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#/*##########################################################################
#
# The PyMca X-Ray Fluorescence Toolkit
#
# Copyright (c) 2004-2014 European Synchrotron Radiation Facility
#
# This file is part of the PyMca X-ray Fluorescence Toolkit developed at
# the ESRF by the Software group.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
#############################################################################*/
cimport cython
cimport numpy as np
import numpy as np
from MinMax cimport getMinMax
# Convert numpy dtype array-protocol string to bit field to pass to C function
# 4th bit for type: 1: floating point, 0: integer
# 3rd bit for signedness (int only): 1: unsigned, 0: signed
# 1st and 2nd bits for size: 00: 8 bits, 01: 16 bits, 10: 32 bits, 11: 64 bits.
_NUMPY_TO_TYPE_DESC = {
'f8': 0b1011,
'f4': 0b1010,
'i1': 0b0000,
'u1': 0b0100,
'i2': 0b0001,
'u2': 0b0101,
'i4': 0b0010,
'u4': 0b0110,
'i8': 0b0011,
'u8': 0b0111,
}
@cython.boundscheck(False)
@cython.wraparound(False)
def minMax(np.ndarray data, bint minPositive=False):
"""Get min, max and optionally min positive of data.
NaNs are ignored while computing min/max.
If all data is NaNs, returned min/max are NaNs and
returned minPositive is None.
:param np.ndarray data: Array of data
:param bool minPositive: Wheither to compute min positive or not.
:returns: (min, max) or (min, minPositive, max) if minPositive is True
If all data < 0, minPositive is None.
:rtype: tuple of float
:raises: ValueError if data is empty
"""
#Convert float16 to float32
if data.dtype.str[1:] == 'f2':
data = np.asarray(data, dtype=np.float32)
cdef np.ndarray c_data = np.ascontiguousarray(data)
cdef void * c_dataPtr = c_data.data
cdef unsigned long c_dataSize = c_data.size
if c_dataSize == 0:
raise ValueError("zero-size array")
cdef double c_dataMin, c_dataMinPos, c_dataMax
cdef unsigned int c_type = _NUMPY_TO_TYPE_DESC[data.dtype.str[1:]]
if minPositive:
with nogil:
getMinMax(c_dataPtr, c_type, c_dataSize,
&c_dataMin, &c_dataMinPos, &c_dataMax)
if c_dataMinPos == 0:
return c_dataMin, None, c_dataMax
else:
return c_dataMin, c_dataMinPos, c_dataMax
else:
with nogil:
getMinMax(c_dataPtr, c_type, c_dataSize,
&c_dataMin, NULL, &c_dataMax)
return c_dataMin, c_dataMax
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