Reduce DeprecationWarnings in Testing

[cyschneck]

PR Summary

Closes #477

PR Checklist

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[cyschneck]

The filter in test_dask is for the warning RuntimeWarning: invalid value encountered in sqrt and filtering it is based on how xarray handles the same issue that dask is triggering

The filters in test_meteorology are warnings for when heatindex is attempting to take the square root of a negative number. Numpy doesn't fail when attempting a square root, but converts the negative number into a nan

import numpy as np
np.sqrt(np.array([-1, 0, 1]))

<stdin>:1: RuntimeWarning: invalid value encountered in sqrt
array([nan,  0.,  1.])

This PR is going to end up leaving two deprecation warnings from test_stats.py. These warnings are for eofuc and eofunc_ts. These are both warnings that originate in geocat-comp stats.py that are used for backwards compatibility.

The remaining geocat warning is for interpolation.py:133 where UserWarning: Interpolation point out of data bounds encountered return func_interpolate(new_levels, xcoords, data, axis=interp_axis) when the func_interpolate is using metpy.interpolate.interpolate_1d function

[kafitzgerald]

I'm a little concerned some of these might also be worth looking into a little more deeply and potentially addressing via better handling or tests in geocat-comp.

[cyschneck]

Sounds good, the interpolate function is a lot of interconnected pieces. Let me write up more about how it is populated

[cyschneck]

The interpolation warning is generated by the test test_interp_hybrid_to_pressure_extrap_geopotential that is populated from press_in which is populated with the values

[[[68619.195 68619.195]
  [69344.43  69290.68 ]
  [70799.516 70643.86 ]]]

To be interpolated along the values

[ 50000  92500  95000 100000]

The test calls interp_hybrid_to_pressure as linear, so it ends up calling metpy interpolate_1d. Specifically, the error being thrown is because the interpolate values and the coordinates shapes are equal without a fill_value

Metpy will raise a warning that:

Warn if interpolated values are outside data bounds, will make these the values at end of data range.

Since the input values max value 70272.49076537043 is less than max interpolate value 100000 it can't interpolate to the bounds outside the range (without setting a fill_value). So, by default, It adds the values to the end of the range

An easy way to see this is interpolating to 4.5 when the range is to 4:

import metpy.interpolate
import numpy as np

x = np.array([1., 2., 3., 4.])
y = np.array([1., 2., 3., 4.])
x_interp = np.array([2.5, 3.5])
metpy.interpolate.interpolate_1d(x_interp, x, y)

Where the array position of the max value is out of bounds, so the array appends nan

metpy.interpolate.interpolate_1d(x_interp, x, y)
<stdin>:1: UserWarning: Interpolation point out of data bounds encountered
array([2.5, nan])

When the values are within range, it returns the interpolated values without a nan

import metpy.interpolate
import numpy as np

x = np.array([1., 2., 3., 4.])
y = np.array([1., 2., 3., 4.])
x_interp = np.array([2.5, 3.5])
metpy.interpolate.interpolate_1d(x_interp, x, y)

array([2.5, 3.5])

[anissa111]

I think I may be a little confused about what's intended to be in this PR. Is this PR supposed to specifically address deprecation warnings only? Also, since this PR will close #477, I'd like to see more of the warnings discussed in that issue addressed here.

[cyschneck]

Added new issue to address UserWarning in interpolation.py (#593)

[cyschneck]

Updated scripts to account for deprecation warnings for using setup.py as well as warnings associated with redirecting links in the docs
Test scripts will continue to throw warnings associated with dask data.chunks, heat_index, and interpolation out of bounds, since these will be handled in upcoming issues (#593 and #596)