/opt/alt/python37/lib64/python3.7/site-packages/numpy/doc/__pycache__
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basics.cpython-37.opt-1.pyc80990644editdlrm
basics.cpython-37.pyc80990644editdlrm
broadcasting.cpython-37.opt-1.pyc57670644editdlrm
broadcasting.cpython-37.pyc57670644editdlrm
byteswapping.cpython-37.opt-1.pyc55440644editdlrm
byteswapping.cpython-37.pyc55440644editdlrm
constants.cpython-37.opt-1.pyc78720644editdlrm
constants.cpython-37.pyc78720644editdlrm
creation.cpython-37.opt-1.pyc57050644editdlrm
creation.cpython-37.pyc57050644editdlrm
glossary.cpython-37.opt-1.pyc125800644editdlrm
glossary.cpython-37.pyc125800644editdlrm
indexing.cpython-37.opt-1.pyc158770644editdlrm
indexing.cpython-37.pyc158770644editdlrm
internals.cpython-37.opt-1.pyc98680644editdlrm
internals.cpython-37.pyc98680644editdlrm
misc.cpython-37.opt-1.pyc63590644editdlrm
misc.cpython-37.pyc63590644editdlrm
structured_arrays.cpython-37.opt-1.pyc116490644editdlrm
structured_arrays.cpython-37.pyc116490644editdlrm
subclassing.cpython-37.opt-1.pyc287610644editdlrm
subclassing.cpython-37.pyc287610644editdlrm
ufuncs.cpython-37.opt-1.pyc56210644editdlrm
ufuncs.cpython-37.pyc56210644editdlrm
__init__.cpython-37.opt-1.pyc8650644editdlrm
__init__.cpython-37.pyc8650644editdlrm
Edit: /opt/alt/python37/lib64/python3.7/site-packages/numpy/doc/__pycache__/constants.cpython-37.pyc (7872B)
B hFd"@sdZddlmZmZmZddlZddlZgZddZedddedd dedd d edd d edddedddedddedddedddedddedddedddedddergZ e xeD]\Z Z e e ddZedZgZxbeD]ZZed eZerderde eZed!ed"efed#n eeqWdeZe d$e efqWde Z eee d%Z[ [ [ [[[[[[[[dS)&zU ========= Constants ========= NumPy includes several constants: %(constant_list)s )divisionabsolute_importprint_functionNcCst||fdS)N) constantsappend)modulenamedocr F/opt/alt/python37/lib64/python3.7/site-packages/numpy/doc/constants.py add_newdocsr ZnumpyZInfz IEEE 754 floating point representation of (positive) infinity. Use `inf` because `Inf`, `Infinity`, `PINF` and `infty` are aliases for `inf`. For more details, see `inf`. See Also -------- inf ZInfinityZNANz IEEE 754 floating point representation of Not a Number (NaN). `NaN` and `NAN` are equivalent definitions of `nan`. Please use `nan` instead of `NAN`. See Also -------- nan ZNINFa IEEE 754 floating point representation of negative infinity. Returns ------- y : float A floating point representation of negative infinity. See Also -------- isinf : Shows which elements are positive or negative infinity isposinf : Shows which elements are positive infinity isneginf : Shows which elements are negative infinity isnan : Shows which elements are Not a Number isfinite : Shows which elements are finite (not one of Not a Number, positive infinity and negative infinity) Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Also that positive infinity is not equivalent to negative infinity. But infinity is equivalent to positive infinity. Examples -------- >>> np.NINF -inf >>> np.log(0) -inf ZNZEROa IEEE 754 floating point representation of negative zero. Returns ------- y : float A floating point representation of negative zero. See Also -------- PZERO : Defines positive zero. isinf : Shows which elements are positive or negative infinity. isposinf : Shows which elements are positive infinity. isneginf : Shows which elements are negative infinity. isnan : Shows which elements are Not a Number. isfinite : Shows which elements are finite - not one of Not a Number, positive infinity and negative infinity. Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). Negative zero is considered to be a finite number. Examples -------- >>> np.NZERO -0.0 >>> np.PZERO 0.0 >>> np.isfinite([np.NZERO]) array([ True], dtype=bool) >>> np.isnan([np.NZERO]) array([False], dtype=bool) >>> np.isinf([np.NZERO]) array([False], dtype=bool) ZNaNz IEEE 754 floating point representation of Not a Number (NaN). `NaN` and `NAN` are equivalent definitions of `nan`. Please use `nan` instead of `NaN`. See Also -------- nan ZPINFZPZEROa IEEE 754 floating point representation of positive zero. Returns ------- y : float A floating point representation of positive zero. See Also -------- NZERO : Defines negative zero. isinf : Shows which elements are positive or negative infinity. isposinf : Shows which elements are positive infinity. isneginf : Shows which elements are negative infinity. isnan : Shows which elements are Not a Number. isfinite : Shows which elements are finite - not one of Not a Number, positive infinity and negative infinity. Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). Positive zero is considered to be a finite number. Examples -------- >>> np.PZERO 0.0 >>> np.NZERO -0.0 >>> np.isfinite([np.PZERO]) array([ True], dtype=bool) >>> np.isnan([np.PZERO]) array([False], dtype=bool) >>> np.isinf([np.PZERO]) array([False], dtype=bool) ea= Euler's constant, base of natural logarithms, Napier's constant. ``e = 2.71828182845904523536028747135266249775724709369995...`` See Also -------- exp : Exponential function log : Natural logarithm References ---------- .. [1] http://en.wikipedia.org/wiki/Napier_constant infa IEEE 754 floating point representation of (positive) infinity. Returns ------- y : float A floating point representation of positive infinity. See Also -------- isinf : Shows which elements are positive or negative infinity isposinf : Shows which elements are positive infinity isneginf : Shows which elements are negative infinity isnan : Shows which elements are Not a Number isfinite : Shows which elements are finite (not one of Not a Number, positive infinity and negative infinity) Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Also that positive infinity is not equivalent to negative infinity. But infinity is equivalent to positive infinity. `Inf`, `Infinity`, `PINF` and `infty` are aliases for `inf`. Examples -------- >>> np.inf inf >>> np.array([1]) / 0. array([ Inf]) Zinftynana IEEE 754 floating point representation of Not a Number (NaN). Returns ------- y : A floating point representation of Not a Number. See Also -------- isnan : Shows which elements are Not a Number. isfinite : Shows which elements are finite (not one of Not a Number, positive infinity and negative infinity) Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. `NaN` and `NAN` are aliases of `nan`. Examples -------- >>> np.nan nan >>> np.log(-1) nan >>> np.log([-1, 1, 2]) array([ NaN, 0. , 0.69314718]) Znewaxisa9 A convenient alias for None, useful for indexing arrays. See Also -------- `numpy.doc.indexing` Examples -------- >>> newaxis is None True >>> x = np.arange(3) >>> x array([0, 1, 2]) >>> x[:, newaxis] array([[0], [1], [2]]) >>> x[:, newaxis, newaxis] array([[[0]], [[1]], [[2]]]) >>> x[:, newaxis] * x array([[0, 0, 0], [0, 1, 2], [0, 2, 4]]) Outer product, same as ``outer(x, y)``: >>> y = np.arange(3, 6) >>> x[:, newaxis] * y array([[ 0, 0, 0], [ 3, 4, 5], [ 6, 8, 10]]) ``x[newaxis, :]`` is equivalent to ``x[newaxis]`` and ``x[None]``: >>> x[newaxis, :].shape (1, 3) >>> x[newaxis].shape (1, 3) >>> x[None].shape (1, 3) >>> x[:, newaxis].shape (3, 1)  z z^(\s+)[-=]+\s*$z%s.. rubric:: %sz.. const:: %s %s)Z constant_list)__doc__Z __future__rrrtextwraprerr Z constants_strsortrr dedentreplacessplitlinesZ new_lineslinematchmpopprevrgroupjoindictr r r r  sf   $+  +& /