動作環境

GeForce GTX 1070 (8GB)
ASRock Z170M Pro4S [Intel Z170chipset]
Ubuntu 16.04 LTS desktop amd64
TensorFlow v1.2.1
cuDNN v5.1 for Linux
CUDA v8.0
Python 3.5.2
IPython 6.0.0 -- An enhanced Interactive Python.
gcc (Ubuntu 5.4.0-6ubuntu1~16.04.4) 5.4.0 20160609
GNU bash, version 4.3.48(1)-release (x86_64-pc-linux-gnu)
scipy v0.19.1
geopandas v0.3.0

関連

link > Python で 1 変量データ補間 > SciPy > interpolate.*
ADDA + Matplotlib > InitField-Y for various values of Re{m}

エラー

ADDAの計算結果を補間しようとしたらエラーになった。

再現コードは以下。

test_interpolate_171028.py

import numpy as np
import sys
from scipy import signal, interpolate

# on Python 3.5.2

xs = ['1.33', '1.41', '1.25', '1.69', '1.05', '1.85', '1.17', '1.37', '1.49', '1.65', '1.77', '1.53', '1.09', '1.81', '1.13', '1.61', '1.57', '1.29', '1.73', '1.21', '1.45']
ys = [-0.026233794340000002, -0.022115366130000001, -0.023346986680000001, 0.0098408259539999998, -0.0039200259860000001, 0.045906058600000001, -0.016363607209999999, -0.025000819000000001, -0.015049274919999999, 0.0016250158680000001, 0.031175279090000001, -0.01194725152, -0.0078601925140000008, 0.041183378409999999, -0.01215601187, -0.0044200969, -0.0086785273040000006, -0.02554396125, 0.019991008380000001, -0.020176115410000001, -0.018504119140000001]

print(xs, ys)

xns = np.array(xs)
yns = np.array(ys)

tt = np.linspace(1.1, 1.8, 51)
print(tt)

f3 = interpolate.interp1d(xns, yns, kind="cubic")
y3 = f3(tt)

run

Traceback (most recent call last):
  File "test_interpolate_171028.py", line 18, in <module>
    f3 = interpolate.interp1d(xns, yns, kind="cubic")
  File "/usr/local/lib/python3.5/dist-packages/scipy/interpolate/interpolate.py", line 488, in __init__
    if np.isnan(self.x).any():
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

対処

参考: https://stackoverflow.com/questions/40809503/python-numpy-typeerror-ufunc-isfinite-not-supported-for-the-input-types

xns = np.array(xs)

を以下にすることでエラーを回避できる。

xns = np.array(xs, dtype=float)