mirror of https://github.com/silx-kit/pyFAI.git
correct openCL parameters
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@ -312,7 +312,7 @@ def histGPU1d(numpy.ndarray weights not None,
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@param bins: number of output bins
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@param pos0Range: minimum and maximum of the 2th range
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@param dummy: value for bins without pixels
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@param deviceType: "cpu" or "gpu" or "all" or "def"
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@param devicetype: "cpu" or "gpu" or "all" or "def"
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@param useFp64: shall histogram be done in double precision (adviced)
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@param platformid: platform number
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@param deviceid: device number
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@ -356,7 +356,7 @@ class AzimuthalIntegrator(Geometry):
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@param dummy: value for dead/masked pixels
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@param delta_dummy: precision for dummy value
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OpenCL specific parameters:
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@param deviceType: "cpu" or "gpu" or "all" or "def"
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@param devicetype: "cpu" or "gpu" or "all" or "def"
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@param useFp64: shall histogram be done in double precision (adviced)
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@param platformid: platform number
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@param deviceid: device number
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@ -377,11 +377,7 @@ class AzimuthalIntegrator(Geometry):
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tthRange=tthRange,
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mask=mask,
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dummy=dummy,
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delta_dummy=delta_dummy,
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devicetype=devicetype,
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useFp64=useFp64,
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platformid=platformid,
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deviceid=deviceid)
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delta_dummy=delta_dummy)
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shape = data.shape
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tth = self.twoThetaArray(data.shape)
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dtth = self.delta2Theta(data.shape)
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@ -401,7 +397,11 @@ class AzimuthalIntegrator(Geometry):
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delta_pos0=dtth[mask],
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bins=nbPt,
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pos0Range=tthRange,
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dummy=dummy)
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dummy=dummy,
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devicetype=devicetype,
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useFp64=useFp64,
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platformid=platformid,
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deviceid=deviceid)
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tthAxis = numpy.degrees(tthAxis)
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if filename:
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open(filename, "w").writelines(["%s\t%s%s" % (t, i, os.linesep) for t, i in zip(tthAxis, I)])
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