def extract(condition, arr):
"""Return the elements of ravel(arr) where ravel(condition) is True
(in 1D).
Equivalent to compress(ravel(condition), ravel(arr)).
"""
return _nx.take(ravel(arr), nonzero(ravel(condition))[0])
def extract(condition, arr):
"""Return the elements of ravel(arr) where ravel(condition) is True
(in 1D).
Equivalent to compress(ravel(condition), ravel(arr)).
"""
return _nx.take(ravel(arr), nonzero(ravel(condition))[0])
def append(arr, values, axis=None):
"""Append to the end of an array along axis (ravel first if None)
"""
arr = asanyarray(arr)
if axis is None:
if arr.ndim != 1:
arr = arr.ravel()
values = ravel(values)
axis = arr.ndim - 1
return concatenate((arr, values), axis=axis)
def append(arr, values, axis=None):
"""Append to the end of an array along axis (ravel first if None)
"""
arr = asanyarray(arr)
if axis is None:
if arr.ndim != 1:
arr = arr.ravel()
values = ravel(values)
axis = arr.ndim-1
return concatenate((arr, values), axis=axis)
def make_mask(m, copy=0, flag=0):
"""make_mask(m, copy=0, flag=0)
return m as a mask, creating a copy if necessary or requested.
Can accept any sequence of integers or nomask. Does not check
that contents must be 0s and 1s.
if flag, return nomask if m contains no true elements.
"""
if m is nomask:
return nomask
elif isinstance(m, ndarray):
if m.dtype.type is MaskType:
if copy:
result = numeric.array(m, dtype=MaskType, copy=copy)
else:
result = m
else:
result = m.astype(MaskType)
else:
result = filled(m, True).astype(MaskType)
if flag and not fromnumeric.sometrue(fromnumeric.ravel(result)):
return nomask
else:
return result
def _array2string(a, max_line_width, precision, suppress_small, separator=' ',
prefix="", formatter=None):
if max_line_width is None:
max_line_width = _line_width
if precision is None:
precision = _float_output_precision
if suppress_small is None:
suppress_small = _float_output_suppress_small
if formatter is None:
formatter = _formatter
if a.size > _summaryThreshold:
summary_insert = "..., "
data = _leading_trailing(a)
else:
summary_insert = ""
data = ravel(a)
formatdict = {'bool': _boolFormatter,
'int': IntegerFormat(data),
'float': FloatFormat(data, precision, suppress_small),
'longfloat': LongFloatFormat(precision),
'complexfloat': ComplexFormat(data, precision,
suppress_small),
'longcomplexfloat': LongComplexFormat(precision),
'datetime': DatetimeFormat(data),
'timedelta': TimedeltaFormat(data),
'numpystr': repr_format,
'str': str}
if formatter is not None:
fkeys = [k for k in formatter.keys() if formatter[k] is not None]
if 'all' in fkeys:
for key in formatdict.keys():
formatdict[key] = formatter['all']
if 'int_kind' in fkeys:
for key in ['int']:
formatdict[key] = formatter['int_kind']
if 'float_kind' in fkeys:
for key in ['float', 'longfloat']:
formatdict[key] = formatter['float_kind']
if 'complex_kind' in fkeys:
for key in ['complexfloat', 'longcomplexfloat']:
formatdict[key] = formatter['complex_kind']
if 'str_kind' in fkeys:
for key in ['numpystr', 'str']:
formatdict[key] = formatter['str_kind']
for key in formatdict.keys():
if key in fkeys:
formatdict[key] = formatter[key]
try:
format_function = a._format
msg = "The `_format` attribute is deprecated in Numpy 2.0 and " \
"will be removed in 2.1. Use the `formatter` kw instead."
import warnings
warnings.warn(msg, DeprecationWarning)
except AttributeError:
# find the right formatting function for the array
dtypeobj = a.dtype.type
if issubclass(dtypeobj, _nt.bool_):
format_function = formatdict['bool']
elif issubclass(dtypeobj, _nt.integer):
if (hasattr(_nt, "timedelta64") and
issubclass(dtypeobj, _nt.timedelta64)):
format_function = formatdict['timedelta']
else:
format_function = formatdict['int']
elif issubclass(dtypeobj, _nt.floating):
if issubclass(dtypeobj, _nt.longfloat):
format_function = formatdict['longfloat']
else:
format_function = formatdict['float']
elif issubclass(dtypeobj, _nt.complexfloating):
if issubclass(dtypeobj, _nt.clongfloat):
format_function = formatdict['longcomplexfloat']
else:
format_function = formatdict['complexfloat']
elif issubclass(dtypeobj, (_nt.unicode_, _nt.string_)):
format_function = formatdict['numpystr']
elif (hasattr(_nt, "datetime64") and
issubclass(dtypeobj, _nt.datetime64)):
format_function = formatdict['datetime']
else:
format_function = formatdict['str']
# skip over "["
next_line_prefix = " "
# skip over array(
next_line_prefix += " " * len(prefix)
lst = _formatArray(a, format_function, len(a.shape), max_line_width,
next_line_prefix, separator,
_summaryEdgeItems, summary_insert)[:-1]
return lst
