Metadata-Version: 2.4
Name: centrex-trajectories
Version: 0.4.1
Author-email: ograsdijk <o.grasdijk@gmail.com>
License-Expression: MIT
License-File: LICENSE
Requires-Python: >3.11
Requires-Dist: joblib<2,>=1.2.0
Requires-Dist: matplotlib<4,>=3.10.1
Requires-Dist: numba<0.62,>=0.61.2
Requires-Dist: numpy<3,>=2.2.5
Requires-Dist: scipy<2,>=1.15.2
Description-Content-Type: text/markdown

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# CeNTREX-trajectories
Code for simulating CeNTREX trajectories

## Installation
Clone repo and install with `pip` or directly install from GitHub with:  
```
pip install git+https://github.com/ograsdijk/CeNTREX-trajectories
```

## Sections
The beamline is split into sections specified with `Section`, which can be used as follows:
```Python
sections = [
    fourK = Section(
        name = "4K shield",
        objects = [CircularAperture(x=0, y=0, z=5e-3)],
        start = 0,
        stop = 10e-2,
        save_collisions = False,
        propagation_type=PropagationType.ballistic,
    )
]
```
This defines a section called `4K shield`, which runs from `z = 0 m -> 10e-2 m`. Collisions aren't
saved, the `propagation_type` is ballistic and it contains a single circular aperture centered around
the z axis with a radius of 5 mm.

## Collision objects
Currently two type of apertures are defined for collisions:
* `CircularAperture(x: float,y: float,r: float)`
* `RectangularAperture(x: float,y: float,wx: float,wy: float)`

Custom collision objects can be defined; apertures should inherit from `Aperture`, and each custom
collision object should have two functions:
* `check_in_bounds(start: float, stop: float)` which returns a boolean specifying whether the object fully resides inside the section
* `get_acceptance(coordinates: Coordinates)` which returns a boolean arrays specifiying which trajectories make it through the aperture

## Propagation types
There is support for ballistic and ODE solver trajectories, which is specified on a per section basis through `Section.propagation_type`
* `PropagationType.ballistic` assumes a constant velocity and constant gravitational acceleration
* `PropagationType.ode` needs a defined force function in the section and uses `scipy.integrate.solve_ivp` to calculate the trajectory

## Working example
```Python
import numpy as np
from centrex_trajectories import (
    Coordinates,
    Velocities,
    Force,
    PropagationType,
    propagate_trajectories,
    PropagationOptions,
)

from centrex_trajectories.beamline_objects import CircularAperture, Section
from centrex_trajectories.particles import TlF

in_to_m = 0.0254

fourK = Section(
    name="4K shield",
    objects=[CircularAperture(x=0, y=0, z=1.75 * in_to_m, r=1 / 2 * in_to_m)],
    start=0,
    stop=2 * in_to_m,
    save_collisions=False,
    propagation_type=PropagationType.ballistic,
)
fourtyK = Section(
    name="40K shield",
    objects=[
        CircularAperture(x=0, y=0, z=fourK.stop + 1.25 * in_to_m, r=1 / 2 * in_to_m)
    ],
    start=fourK.stop,
    stop=fourK.stop + 1.5 * in_to_m,
    save_collisions=False,
    propagation_type=PropagationType.ballistic,
)
bbexit = Section(
    name="Beamsource Exit",
    objects=[CircularAperture(0, 0, fourtyK.stop + 2.5 * in_to_m, 2 * in_to_m)],
    start=fourtyK.stop,
    stop=fourtyK.stop + 3.25 * in_to_m,
    save_collisions=False,
    propagation_type=PropagationType.ballistic,
)

sections = [fourK, fourtyK, bbexit]

n_trajectories = 100_000
coordinates_init = Coordinates(
    x=np.random.randn(n_trajectories) * 1.5e-3,
    y=np.random.randn(n_trajectories) * 1.5e-3,
    z=np.zeros(n_trajectories),
)
velocities_init = Velocities(
    vx=np.random.randn(n_trajectories) * 39.4,
    vy=np.random.randn(n_trajectories) * 39.4,
    vz=np.random.randn(n_trajectories) * 16 + 184,
)

options = PropagationOptions(n_cores=6, verbose=False)
particle = TlF()
gravity = Force(0, -9.81*particle.mass, 0)

section_data, trajectories = propagate_trajectories(
    sections,
    coordinates_init,
    velocities_init,
    particle,
    force=gravity,
    options=options,
)

```