docs: documentation for matrix operations extended, docstrings in

input.misc fixed

pyerrors/__init__.py

@@ -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 *

pyerrors/input/misc.py

@@ -1,6 +1,3 @@
-#!/usr/bin/env python
-# coding: utf-8
-
 import os
 import fnmatch
 import re
@@ -12,11 +9,12 @@ from ..obs import Obs
 def read_pbp(path, prefix, **kwargs):
     """Read pbp format from given folder structure. Returns a list of length nrw
 
-    Keyword arguments
-    -----------------
-    r_start -- list which contains the first config to be read for each replicum
-    r_stop -- list which contains the last config to be read for each replicum
-
+    Parameters
+    ----------
+    r_start : list
+        list which contains the first config to be read for each replicum
+    r_stop : list
+        list which contains the last config to be read for each replicum
     """
 
     extract_nfct = 1
@@ -66,7 +64,6 @@ def read_pbp(path, prefix, **kwargs):
         tmp_array = []
         with open(path + '/' + ls[rep], 'rb') as fp:
 
-            # header
             t = fp.read(4)  # number of reweighting factors
             if rep == 0:
                 nrw = struct.unpack('i', t)[0]
@@ -74,7 +71,7 @@ def read_pbp(path, prefix, **kwargs):
                     deltas.append([])
             else:
                 if nrw != struct.unpack('i', t)[0]:
-                    raise Exception('Error: different number of reweighting factors for replicum', rep)
+                    raise Exception('Error: different number of factors for replicum', rep)
 
             for k in range(nrw):
                 tmp_array.append([])