<jupyter_start><jupyter_text>http://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.interp1d.html<jupyter_code>%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy import interpolate
x = np.arange(0, 10)
y = np.exp(-x/3.0)
f = interpolate.interp1d(x, y)   # returns an interpolate function

xnew = np.arange(0, 9, 0.1)
ynew = f(xnew)   # use interpolation function returned by `interp1d`
plt.plot(x, y, 'o', xnew, ynew, '-')
plt.show()<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '290720', 'license': 'MIT', 'n_tokens_mistral': 219, 'n_tokens_neox': 210, 'n_words': 44, 'path': 'Scipy/1D interpolate.ipynb', 'repo_name': 'afcarl/Useful-python', 'size': '508'}