# -----------------------------------------------------------------------
# Copyright: 2010-2018, imec Vision Lab, University of Antwerp
# 2013-2018, CWI, Amsterdam
#
# Contact: astra@astra-toolbox.com
# Website: http://www.astra-toolbox.com/
#
# This file is part of the ASTRA Toolbox.
#
#
# The ASTRA Toolbox is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# The ASTRA Toolbox is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with the ASTRA Toolbox. If not, see .
#
# -----------------------------------------------------------------------
#
# distutils: language = c++
# distutils: libraries = astra
import sys
cimport numpy as np
import numpy as np
import six
if six.PY3:
import builtins
else:
import __builtin__ as builtins
from libcpp.string cimport string
from libcpp.vector cimport vector
from libcpp.list cimport list
from cython.operator cimport dereference as deref, preincrement as inc
from cpython.version cimport PY_MAJOR_VERSION
cimport PyXMLDocument
from .PyXMLDocument cimport XMLDocument
from .PyXMLDocument cimport XMLNode
from .PyIncludes cimport *
from .pythonutils import GPULink, checkArrayForLink
cdef extern from "CFloat32CustomPython.h":
cdef cppclass CFloat32CustomPython:
CFloat32CustomPython(arrIn)
cdef extern from "Python.h":
void* PyLong_AsVoidPtr(object)
include "config.pxi"
cdef Config * dictToConfig(string rootname, dc) except NULL:
cdef Config * cfg = new Config()
cfg.initialize(rootname)
try:
readDict(cfg.self, dc)
except Exception:
del cfg
exc = sys.exc_info()
raise exc[0], exc[1], exc[2]
return cfg
def convert_item(item):
if isinstance(item, six.string_types):
return item.encode('ascii')
if type(item) is not dict:
return item
out_dict = {}
for k in item:
out_dict[convert_item(k)] = convert_item(item[k])
return out_dict
def wrap_to_bytes(value):
if isinstance(value, six.binary_type):
return value
s = str(value)
if PY_MAJOR_VERSION == 3:
s = s.encode('ascii')
return s
def wrap_from_bytes(value):
s = value
if PY_MAJOR_VERSION == 3:
s = s.decode('ascii')
return s
cdef bool readDict(XMLNode root, _dc) except False:
cdef XMLNode listbase
cdef XMLNode itm
cdef int i
cdef int j
cdef double* data
dc = convert_item(_dc)
for item in dc:
val = dc[item]
if isinstance(val, builtins.list) or isinstance(val, tuple):
val = np.array(val,dtype=np.float64)
if isinstance(val, np.ndarray):
if val.size == 0:
break
listbase = root.addChildNode(item)
contig_data = np.ascontiguousarray(val,dtype=np.float64)
data = np.PyArray_DATA(contig_data)
if val.ndim == 2:
listbase.setContent(data, val.shape[1], val.shape[0], False)
elif val.ndim == 1:
listbase.setContent(data, val.shape[0])
else:
raise Exception("Only 1 or 2 dimensions are allowed")
elif isinstance(val, dict):
if item == six.b('option') or item == six.b('options') or item == six.b('Option') or item == six.b('Options'):
readOptions(root, val)
else:
itm = root.addChildNode(item)
readDict(itm, val)
else:
if item == six.b('type'):
root.addAttribute(< string > six.b('type'), wrap_to_bytes(val))
else:
if isinstance(val, builtins.bool):
val = int(val)
itm = root.addChildNode(item, wrap_to_bytes(val))
return True
cdef bool readOptions(XMLNode node, dc) except False:
cdef XMLNode listbase
cdef XMLNode itm
cdef int i
cdef int j
cdef double* data
for item in dc:
val = dc[item]
if node.hasOption(item):
raise Exception('Duplicate Option: %s' % item)
if isinstance(val, builtins.list) or isinstance(val, tuple):
val = np.array(val,dtype=np.float64)
if isinstance(val, np.ndarray):
if val.size == 0:
break
listbase = node.addChildNode(six.b('Option'))
listbase.addAttribute(< string > six.b('key'), < string > item)
contig_data = np.ascontiguousarray(val,dtype=np.float64)
data = np.PyArray_DATA(contig_data)
if val.ndim == 2:
listbase.setContent(data, val.shape[1], val.shape[0], False)
elif val.ndim == 1:
listbase.setContent(data, val.shape[0])
else:
raise Exception("Only 1 or 2 dimensions are allowed")
else:
if isinstance(val, builtins.bool):
val = int(val)
node.addOption(item, wrap_to_bytes(val))
return True
cdef configToDict(Config *cfg):
return XMLNode2dict(cfg.self)
def castString3(input):
return input.decode('utf-8')
def castString2(input):
return input
if six.PY3:
castString = castString3
else:
castString = castString2
def stringToPythonValue(inputIn):
input = castString(inputIn)
# matrix
if ';' in input:
input = input.rstrip(';')
row_strings = input.split(';')
col_strings = row_strings[0].split(',')
nRows = len(row_strings)
nCols = len(col_strings)
out = np.empty((nRows,nCols))
for ridx, row in enumerate(row_strings):
col_strings = row.split(',')
for cidx, col in enumerate(col_strings):
out[ridx,cidx] = float(col)
return out
# vector
if ',' in input:
input = input.rstrip(',')
items = input.split(',')
out = np.empty(len(items))
for idx,item in enumerate(items):
out[idx] = float(item)
return out
try:
# integer
return int(input)
except ValueError:
try:
#float
return float(input)
except ValueError:
# string
return str(input)
cdef XMLNode2dict(XMLNode node):
cdef XMLNode subnode
cdef list[XMLNode] nodes
cdef list[XMLNode].iterator it
dct = {}
opts = {}
if node.hasAttribute(six.b('type')):
dct['type'] = castString(node.getAttribute(six.b('type')))
nodes = node.getNodes()
it = nodes.begin()
while it != nodes.end():
subnode = deref(it)
if castString(subnode.getName())=="Option":
if subnode.hasAttribute('value'):
opts[castString(subnode.getAttribute('key'))] = stringToPythonValue(subnode.getAttribute('value'))
else:
opts[castString(subnode.getAttribute('key'))] = stringToPythonValue(subnode.getContent())
else:
dct[castString(subnode.getName())] = stringToPythonValue(subnode.getContent())
inc(it)
if len(opts)>0: dct['options'] = opts
return dct
cdef CFloat32VolumeData3D* linkVolFromGeometry(CVolumeGeometry3D *pGeometry, data) except NULL:
cdef CFloat32VolumeData3D * pDataObject3D = NULL
geom_shape = (pGeometry.getGridSliceCount(), pGeometry.getGridRowCount(), pGeometry.getGridColCount())
if isinstance(data, np.ndarray):
data_shape = data.shape
elif isinstance(data, GPULink):
data_shape = (data.z, data.y, data.x)
if geom_shape != data_shape:
raise ValueError(
"The dimensions of the data do not match those specified in the geometry: {} != {}".format(data_shape, geom_shape))
if isinstance(data, np.ndarray):
checkArrayForLink(data)
pCustom = new CFloat32CustomPython(data)
pDataObject3D = new CFloat32VolumeData3DMemory(pGeometry, pCustom)
elif isinstance(data, GPULink):
IF HAVE_CUDA==True:
hnd = wrapHandle(PyLong_AsVoidPtr(data.ptr), data.x, data.y, data.z, data.pitch/4)
pDataObject3D = new CFloat32VolumeData3DGPU(pGeometry, hnd)
ELSE:
raise NotImplementedError("CUDA support is not enabled in ASTRA")
else:
raise TypeError("data should be a numpy.ndarray or a GPULink object")
return pDataObject3D
cdef CFloat32ProjectionData3D* linkProjFromGeometry(CProjectionGeometry3D *pGeometry, data) except NULL:
cdef CFloat32ProjectionData3D * pDataObject3D = NULL
geom_shape = (pGeometry.getDetectorRowCount(), pGeometry.getProjectionCount(), pGeometry.getDetectorColCount())
if isinstance(data, np.ndarray):
data_shape = data.shape
elif isinstance(data, GPULink):
data_shape = (data.z, data.y, data.x)
if geom_shape != data_shape:
raise ValueError(
"The dimensions of the data do not match those specified in the geometry: {} != {}".format(data_shape, geom_shape))
if isinstance(data, np.ndarray):
checkArrayForLink(data)
pCustom = new CFloat32CustomPython(data)
pDataObject3D = new CFloat32ProjectionData3DMemory(pGeometry, pCustom)
elif isinstance(data, GPULink):
IF HAVE_CUDA==True:
hnd = wrapHandle(PyLong_AsVoidPtr(data.ptr), data.x, data.y, data.z, data.pitch/4)
pDataObject3D = new CFloat32ProjectionData3DGPU(pGeometry, hnd)
ELSE:
raise NotImplementedError("CUDA support is not enabled in ASTRA")
else:
raise TypeError("data should be a numpy.ndarray or a GPULink object")
return pDataObject3D