Metadata-Version: 2.1
Name: linsolve
Version: 1.1.5
Summary: high-level tools for linearizing and solving systems of equations
Author: HERA Team
License: MIT License
        
        Copyright (c) 2017 Hydrogen Epoch of Reionization Array (HERA)
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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Project-URL: Repository, https://github.com/HERA-Team/linsolve
Keywords: linear equations,optimal estimation
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.23
Requires-Dist: scipy
Provides-Extra: test
Requires-Dist: pytest; extra == "test"
Requires-Dist: pytest-cov; extra == "test"
Provides-Extra: dev
Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: linsolve[test]; extra == "dev"

# linsolve

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`linsolve` is a module providing high-level tools for linearizing and solving systems of equations.

# Overview

The solvers in `linsolve` include `LinearSolver`, `LogProductSolver`, and `LinProductSolver`.
`LinearSolver` solves linear equations of the form `'a*x + b*y + c*z'`.
`LogProductSolver` uses logrithms to linearize equations of the form `'x*y*z'`.
`LinProductSolver` uses symbolic Taylor expansion to linearize equations of the
form `'x*y + y*z'`.

See [linsolve_example.ipynb](linsolve_example.ipynb) for a tutorial on how to use these functionalities.

---

Below we give a brief example on the general usage of `LinearSolver`.

Assume we have a linear system of equations, with a data vector `y` containing measurements
and a model vector `b` containing parameters we would like to solve for. Let's simplify to
the problem of fitting a line to three data points, which amounts to solving for a slope and an offset.
In this case, our linear system of equations can be written as

<img align='center' src="imgs/linear_model.png" width=300/>

where `b_1` is the slope and `b_2` is the offset, and the `A` matrix contains the mapping
from model vector `b` to data vector `y`. In our case, the `a_x1` values are the x-values of the data points, and the `a_x2` values are equal to unity. Let's assume the data vector measurements are `y_1 = 2`, `y_2 = 4` and `y_3 = 7`, and their corresponding dependent variable values are `a_11 = 0`, `a_21 = 2` and `a_31 = 4`.

<img align='center' src="imgs/points.png" width=300/>

We will use `LinearSolver` to solve this system of equations in the following manner.
First we setup a data dictionary, which contains as keys strings of the RHS of our linear model equation,
and as values the y-data measurements:

```python
data = {'b_2': 2.0, '2.0*b_1 + b_2': 4.0, '4*b_1 + b_2': 7.0}
```

Alternatively, we can write the data dictionary more generally by also writing dictionary of constants we don't want to solve for (i.e. the values of the `A` matrix):

```python
data = {'a_11*b_1 + a_12*b_2': 2.0, 'a_21*b_1 + a_22*b_2': 4.0, 'a_31*b_1 + a_32*b_2': 7.0}
consts = {'a_11': 0.0, 'a_21': 2.0, 'a_31': 4.0, 'a_12': 1.0, 'a_22': 1.0, 'a_32': 1.0}
```

We then feed this into `linsolve.LinearSolver` (optionally passing the `consts` dictionary as keyword arguments.)

```python
ls = linsolve.LinearSolver(data) # or linsolve.LinearSolver(data, **consts) if we use constants
solution = ls.solve()
```

The output, `solution`, is a dictionary with solution of our model vector:

```python
{'b_1': 1.2499999999999998, 'b_2': 1.8333333333333324}
```

Weighting of measurements can be implemented through an optional wgts
dictionary that parallels the construction of data. To see a more in-depth example,
please consult the [linsolve_example.ipynb](linsolve_example.ipynb) tutorial.

---

# Package Details
## Known Issues and Planned Improvements

For details see the [issue log](https://github.com/HERA-Team/linsolve/issues).

## Community Guidelines
Contributions to this package to add new file formats or address any of the
issues in the [issue log](https://github.com/HERA-Team/linsolve/issues) are very welcome.
Please submit improvements as pull requests against the repo after verifying that
the existing tests pass and any new code is well covered by unit tests.

Bug reports or feature requests are also very welcome, please add them to the
issue log after verifying that the issue does not already exist.
Comments on existing issues are also welcome.

# Installation
Preferred method of installation is `pip install .`
(or `pip install git+https://github.com/HERA-Team/linsolve`). This will install all
dependencies. See below for manual management of dependencies.

## Dependencies
If you use `conda` and would like to ensure that dependencies are installed with `conda`
rather than `pip`, you should execute::

    $ conda install "numpy>=1.14" scipy


## Development
If you are developing `linsolve`, it is recommended to create a fresh environment by::

    $ git clone https://github.com/HERA-Team/linsolve.git
    $ cd linsolve
    $ conda create -n linsolve python=3
    $ conda activate linsolve
    $ conda env update -n linsolve -f environment.yml
    $ pip install -e .

This will install extra dependencies required for testing/development as well as the
standard ones.

To run tests, just run `nosetests` in the top-level directory.
