How can we extract line profile from our two-dimensional image data? The function line_profile does the work. Let's say we want to extract an energy distribution curve (EDC) from our ARPES spectrum.

```python showLineNumbers import arpespythontools as arp data, energy, angle = arp.load_ses_spectra('sample_spectra.txt')

extract line profile between angles (-3, 3)

edc = arp.line_profile(data, angle, -3, 3)

Plot image

import matplotlib.pyplot as plt %matplotlib inline

Above line is specific to Jupyter Notebook

plt.figure(figsize = (8, 6)) plt.plot(energy, edc/max(edc)) plt.xlabel('$E_{kin}$ (eV)') plt.ylabel('Intensity (a.u)') plt.show()

<picture>
  <source type="image/webp" srcSet={require("/img/edc.webp").default} />
  <img src={require("/img/edc.png").default} alt="edc" />
</picture>

How about if we want the momentum distribution curve (MDC) instead? That means
we have to extract line profile along the other axis, which can be  done by
transposing the data, and interchanging the axes:

```python showLineNumbers
# extract line profile between energy values (16.5, 16.7)
mdc = arp.line_profile(data.T, energy, 16.5, 16.7)

# Plot image
import matplotlib.pyplot as plt
%matplotlib inline
# Above line is specific to Jupyter Notebook
plt.figure(figsize = (8, 6))
plt.plot(angle, mdc/max(mdc))
plt.xlabel('$\\theta$ (deg)')
plt.ylabel('Intensity (a.u)')
plt.show()

:::tip

If you do not need to specify the integration limits i.e., you want to sum over full angle (in case of EDC) or energy (in case MDC) range, it is simpler to use numpy.sum method instead.

import numpy as np
edc = np.sum(data, axis=1)
mdc = np.sum(data, axis=0)

:::