def __setitem__(self, i, value):
if isinstance(i, (int, long)):
self.array.set(i, value)
elif isinstance(i, slice):
if isinstance(value, ObjectArray):
raise Exception
elif isinstance(value, ndarray):
what = value.array
else:
what = value
try:
Numpy.setslice(what, self.array, i.start or 0, i.stop or len(self), i.step or 1)
except java.lang.IllegalArgumentException:
raise ValueError("Could not broadcast arrays of different shapes")
elif isinstance(i, ndarray):
if isinstance(value, ObjectArray):
raise Exception
elif isinstance(value, ndarray):
what = value.array
else:
what = value
try:
Numpy.setfancy(what, self.array, i.array)
except java.lang.IllegalArgumentException:
raise ValueError("Could not broadcast arrays of different shapes")
except java.lang.IndexOutOfBoundsException:
raise IndexError("Index out of bounds")
else:
raise NotImplementedError
def ones(shape, dtype=float, order="C"):
if isinstance(shape, int):
if dtype is bool:
return ndarray(Numpy.onesBoolean(shape))
elif dtype is float:
return ndarray(Numpy.onesDouble(shape))
elif dtype is int:
return ndarray(Numpy.onesInteger(shape))
elif dtype is object:
return ObjectArray([1] * shape)
else:
raise NotImplementedError
else:
raise NotImplementedError
def ones(shape, dtype=float, order="C"):
if isinstance(shape, int):
if dtype is bool:
return ndarray(Numpy.onesBoolean(shape))
elif dtype is float:
return ndarray(Numpy.onesDouble(shape))
elif dtype is int:
return ndarray(Numpy.onesInteger(shape))
elif dtype is object:
return ObjectArray([1] * shape)
else:
raise NotImplementedError
else:
raise NotImplementedError
def __getitem__(self, i):
if isinstance(i, (int, long)):
return self.array.get(i)
elif isinstance(i, slice):
return ndarray(Numpy.getslice(self.array, i.start or 0, i.stop or len(self), i.step or 1))
elif isinstance(i, ndarray):
try:
return ndarray(Numpy.getfancy(self.array, i.array));
except java.lang.IndexOutOfBoundsException:
raise IndexError("Index out of bounds")
else:
raise NotImplementedError
def __getitem__(self, i):
if isinstance(i, (int, long)):
return self.array.get(i)
elif isinstance(i, slice):
return ndarray(
Numpy.getslice(self.array, i.start or 0, i.stop
or len(self), i.step or 1))
elif isinstance(i, ndarray):
try:
return ndarray(Numpy.getfancy(self.array, i.array))
except java.lang.IndexOutOfBoundsException:
raise IndexError("Index out of bounds")
else:
raise NotImplementedError
def __setitem__(self, i, value):
if isinstance(i, (int, long)):
self.array.set(i, value)
elif isinstance(i, slice):
if isinstance(value, ObjectArray):
raise Exception
elif isinstance(value, ndarray):
what = value.array
else:
what = value
try:
Numpy.setslice(what, self.array, i.start or 0, i.stop
or len(self), i.step or 1)
except java.lang.IllegalArgumentException:
raise ValueError(
"Could not broadcast arrays of different shapes")
elif isinstance(i, ndarray):
if isinstance(value, ObjectArray):
raise Exception
elif isinstance(value, ndarray):
what = value.array
else:
what = value
try:
Numpy.setfancy(what, self.array, i.array)
except java.lang.IllegalArgumentException:
raise ValueError(
"Could not broadcast arrays of different shapes")
except java.lang.IndexOutOfBoundsException:
raise IndexError("Index out of bounds")
else:
raise NotImplementedError
def count_nonzero(x): return Numpy.count_nonzero(x.array) def mean(x): return Numpy.mean(x.array)
def copy(x): return Numpy.copy(x.array) def count_nonzero(x): return Numpy.count_nonzero(x.array)
def __init__(self, pythonList):
self.pythonList = pythonList
self.indexArray = ndarray(Numpy.indexArray(len(pythonList)))
def __setitem__(self, i, value):
if isinstance(i, (int, long)):
self.pythonList[i] = value
elif isinstance(i, slice):
if isinstance(value, ndarray):
p = self.pythonList
if isinstance(value, ObjectArray):
g = value.pythonList.__getitem__
else:
g = value.array.get
for index in xrange(i.start or 0, i.stop or len(self), i.step or 1):
p[index] = g(index)
else:
p = self.pythonList
for index in xrange(i.start or 0, i.stop or len(self), i.step or 1):
p[index] = value
elif isinstance(i, ndarray):
if isinstance(i.array, ArrayBoolean1d):
if len(i) != len(self):
raise ValueError("Could not broadcast arrays of different shapes")
if isinstance(value, ndarray):
if Numpy.count_nonzero(i.array) != len(value):
raise ValueError("Could not broadcast arrays of different shapes")
j = 0
p = self.pythonList
if isinstance(value, ObjectArray):
g = value.pythonList.__getitem__
else:
g = value.array.get
for ii in xrange(len(self)):
if i.array.get(ii):
p[ii] = g(j)
j += 1
else:
p = self.pythonList
for ii in xrange(len(self)):
if i.array.get(ii):
p[ii] = value
elif isinstance(i.array, ArrayInteger1d):
if isinstance(value, ndarray):
if len(i) != len(value):
raise ValueError("Could not broadcast arrays of different shapes")
l = len(self)
p = self.pythonList
for ii in xrange(len(i)):
index = i.array.get(ii)
if index < 0:
index = l + index
p[index] = value[ii]
else:
l = len(self)
p = self.pythonList
for ii in xrange(len(i)):
index = i.array.get(ii)
if index < 0:
index = l + index
p[index] = value
else:
raise Exception
def count_nonzero(x):
return Numpy.count_nonzero(x.array)
def sum(x): return Numpy.sum(x.array) except ImportError:
def nanmin(x): return Numpy.nanmin(x.array) def std(x, ddof=0): return Numpy.std(x.array, ddof)
def sum(x):
return Numpy.sum(x.array)
def std(x, ddof=0):
return Numpy.std(x.array, ddof)
def nanmin(x):
return Numpy.nanmin(x.array)
def nanmax(x):
return Numpy.nanmax(x.array)
def mean(x):
return Numpy.mean(x.array)
def copy(self):
return Numpy.copy(self.array)
def mean(x): return Numpy.mean(x.array) def nanmax(x): return Numpy.nanmax(x.array)
def nanmax(x): return Numpy.nanmax(x.array) def nanmin(x): return Numpy.nanmin(x.array)
def __setitem__(self, i, value):
if isinstance(i, (int, long)):
self.pythonList[i] = value
elif isinstance(i, slice):
if isinstance(value, ndarray):
p = self.pythonList
if isinstance(value, ObjectArray):
g = value.pythonList.__getitem__
else:
g = value.array.get
for index in xrange(i.start or 0, i.stop or len(self),
i.step or 1):
p[index] = g(index)
else:
p = self.pythonList
for index in xrange(i.start or 0, i.stop or len(self),
i.step or 1):
p[index] = value
elif isinstance(i, ndarray):
if isinstance(i.array, ArrayBoolean1d):
if len(i) != len(self):
raise ValueError(
"Could not broadcast arrays of different shapes")
if isinstance(value, ndarray):
if Numpy.count_nonzero(i.array) != len(value):
raise ValueError(
"Could not broadcast arrays of different shapes"
)
j = 0
p = self.pythonList
if isinstance(value, ObjectArray):
g = value.pythonList.__getitem__
else:
g = value.array.get
for ii in xrange(len(self)):
if i.array.get(ii):
p[ii] = g(j)
j += 1
else:
p = self.pythonList
for ii in xrange(len(self)):
if i.array.get(ii):
p[ii] = value
elif isinstance(i.array, ArrayInteger1d):
if isinstance(value, ndarray):
if len(i) != len(value):
raise ValueError(
"Could not broadcast arrays of different shapes"
)
l = len(self)
p = self.pythonList
for ii in xrange(len(i)):
index = i.array.get(ii)
if index < 0:
index = l + index
p[index] = value[ii]
else:
l = len(self)
p = self.pythonList
for ii in xrange(len(i)):
index = i.array.get(ii)
if index < 0:
index = l + index
p[index] = value
else:
raise Exception
def std(x, ddof=0): return Numpy.std(x.array, ddof) def sum(x): return Numpy.sum(x.array)
def __init__(self, pythonList):
self.pythonList = pythonList
self.indexArray = ndarray(Numpy.indexArray(len(pythonList)))
def copy(self):
return Numpy.copy(self.array)
def copy(x):
return Numpy.copy(x.array)
