numpy.lib.function_base
index
/usr/lib/python2.6/dist-packages/numpy/lib/function_base.py

 
Modules
       
numpy.core.numeric
numpy
re
sys
types
warnings

 
Functions
       
_chbevl(x, vals)
_get_nargs(obj)
_i0_1(x)
_i0_2(x)
_insert(...)
Insert vals sequentially into equivalent 1-d positions indicated by mask.
_nanop(op, fill, a, axis=None)
General operation on arrays with not-a-number values.
 
Parameters
----------
op : callable
    Operation to perform.
fill : float
    NaN values are set to fill before doing the operation.
a : array-like
    Input array.
axis : {int, None}, optional
    Axis along which the operation is computed.
    By default the input is flattened.
 
Returns
-------
y : {ndarray, scalar}
    Processed data.
compiled_interp = interp(...)

 
Data
        __all__ = ['logspace', 'linspace', 'select', 'piecewise', 'trim_zeros', 'copy', 'iterable', 'diff', 'gradient', 'angle', 'unwrap', 'sort_complex', 'disp', 'unique', 'extract', 'place', 'nansum', 'nanmax', 'nanargmax', 'nanargmin', ...]
__docformat__ = 'restructuredtext en'
__file__ = '/usr/lib/python2.6/dist-packages/numpy/lib/function_base.pyc'
__name__ = 'numpy.lib.function_base'
__package__ = 'numpy.lib'
_i0A = [-4.4153416464793395e-18, 3.3307945188222384e-17, -2.4312798465479549e-16, 1.7153912855551331e-15, -1.1685332877993451e-14, 7.6761854986049361e-14, -4.856446783111929e-13, 2.9550526631296399e-12, -1.7268262914415559e-11, 9.675809035373237e-11, -5.1897956016352627e-10, 2.6598237246823866e-09, -1.300025009986248e-08, 6.0469950225419186e-08, -2.6707938539406119e-07, 1.1173875391201037e-06, -4.4167383584587505e-06, 1.6448448070728896e-05, -5.754195010082104e-05, 0.00018850288509584165, ...]
_i0B = [-7.2331804878747538e-18, -4.8305044859441819e-18, 4.4656214202967598e-17, 3.4612228676974612e-17, -2.8276239805165836e-16, -3.425485619677219e-16, 1.7725601330565263e-15, 3.8116806693526224e-15, -9.5548466988283073e-15, -4.1505693472872222e-14, 1.54008621752141e-14, 3.8527783827421426e-13, 7.180124451383666e-13, -1.7941785315068062e-12, -1.3215811840447713e-11, -3.1499165279632416e-11, 1.1889147107846439e-11, 4.9406023882249701e-10, 3.3962320257083865e-09, 2.266668990498178e-08, ...]