def fasteval(self, type=_na.Float64):
"""fasteval(self, type=Float64) converts CharArray 'self' into
a NumArray of the specified type. fasteval() can't convert
complex arrays at all, and loses precision when converting
UInt64 or Int64.
>>> array([["1","2"],["3","4"]]).fasteval().astype('Long')
array([[1, 2],
[3, 4]])
>>> try:
... array([["1","2"],["3","other"]]).fasteval()
... except _chararray.error:
... pass
"""
n = _na.array(shape=self._shape, type=_na.Float64)
type = _nt.getType(type)
_chararray.Eval((), self, n);
if type != _na.Float64:
if ((type is _na.Int64) or
(_numinclude.hasUInt64 and type is _na.UInt64)):
warnings.warn("Loss of precision converting to 64-bit type. Consider using eval().", PrecisionWarning)
return n.astype(type)
else:
return n
def fasteval(self, type=_na.Float64):
"""fasteval(self, type=Float64) converts CharArray 'self' into
a NumArray of the specified type. fasteval() can't convert
complex arrays at all, and loses precision when converting
UInt64 or Int64.
>>> array([["1","2"],["3","4"]]).fasteval().astype('Long')
array([[1, 2],
[3, 4]])
>>> try:
... array([["1","2"],["3","other"]]).fasteval()
... except _chararray.error:
... pass
"""
n = _na.array(shape=self._shape, type=_na.Float64)
type = _nt.getType(type)
_chararray.Eval((), self, n)
if type != _na.Float64:
if ((type is _na.Int64)
or (_numinclude.hasUInt64 and type is _na.UInt64)):
warnings.warn(
"Loss of precision converting to 64-bit type. Consider using eval().",
PrecisionWarning)
return n.astype(type)
else:
return n
def argsort(self, axis=-1):
"""
>>> a=fromlist(["other","that","this","another"])
>>> a.argsort()
array([3, 0, 1, 2])
"""
if axis != -1:
raise TypeError("CharArray.argsort() does not support the axis parameter.")
ax = range(len(self))
ax.sort(lambda x, y, z=self: cmp(z[x], z[y]))
return _na.array(ax)
def argsort(self, axis=-1):
"""
>>> a=fromlist(["other","that","this","another"])
>>> a.argsort()
array([3, 0, 1, 2])
"""
if axis != -1:
raise TypeError(
"CharArray.argsort() does not support the axis parameter.")
ax = range(len(self))
ax.sort(lambda x, y, z=self: cmp(z[x], z[y]))
return _na.array(ax)
def fromrecords(recList, formats=None, names=None, shape=0, byteorder=sys.byteorder, aligned=0):
""" create a Record Array from a list of records in text form
The data in the same field can be heterogeneous, they will be promoted
to the highest data type. This method is intended for creating
smaller record arrays. If used to create large array e.g.
r=fromrecords([[2,3.,'abc']]*100000)
it is slow.
>>> r=fromrecords([[456,'dbe',1.2],[2,'de',1.3]],names='col1,col2,col3')
>>> print r[0]
(456, 'dbe', 1.2)
>>> r.field('col1')
array([456, 2])
>>> r.field('col2')
CharArray(['dbe', 'de'])
>>> import cPickle
>>> print cPickle.loads(cPickle.dumps(r))
RecArray[
(456, 'dbe', 1.2),
(2, 'de', 1.3)
]
"""
if shape == 0:
_shape = len(recList)
else:
_shape = shape
_nfields = len(recList[0])
for _rec in recList:
if len(_rec) != _nfields:
raise ValueError, "inconsistent number of objects in each record"
arrlist = [0]*_nfields
for col in range(_nfields):
tmp = [0]*_shape
for row in range(_shape):
tmp[row] = recList[row][col]
try:
arrlist[col] = num.array(tmp)
except:
try:
arrlist[col] = chararray.array(tmp)
except:
raise ValueError, "inconsistent data at row %d,field %d" % (row, col)
_array = fromarrays(arrlist, formats=formats, shape=_shape, names=names,
byteorder=byteorder, aligned=aligned)
del arrlist
del tmp
return _array
def _get_fields(self):
"""Get a dictionary of fields as numeric arrays."""
# Iterate over all the fields
fields = {}
for indx in range(self._nfields):
# determine the offset within the record
_start = self._stops[indx] - self._sizes[indx] + 1
_shape = self._shape
_type = self._fmt[indx]
_buffer = self._data
_offset = self._byteoffset + _start
# don't use self._itemsize due to possible slicing
_stride = self._strides[-1]
_order = self._byteorder
if isinstance(_type, Char):
arr = chararray.CharArray(buffer=_buffer,
shape=_shape,
itemsize=self._itemsizes[indx],
byteoffset=_offset,
bytestride=_stride)
else:
arr = num.NumArray(shape=_shape,
type=_type,
buffer=_buffer,
byteoffset=_offset,
bytestride=_stride,
byteorder=_order)
# modify the _shape and _strides for array elements
if (self._repeats[indx] != 1):
if type(self._repeats[indx]) == types.TupleType:
arr._shape = self._shape + self._repeats[indx]
else:
arr._shape = self._shape + (self._repeats[indx], )
nd_stride = num.array(arr._shape[2:] + (1, ))[::-1]
nd_stride = num.cumproduct(nd_stride) * self._itemsizes[indx]
nd_stride = nd_stride[::-1]
arr._strides = (self._strides[0], ) + tuple(nd_stride)
# Put this array as a value in dictionary
# Do both name and index
fields[indx] = arr
fields[self._names[indx]] = arr
return fields
def eval(self):
"""eval(self) converts CharArray 'self' into a NumArray.
This is the original slow implementation based on a Python loop
and the eval() function.
>>> array([["1","2"],["3","4"]]).eval()
array([[1, 2],
[3, 4]])
>>> try:
... array([["1","2"],["3","other"]]).eval()
... except NameError:
... pass
"""
n = _na.array([eval(x, {}, {}) for x in _na.ravel(self)])
n.setshape(self._shape)
return n
def eval(self):
"""eval(self) converts CharArray 'self' into a NumArray.
This is the original slow implementation based on a Python loop
and the eval() function.
>>> array([["1","2"],["3","4"]]).eval()
array([[1, 2],
[3, 4]])
>>> try:
... array([["1","2"],["3","other"]]).eval()
... except NameError:
... pass
"""
n = _na.array([eval(x, {}, {}) for x in _na.ravel(self)])
n.setshape(self._shape)
return n
def _get_fields(self):
"""Get a dictionary of fields as numeric arrays."""
# Iterate over all the fields
fields = {}
for indx in range(self._nfields):
# determine the offset within the record
_start = self._stops[indx] - self._sizes[indx] + 1
_shape = self._shape
_type = self._fmt[indx]
_buffer = self._data
_offset = self._byteoffset + _start
# don't use self._itemsize due to possible slicing
_stride = self._strides[-1]
_order = self._byteorder
if isinstance(_type, Char):
arr = chararray.CharArray(buffer=_buffer, shape=_shape,
itemsize=self._itemsizes[indx], byteoffset=_offset,
bytestride=_stride)
else:
arr = num.NumArray(shape=_shape, type=_type,
buffer=_buffer, byteoffset=_offset,
bytestride=_stride, byteorder = _order)
# modify the _shape and _strides for array elements
if (self._repeats[indx] != 1):
if type(self._repeats[indx]) == types.TupleType:
arr._shape = self._shape + self._repeats[indx]
else:
arr._shape = self._shape + (self._repeats[indx],)
nd_stride = num.array(arr._shape[2:]+(1,))[::-1]
nd_stride = num.cumproduct(nd_stride) * self._itemsizes[indx]
nd_stride = nd_stride[::-1]
arr._strides = (self._strides[0],) + tuple(nd_stride)
# Put this array as a value in dictionary
# Do both name and index
fields[indx] = arr
fields[self._names[indx]] = arr
return fields
def search(self, pattern, flags=0):
"""
>>> a=fromlist([["wo","what"],["wen","erewh"]])
>>> a.search("wh")
(array([0, 1]), array([1, 1]))
>>> a.search("1")
(array([], type=Long), array([], type=Long))
>>> b=array(["",""])
>>> b.search("1")
(array([], type=Long),)
>>> b.search("")
(array([0, 1]),)
"""
searcher = re.compile(pattern, flags).search
l = lambda x, f=searcher: int(f(x) is not None)
matches = _na.array(self.amap(l), type=_na.Bool)
if len(matches):
return _na.nonzero(matches)
else:
return ()
def search(self, pattern, flags=0):
"""
>>> a=fromlist([["wo","what"],["wen","erewh"]])
>>> a.search("wh")
(array([0, 1]), array([1, 1]))
>>> a.search("1")
(array([], type=Long), array([], type=Long))
>>> b=array(["",""])
>>> b.search("1")
(array([], type=Long),)
>>> b.search("")
(array([0, 1]),)
"""
searcher = re.compile(pattern, flags).search
l = lambda x, f=searcher: int(f(x) is not None)
matches = _na.array(self.amap(l), type=_na.Bool)
if len(matches):
return _na.nonzero(matches)
else:
return ()
def _BIT(x):
a = _na.array((1 << x), type=_na.Int32)
a.__class__ = _IeeeMaskBit
return a
Warning: Encountered divide by zero(s) in divide
>>> negzero = array([1], type=Float64)/neginf
>>> ieeemask(negzero, POS_ZERO)
array([0], type=Bool)
>>> ieeemask(negzero, NEG_ZERO)
array([1], type=Bool)
>>> ieeemask(array([-0], type=Float64), ZERO)
array([1], type=Bool)
"""
import numarrayall as _na
from numarray.ufunc import isnan
# Define *ieee special values*
_na.Error.pushMode(all="ignore")
plus_inf = inf = (_na.array(1.0) / _na.array(0.0))[()]
minus_inf = (_na.array(-1.0) / _na.array(0.0))[()]
nan = (_na.array(0.0) / _na.array(0.0))[()]
plus_zero = zero = 0.0
minus_zero = (_na.array(-1.0) * 0.0)[()]
_na.Error.popMode()
# Define *mask condition bits*
class _IeeeMaskBit(_na.NumArray):
pass
def _BIT(x):
a = _na.array((1 << x), type=_na.Int32)
def _BIT(x):
a = _na.array((1 << x), type=_na.Int32)
a.__class__ = _IeeeMaskBit
return a
Warning: Encountered divide by zero(s) in divide
>>> negzero = array([1], type=Float64)/neginf
>>> ieeemask(negzero, POS_ZERO)
array([0], type=Bool)
>>> ieeemask(negzero, NEG_ZERO)
array([1], type=Bool)
>>> ieeemask(array([-0], type=Float64), ZERO)
array([1], type=Bool)
"""
import numarrayall as _na
from numarray.ufunc import isnan
# Define *ieee special values*
_na.Error.pushMode(all="ignore")
plus_inf = inf = (_na.array(1.0)/_na.array(0.0))[()]
minus_inf = (_na.array(-1.0)/_na.array(0.0))[()]
nan = (_na.array(0.0)/_na.array(0.0))[()]
plus_zero = zero = 0.0
minus_zero = (_na.array(-1.0)*0.0)[()]
_na.Error.popMode()
# Define *mask condition bits*
class _IeeeMaskBit(_na.NumArray):
pass
def _BIT(x):
a = _na.array((1 << x), type=_na.Int32)
a.__class__ = _IeeeMaskBit
return a
def fromrecords(recList,
formats=None,
names=None,
shape=0,
byteorder=sys.byteorder,
aligned=0):
""" create a Record Array from a list of records in text form
The data in the same field can be heterogeneous, they will be promoted
to the highest data type. This method is intended for creating
smaller record arrays. If used to create large array e.g.
r=fromrecords([[2,3.,'abc']]*100000)
it is slow.
>>> r=fromrecords([[456,'dbe',1.2],[2,'de',1.3]],names='col1,col2,col3')
>>> print r[0]
(456, 'dbe', 1.2)
>>> r.field('col1')
array([456, 2])
>>> r.field('col2')
CharArray(['dbe', 'de'])
>>> import cPickle
>>> print cPickle.loads(cPickle.dumps(r))
RecArray[
(456, 'dbe', 1.2),
(2, 'de', 1.3)
]
"""
if shape == 0:
_shape = len(recList)
else:
_shape = shape
_nfields = len(recList[0])
for _rec in recList:
if len(_rec) != _nfields:
raise ValueError, "inconsistent number of objects in each record"
arrlist = [0] * _nfields
for col in range(_nfields):
tmp = [0] * _shape
for row in range(_shape):
tmp[row] = recList[row][col]
try:
arrlist[col] = num.array(tmp)
except:
try:
arrlist[col] = chararray.array(tmp)
except:
raise ValueError, "inconsistent data at row %d,field %d" % (
row, col)
_array = fromarrays(arrlist,
formats=formats,
shape=_shape,
names=names,
byteorder=byteorder,
aligned=aligned)
del arrlist
del tmp
return _array