B &]\@sdZddlmZmZmZddlZddlmZej fddZ ej dd d d Z ej d d d dZ ej dd ddZej dd ddZej dd ddZdS)z; helper_funcs.py. scavenged from enthought,interpolate )divisionprint_functionabsolute_importN) _interpolatecCstt||S)N)np atleast_1dZascontiguousarray)ZaryZdtyper Dlib/python3.7/site-packages/scipy/interpolate/interpolate_wrapper.pyatleast_1d_and_contiguous sr z&'nearest' is deprecated in SciPy 1.0.0)messagecCstt|ddg|ddf}td||}t|}d}t|||d}tt|dtjt }tj ||dd}|S)a Rounds each new x to nearest input x and returns corresponding input y. Parameters ---------- x : array_like Independent values. y : array_like Dependent values. new_x : array_like The x values to return the interpolate y values. Returns ------- nearest : ndarray Rounds each `new_x` to nearest `x` and returns the corresponding `y`. rrg?g|=)axis) rZ concatenateZarrayr searchsortedrclipInfastypeinttake)xynew_xZ shifted_xZmidpoints_of_xTINYindicesnew_yr r r nearests&rz%'linear' is deprecated in SciPy 1.0.0cCst|tj}t|tj}t|tj}|jdkr6tdt|jdkrt|jdt|ftj}xPtt|D]}t ||||||qnWn"tt|tj}t |||||S)a Linearly interpolates values in new_x based on the values in x and y Parameters ---------- x : array_like Independent values y : array_like Dependent values new_x : array_like The x values to return the interpolated y values. z+`linear` only works with 1-D or 2-D arrays.r) r rfloat64ndim ValueErrorlenshapezerosrangerZ linear_dddd)rrrrir r r linear/s    r%z*'logarithmic' is deprecated in SciPy 1.0.0cCst|tj}t|tj}t|tj}|jdkr6tdt|jdkrt|jdt|ftj}xPtt|D]}t ||||||qnWn"tt|tj}t |||||S)a Linearly interpolates values in new_x based in the log space of y. Parameters ---------- x : array_like Independent values. y : array_like Dependent values. new_x : array_like The x values to return interpolated y values at. rz+`linear` only works with 1-D or 2-D arrays.r) r rrrrr r!r"r#rZloginterp_dddd)rrrrr$r r r logarithmicOs    r&z2'block_average_above' is deprecated in SciPy 1.0.0cCsd}t|tj}t|tj}t|tj}|jdkr:tdt|jdkrt|jdt|ftj}xZtt|D]&}t ||||||}|dk rrPqrWn"tt|tj}t ||||}|dk rd||||d|df}t||S)a Linearly interpolates values in new_x based on the values in x and y. Parameters ---------- x : array_like Independent values. y : array_like Dependent values. new_x : array_like The x values to interpolate y values. Nrz+`linear` only works with 1-D or 2-D arrays.rzVblock_average_above cannot extrapolate and new_x[%d]=%f is out of the x range (%f, %f)r ) r rrrrr r!r"r#rZblock_averave_above_ddddZblock_average_above_dddd)rrrZ bad_indexrr$msgr r r block_average_aboveos(      r(z$'block' is deprecated in SciPy 1.0.0cCsHd}t|||d}tt|dtjt}tj||dd}|S)a Essentially a step function. For each `new_x`, finds largest j such that``x[j] < new_x[j]`` and returns ``y[j]``. Parameters ---------- x : array_like Independent values. y : array_like Dependent values. new_x : array_like The x values used to calculate the interpolated y. Returns ------- block : ndarray Return array, of same length as `x_new`. g|=rrr )r)rrrrrrrr)rrrrrrr r r blocks r))__doc__Z __future__rrrZnumpyrrrr Z deprecaterr%r&r(r)r r r r s !  *