[1], "-b", label='fit2d')
sp.plot(tth, I, "-r", label="numpy histogram")
handles, labels = sp.get_legend_handles_labels()
fig.legend(handles, labels)
fig.show()
input("Press enter to quit")
assert rwp < 11