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duality-group
duality-group / Bottleneck python
Repository URL to install this package:
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Version:
1.3.5 ▾
|
Bottleneck
/
nonreduce.cpython-310-x86_64-linux-gnu.so
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H=G è=æÿÿHÆ$ H=6 Hè'æÿÿHÐ$ H=$ HèæÿÿHÊ$ HLè]A\A]Ãf D Lçè@åÿÿé"ÿÿÿ Hïè0åÿÿH1* éAÿÿÿ @ ÿº H5² ÁHQ$ H81ÀèßåÿÿèåÿÿHs$ E1íH5± H8èñäÿÿLè]A\A]à H$ H5: H8èÊäÿÿHm u´Hïè«äÿÿëªÿ º H5 ÁHÖ# H81ÀèdåÿÿëHÃ# H5ä H81ÀèJåÿÿéfÿÿÿH¦# H5 H81Àè-åÿÿéIÿÿÿH# H5Ô H8èBäÿÿé.ÿÿÿH®# H5¤ H8è'äÿÿéÿÿÿ HìHÄà Cannot import bottleneck.slow replace wrong number of arguments 1 Cannot find `a` keyword input too many arguments wrong number of arguments 4 `old` must be a number `new` must be a number numpy.core._multiarray_umath _ARRAY_API _ARRAY_API not found _ARRAY_API is NULL pointer a old new nonreduce Cannot import %s from bottleneck.slow bottleneck.slow.%s is not callable Cannot safely cast `old` to int Cannot safely cast `new` to int Cannot find `old` keyword input Cannot find `new` keyword input wrong number of keyword arguments 3 works in place so input must be an array, not (e.g.) a list `old_obj` should never be NULL; please report this bug. `new_obj` should never be NULL; please report this bug. _ARRAY_API is not PyCapsule object module compiled against ABI version 0x%x but this version of numpy is 0x%x module compiled against API version 0x%x but this version of numpy is 0x%x FATAL: module compiled as unknown endian FATAL: module compiled as little endian, but detected different endianness at runtime numpy.core.multiarray failed to import ð¿;L ÈÛÿÿh ØÝÿÿ ãÿÿà ¸äÿÿ4 Èèÿÿ 8ìÿÿÔ øðÿÿ$ õÿÿ zR x $ XÛÿÿP FJ w ?;*3$" L D @Ýÿÿ¯ BBB B(D0A8G°Ö
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¨ þÿÿo ÿÿÿo ðÿÿo < ùÿÿo ÈM 6 F V f v ¦ ¶ Æ Ö æ ö & 6 F V f replace(a, old, new)
Replace (inplace) given scalar values of an array with new values.
The equivalent numpy function:
a[a==old] = new
Or in the case where old=np.nan:
a[np.isnan(old)] = new
Parameters
----------
a : numpy.ndarray
The input array, which is also the output array since this functions
works inplace.
old : scalar
All elements in `a` with this value will be replaced by `new`.
new : scalar
All elements in `a` with a value of `old` will be replaced by `new`.
Returns
-------
Returns a view of the input array after performing the replacements,
if any.
Examples
--------
Replace zero with 3 (note that the input array is modified):
>>> a = np.array([1, 2, 0])
>>> bn.replace(a, 0, 3)
>>> a
array([1, 2, 3])
Replace np.nan with 0:
>>> a = np.array([1, 2, np.nan])
>>> bn.replace(a, np.nan, 0)
>>> a
array([ 1., 2., 0.])
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