<!---
SPDX-FileCopyrightText: 2022 Dominik Vilsmeier
SPDX-License-Identifier: GPL-3.0-or-later
-->
[](https://accinv.readthedocs.io/en/latest/)
[](https://pypi.org/project/accinv/)
[](https://pypi.org/project/accinv/)
# (acc)<sup>-1</sup>
*accinv - Python project for inverse modeling of accelerator lattices*
-----
**Note:** This project is in proof-of-concept stage and therefore lacks more advanced features
of some of the implemented methods.
-----
In its current state, the package provides functionality for inverse modeling of linear optics
via fitting of orbit response matrix (ORM) data, typically referred to as linear optics
from closed orbits. It supports [`cpymad`](https://pypi.org/project/cpymad/) as a backend.
The main class is `accinv.loco.Loco` which requires one of the models from `accinv.model`, as well as
a method for computing Jacobians, as an argument.
Two methods for Jacobian computation are available.
* `AnalyticalJacobianMethod`: This method uses an analytical formula to compute the Jacobian of the ORM
with respect to quadrupole gradient errors and BPM and steerer gain errors. The data for the
analytical formula is obtained from a single Twiss call for the current lattice configuration.
* `NumericalMJacobianMethod`: This method uses a finite difference approximation scheme to compute the Jacobian of
the ORM with respect to the quadrupole gradient errors. Thus, the number of ORMs that will be computed
is proportional to the number of quadrupoles.
The inverse modeling process can be started by creating a `Loco` object and calling its `run` method:
```py
from accinv.jacobian import AnalyticalJacobianMethod
from accinv.loco import Loco, OrmMeasurement
from accinv.model import Madx
model = Madx(path='path/to/script.madx')
loco = Loco(
model_and_jacobian_method=(model, AnalyticalJacobianMethod),
quadrupoles=[...], # names of quadrupoles
hbpms=[...], # names of horizontal BPMs
hsteerers=[...], # names of horizontal steerers
vbpms=[...], # names of vertical BPMs
vsteerers=[...], # names of vertical steerers
orm_measurement=OrmMeasurement(
orm=np.load('path/to/measured_orm.npy'),
uncertainty=np.load('path/to/orm_uncertainty.npy'),
),
)
result = loco.run()
```
Please consider the documentation of the
[`Loco` class](https://accinv.readthedocs.io/en/latest/api/accinv.loco.html#accinv.loco.Loco)
for more details.
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