Fix periodicity behavior of chord_length

[maxnoe]

In [1]: from ctapipe.image.muon.intensity_fitter import chord_length
In [2]: import numpy as np
In [3]: phi = np.linspace(0, 2 * np.pi, 500)
In [4]: %timeit chord_length(10.0, 1.2, phi)

This branch:

5.6 μs ± 12.5 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)

On branch of #2872:

7.6 μs ± 28.2 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)

from ctapipe.image.muon.intensity_fitter import chord_length
import numpy as np
import matplotlib.pyplot as plt


phi = np.linspace(-4 * np.pi, 4 * np.pi, 1000)

fig, ax = plt.subplots(1, 1, layout="constrained", sharex=True)

for rho in (0.5, 1.2):
    ax.plot(phi, chord_length(10, rho, phi), label=f"{rho = }")

ax.legend()
fig.savefig("chord_length.png")
plt.show()

Before:

Now:

[burmist-git]

So the modulo involves really expensive calculations… But are you sure that this replacement of the modulo works for all cases?

[maxnoe]

It passes the tests... and logically, yes, it should be the same as we use the cosine to select the same domain as the modulus.

[burmist-git]

It passes the tests... and logically, yes, it should be the same as we use the cosine to select the same domain as the modulus.

Yes one test is passing. I am trusting you but this check you are doing is not intuitive for me. I will approve the PR. But will make more tests.

[maxnoe]

But will make more tests.

More tests are always welcome! Just make sure to add them to the repo :)

[ctao-sonarqube]

Quality Gate failed

Failed conditions
66.7% Coverage on New Code (required ≥ 80%)

See analysis details on SonarQube

[maxnoe]

from ctapipe.image.muon.intensity_fitter import chord_length
import numpy as np
import matplotlib.pyplot as plt


phi = np.linspace(-4 * np.pi, 4 * np.pi, 1000)
rho = 1.2

phi_mod = (phi + np.pi) % (2 * np.pi) - np.pi
mod_cond = np.abs(phi_mod) < np.arcsin(1 / rho)
new_cond = (np.abs(np.sin(phi)) < 1 / rho) & (np.cos(phi) > 0)

fig, ax = plt.subplots(1, 1, layout="constrained", sharex=True)

ax.plot(phi, mod_cond, label='mod condition')
ax.plot(phi, new_cond, ls=':', label='cos condition')
ax.legend()

fig.savefig("chord_conditions.png")