Typo moke -> mock (close #301)

This commit is contained in:
Valentin Valls 2016-06-22 17:10:33 +02:00
parent a2fee4ac17
commit dac78233e5
8 changed files with 12 additions and 12 deletions

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@ -1,5 +1,5 @@
# Fake calibrant used
# with moke.tif image for tests
# with mock.tif image for tests
1.432685417392191241e+01
1.146279281302667385e+01
9.553661304648699115e+00

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@ -33,7 +33,7 @@ __author__ = "Jérôme Kieffer"
__contact__ = "Jerome.Kieffer@ESRF.eu"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "29/01/2016"
__date__ = "22/06/2016"
import unittest
@ -243,7 +243,7 @@ class TestMaskBeamstop(unittest.TestCase):
"""
Test for https://github.com/kif/pyFAI/issues/76
"""
dataFile = "1788/moke.tif"
dataFile = "1788/mock.tif"
def setUp(self):
"""

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@ -33,7 +33,7 @@ __author__ = "Jérôme Kieffer"
__contact__ = "Jerome.Kieffer@ESRF.eu"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "11/03/2016"
__date__ = "22/06/2016"
import os
import sys
@ -53,7 +53,7 @@ import fabio
class TestMultiGeometry(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.data = fabio.open(UtilsTest.getimage("1788/moke.tif")).data
cls.data = fabio.open(UtilsTest.getimage("1788/mock.tif")).data
cls.lst_data = [cls.data[:250, :300], cls.data[250:, :300], cls.data[:250, 300:], cls.data[250:, 300:]]
cls.det = Detector(1e-4, 1e-4)
cls.det.max_shape = (500, 600)

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@ -33,7 +33,7 @@ __author__ = "Jérôme Kieffer"
__contact__ = "Jerome.Kieffer@ESRF.eu"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "29/01/2016"
__date__ = "22/06/2016"
import unittest
@ -56,7 +56,7 @@ class testPeakPicking(unittest.TestCase):
def setUp(self):
"""Download files"""
self.calibFile = "1788/moke.tif"
self.calibFile = "1788/mock.tif"
self.ctrlPt = {0: (300, 230),
1: (300, 212),
2: (300, 195),
@ -129,7 +129,7 @@ class testPeakPicking(unittest.TestCase):
class TestMassif(unittest.TestCase):
"""test for ring extraction algorithm with image which needs binning (non regression test)"""
calibFile = "1788/moke.tif"
calibFile = "1788/mock.tif"
#TODO !!!

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@ -28,8 +28,8 @@ import numpy
import fabio
from utilstest import UtilsTest
pyFAI = UtilsTest.pyFAI
data = fabio.open(UtilsTest.getimage("1788/moke.tif")).data
ai = pyFAI.AzimuthalIntegrator.sload("moke.poni")
data = fabio.open(UtilsTest.getimage("1788/mock.tif")).data
ai = pyFAI.AzimuthalIntegrator.sload("mock.poni")
ai.xrpd(data, 1000)
tth = ai.twoThetaArray(data.shape)
dtth = ai.delta2Theta(data.shape)

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@ -23,6 +23,6 @@
#
import pyFAI, numpy
ai = pyFAI.load("moke.poni")
ai = pyFAI.load("mock.poni")
shape = (600, 600)
ai.xrpd_OpenCL(numpy.ones(shape), 500, devicetype="cpu", useFp64=False)

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@ -25,6 +25,6 @@
import fabio, pyFAI, numpy
shape = (1000, 1000)
a = numpy.ones(shape)
ai = pyFAI.load("moke.poni")
ai = pyFAI.load("mock.poni")
print(ai)
ai.xrpd_OpenCL(a, 1000, devicetype="gpu")