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docs: documentation for matrix operations extended, docstrings in

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input.misc fixed
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Fabian Joswig 2022-01-21 14:53:55 +00:00
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pyerrors/__init__.py
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@ -161,7 +161,7 @@ Passing arguments to the `gamma_method` still dominates over the dictionaries.
## Irregular Monte Carlo chains
Irregular Monte Carlo chains can be initialized with the parameter `idl`.
`Obs` objects defined on irregular Monte Carlo chains can be initialized with the parameter `idl`.
```python
# Observable defined on configurations 20 to 519
@ -187,6 +187,8 @@ obs3.details()
```
`Obs` objects defined on regular and irregular histories of the same ensemble can be computed with each other and the correct error propagation and estimation is automatically taken care of.
**Warning:** Irregular Monte Carlo chains can result in odd patterns in the autocorrelation functions.
Make sure to check the autocorrelation time with e.g. `pyerrors.obs.Obs.plot_rho` or `pyerrors.obs.Obs.plot_tauint`.
@ -241,7 +243,7 @@ my_new_corr = 0.3 * my_corr[2] * my_corr * my_corr + 12 / my_corr
- `Corr.correlate` constructs a disconnected correlation function from the correlator and another `Corr` or `Obs` object.
- `Corr.reweight` reweights the correlator.
`pyerrors` can also handle matrices of correlation functions and extract energy states from these matrices via a generalized eigenvalue problem (see `pyerrors.correlators.Corr.GEVP).
`pyerrors` can also handle matrices of correlation functions and extract energy states from these matrices via a generalized eigenvalue problem (see `pyerrors.correlators.Corr.GEVP`).
For the full API see `pyerrors.correlators.Corr`.
@ -273,17 +275,26 @@ print(my_derived_cobs)
`pyerrors.roots`
# Matrix operations
`pyerrors.linalg`
`pyerrors` provides wrappers for `Obs`-valued matrix operations based on `numpy.linalg`. The supported functions include:
- `inv` for the matrix inverse.
- `cholseky` for the Cholesky decomposition.
- `det` for the matrix determinant.
- `eigh` for eigenvalues and eigenvectors of hermitean matrices.
- `eig` for eigenvalues of general matrices.
- `pinv` for the Moore-Penrose pseudoinverse.
- `svd` for the singular-value-decomposition.
For the full API see `pyerrors.linalg`.
# Export data
The preferred exported file format within `pyerrors` is
The preferred exported file format within `pyerrors` is json.gz
## Jackknife samples
For comparison with other analysis workflows `pyerrors` can generate jackknife samples from an `Obs` object or import jackknife samples into an `Obs` object.
See `pyerrors.obs.Obs.export_jackknife` and `pyerrors.obs.import_jackknife` for details.
# Input
`pyerrors.input`
`pyerrors` includes an `input` submodule in which input routines and parsers for the output of various numerical programs are contained. For details see `pyerrors.input`.
'''
from .obs import *
from .correlators import *