Metadata-Version: 2.4
Name: iupitermag
Version: 0.1.6
Requires-Dist: numpy>=2.4.2
License-File: LICENSE
Summary: Python package with Rust bindings to calculate the magnetic field in Jupiter's magnetosphere.
Author: Yash Sarkango
Requires-Python: >=3.12
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Repository, https://github.com/ysar/iupitermag.git

# iupitermag

## Introduction 

iupitermag is a Python package with Rust bindings to model Jupiter's magnetic field.  This includes 
the internal field represented by spherical harmonics and the current sheet field like CON2020. In 
addition to using named field models like JRM33, JRM09, CON2020, you may also use your own model 
parameters to define a custom field model.

![Jupiter's Surface Field Strength](images/jupiter_surfacefield.png)

*Jupiter's internal magnetic field intensity at the 1-bar "surface" using the JRM33 model.*

Many other public codes do this or something similar,

* [`JupiterMag`](https://github.com/mattkjames7/JupiterMag) - 
  A Python package that uses the 
  [`libjupitermag`](https://github.com/mattkjames7/libjupitermag) 
  C++ library (both written by Matt James).
* [`jovian_jrm09_internal`](https://github.com/marissav06/jovian_jrm09_internal_matlab), 
  [`con_2020`](https://github.com/marissav06/con2020_matlab) - Codes written for MATLAB and IDL by Marrisa Vogt. 
* [`con2020`](https://github.com/gabbyprovan/con2020) - Python code by Gabby Provan.

> More details on Jupiter magnetic field models and these codes 
> can be found in this paper - Wilson, R.J., Vogt, M.F., Provan, G. et al. **Internal and External Jovian 
> Magnetic Fields: Community Code to Serve the Magnetospheres of the Outer Planets
> Community.** Space Sci Rev 219, 15 (2023). 
> [https://doi.org/10.1007/s11214-023-00961-3](https://doi.org/10.1007/s11214-023-00961-3)

## Installation

### Installing using wheels on PyPI

If you are on Python versions 3.12 or 3.13, you can install directly using the wheels hosted 
on PyPI. This does not require you to install the Rust toolchain.

```shell
pip install iupitermag
```

If you are using a package manager like `uv`, you can also use the following commands. These will 
use the wheels uploaded on PyPI unless you are on a Python version or platform for which the wheels
are unavailable.

```shell
uv pip install iupitermag
```
To add to `uv.lock` and `pyproject.toml` in your projects, use -

```shell
uv add iupitermag
```

### Installing from source using `uv`

```shell
git clone https://github.com/ysar/iupitermag.git --depth=1
cd iupitermag
uv pip install .
```
### Installing from source using `maturin`

```shell
maturin develop --release
```

## Usage

### Calculating the internal and current sheet fields at a single point.

All positions should be in the IAU_JUPITER coordinate system.

```python
import numpy as np
import iupitermag as im

internal_field = im.InternalField("JRM33")
currentsheet_field = im.CurrentSheetField("CON2020")

r = 10.
theta = 0.
phi = 0.
b_int_rtp = internal_field.calc_field(r, theta, phi)
b_ext_rtp = currentsheet_field.calc_field(r, theta, phi)

# Or, you can the cartesian form.  This calls the spherical version internally.
x = 10.
y = 5.
z = 1.
b_int_xyz = internal_field.calc_field_xyz(x, y, z)
b_ext_xyz = currentsheet_field.calc_field_xyz(x, y, z)
```

### Calculating the internal and current sheet fields for a collection of points.

If you have a collection of points stored as a single numpy array of shape (N, 3), 
you can use `map_calc_field` or `parmap_calc_field` (or their corresponding 
cartesian versions `map_calc_field_xyz` and `parmap_calc_field_xyz`).

```python
# By default, iupitermag uses spherical coordinates (r, theta, phi)
points = np.zeros((10000, 3))
points[:, 0] = np.random.random_sample((10000,)) * 10 + 5

b_int = internal_field.map_calc_field(points)
b_ext = currentsheet_field.map_calc_field(points)

b_int = internal_field.parmap_calc_field(points)
b_ext = currentsheet_field.parmap_calc_field(points)

# Assume some cartesian coordinates in shape (N, 3)
points_xyz = points * 1.

b_int_xyz = internal_field.map_calc_field_xyz(points_xyz)
b_ext_xyz = currentsheet_field.map_calc_field_xyz(point_xyz)

b_int_xyz = internal_field.parmap_calc_field_xyz(points_xyz)
b_ext_xyz = currentsheet_field.parmap_calc_field_xyz(points_xyz)
```

The below figure shows the results of benchmarking different methods to calculate the JRM09 field 
for different number of points.  Show are 1) a pure Python implementation of the internal field,
2) a Python loop that calls `iupitermag`'s `calc_field` repeatedly on a number of points, 3) using
`map_calc_field` directly on a points collections, and 4) using `parmap_calc_field` on a points 
collection, which is similar to `map` but uses Rayon for parallelization.

![Benchmark](images/benchmark.png)

As you can see, `parmap_` is usually the better option if you have more than 20 or so points, at
least for this test that uses JRM33.  Compared to the pure-Python implementation, `parmap_` is 
about three orders of magnitude faster.

### Tracing magnetic field lines

`iupitermag` can trace magnetic field lines to Jupiter using `trace_field_to_planet`, which takes 
as input a collection of starting points (which each result in a separate trace).  The coordinates 
for these starting points should be cartesian.

```python
import numpy as np
import iupitermag as im

internal_field = im.InternalField("JRM33")
currentsheet_field = im.CurrentSheetField("CON2020")

starting_positions_xyz = np.array([
    [-10., 0., 0.],
    [-15., 0., 0.],
    [-20., 0., 0.],
    [-25., 0., 0.],
    [10., 0., 0.],
    [15., 0., 0.],
    [20., 0., 0.],
    [25., 0., 0.],
])

trace = im.trace_field_to_planet(starting_positions_xyz, internal_field, currentsheet_field)
```

![Traced field lines](images/traced_field_lines.png)

### Using a custom internal and current sheet field

To use your own internal field or current sheet model, use the "Custom" argument when instantiating 
a field object. The following example describes how to create an internal field for an 
axially-aligned dipole and defining new current sheet model that is similar to CON2020 but ignores 
the current sheet tilt.

```python
import numpy as np
import iupitermag as im

# Create a new axially aligned dipole field using Schmidt coefficients. 
# That is, only g[1, 0] is non-zero.
internal_field = im.InternalField(
    "Custom",
    g=np.array([[0.0, 0.0], [410993.4, 0.0]]),
    h=np.array([[0.0, 0.0], [0.0, 0.0]]),
)

# Get parameters for CON2020
con2020_field = im.CurrentSheetField("CON2020")
params = con2020_field.get_params()

# Change current sheet tilt to 0.0
params["theta_d"] = 0.0

# Define a modified current sheet field based on CON2020 parameters.
currentsheet_field = im.CurrentSheetField("Custom", params=params)

starting_positions = np.array(
    [
        [-10.0, 0.0, 0.0],
        [-15.0, 0.0, 0.0],
        [-20.0, 0.0, 0.0],
        [-25.0, 0.0, 0.0],
        [10.0, 0.0, 0.0],
        [15.0, 0.0, 0.0],
        [20.0, 0.0, 0.0],
        [25.0, 0.0, 0.0],
    ]
)

trace = im.trace_field_to_planet(
    starting_positions, internal_field, currentsheet_field
)
```

![Traced field lines (Custom field)](images/traced_field_lines_custom.png)

