# `interpolate.interpolate_wrapper`¶

helper_funcs.py. scavenged from enthought,interpolate

## Module Contents¶

### Functions¶

 `atleast_1d_and_contiguous`(ary,dtype=None) `nearest`(x,y,new_x) Rounds each new x to nearest input x and returns corresponding input y. `linear`(x,y,new_x) Linearly interpolates values in new_x based on the values in x and y `logarithmic`(x,y,new_x) Linearly interpolates values in new_x based in the log space of y. `block_average_above`(x,y,new_x) Linearly interpolates values in new_x based on the values in x and y. `block`(x,y,new_x) Essentially a step function.
`atleast_1d_and_contiguous`(ary, dtype=None)
`nearest`(x, y, new_x)

Rounds each new x to nearest input x and returns corresponding input y.

x : array_like
Independent values.
y : array_like
Dependent values.
new_x : array_like
The x values to return the interpolate y values.
nearest : ndarray
Rounds each new_x to nearest x and returns the corresponding y.
`linear`(x, y, new_x)

Linearly interpolates values in new_x based on the values in x and y

x : array_like
Independent values
y : array_like
Dependent values
new_x : array_like
The x values to return the interpolated y values.
`logarithmic`(x, y, new_x)

Linearly interpolates values in new_x based in the log space of y.

x : array_like
Independent values.
y : array_like
Dependent values.
new_x : array_like
The x values to return interpolated y values at.
`block_average_above`(x, y, new_x)

Linearly interpolates values in new_x based on the values in x and y.

x : array_like
Independent values.
y : array_like
Dependent values.
new_x : array_like
The x values to interpolate y values.
`block`(x, y, new_x)

Essentially a step function.

For each new_x, finds largest j such that``x[j] < new_x[j]`` and returns `y[j]`.

x : array_like
Independent values.
y : array_like
Dependent values.
new_x : array_like
The x values used to calculate the interpolated y.
block : ndarray
Return array, of same length as x_new.