Finding the lowest point of a graph using matplotlib

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Say I have 2 arrays, one with a range of values for the slope of a graph, and another one for the chi squared values graphing them produces the following image

plt.figure(figsize=(8,6))
plt.plot(maybe_slopes, chi2, c = 'grey')
plt.grid(True)

Slope vs Chi squared

Slope vs Chi squared

How can I find the slope corresponding to the minimum chi square without having to explore the whole grid of parameters? (since for this examples, there are 50 values per, but if I had 100 or 1000 values, there is more data to sift through) For this example, the slope is close to -2 And the lowest chi squared is around 20K Sorry, I'm new with matplot, and yes this is for a class project

matplotlib python
1 Answers

Let's consider your curves are stored in a NumPy array. If they are in a list, you can turn them into a NumPy array with all_chi2 = np.array(all_chi2). Now you have your array of all_chi2 with, say, m rows and n columns, with m being the number of points in the chi vector, and n being the number of curves.

Because all_chi2 is a 2-dimensional array, you are looking for the coordinate of the minimum value of this matrix (m_min, n_min). This can be done with

import numpy as np

# first, find the index of maximum on the unraveled matrix
arg_min = np.argmin(all_chi2)

# then find back the 2d indexes
m_min, n_min = np.unravel_index(arg_min, allchi2.shape)

There you go, you can extract the values that you pinpointed from the graph automatically.

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