I have a simple function defined in the following snippet:
--- start ---
import numpy
def chebyshev(x, m):
'''Calculates Chebyshev functions of the first kind using the
trigonometric identities.'''
theta = numpy.where(
numpy.abs(x)<=1.0,
numpy.arccos(x),
numpy.arccosh(numpy.abs(x))
)
y = numpy.where(
numpy.abs(x)<=1.0,
numpy.cos(m*theta),
numpy.cosh(m*theta) * numpy.where(
x > 0.0,
1.0,
-1.0
)**m
)
return y
if __name__ == '__main__':
x = numpy.linspace(-2.0, 2.0, 21)
y = chebyshev(x,3)
print(y)
--- end ---
I'm using the numpy.where() call to extract only legal values for the
circular and hyperbolic trigonometric functions. But I still get
warnings that I'm passing invalid anrguments:
--- start---
$ python3 demo.py
demo.py:8: RuntimeWarning: invalid value encountered in arccos
numpy.arccos(x),
demo.py:9: RuntimeWarning: invalid value encountered in arccosh
numpy.arccosh(numpy.abs(x))
[ -2.60000000e+01 -1.79280000e+01 -1.15840000e+01 -6.77600000e+00
-3.31200000e+00 -1.00000000e+00 3.52000000e-01 9.36000000e-01
9.44000000e-01 5.68000000e-01 -1.83697020e-16 -5.68000000e-01
-9.44000000e-01 -9.36000000e-01 -3.52000000e-01 1.00000000e+00
3.31200000e+00 6.77600000e+00 1.15840000e+01 1.79280000e+01
2.60000000e+01]
--- end ---
(I get the same with Python 2 so don't get excited about that.)
I'm guessing that numpy.where() is evaluating the complete arccos and
arccosh arrays and therefore getting invalid arguments.
Now, I can turn off the warnings with numpy.seterr(invalid='ignore') but
that's not what I would regard as good practice.
Is there a "numpythonic" way to address the issue?
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