[Fix] Remove mutables as default argument and fix smaller issues

pyerrors/__init__.py

@@ -1,4 +1,4 @@
-r'''
+r"""
 # What is pyerrors?
 `pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data.
 It is based on the gamma method [arXiv:hep-lat/0306017](https://arxiv.org/abs/hep-lat/0306017). Some of its features are:
@@ -476,7 +476,7 @@ def func(a, x):
 A JSON schema that may be used to verify the correctness of a file with respect to the format definition is stored in ./examples/json_schema.json. The schema is a self-descriptive format definition and contains an exemplary file.
 
 Julia I/O routines for the json.gz format, compatible with [ADerrors.jl](https://gitlab.ift.uam-csic.es/alberto/aderrors.jl), can be found [here](https://github.com/fjosw/ADjson.jl).
-'''
+"""
 from .obs import *
 from .correlators import *
 from .fits import *

pyerrors/correlators.py

@@ -42,7 +42,7 @@ class Corr:
 
     __slots__ = ["content", "N", "T", "tag", "prange"]
 
-    def __init__(self, data_input, padding=[0, 0], prange=None):
+    def __init__(self, data_input, padding=None, prange=None):
         """ Initialize a Corr object.
 
         Parameters
@@ -58,6 +58,8 @@ def __init__(self, data_input, padding=[0, 0], prange=None):
             region identified for this correlator.
         """
 
+        if padding is None:
+            padding = [0, 0]
         if isinstance(data_input, np.ndarray):
             if data_input.ndim == 1:
                 data_input = list(data_input)
@@ -105,7 +107,7 @@ def __init__(self, data_input, padding=[0, 0], prange=None):
                 self.N = noNull[0].shape[0]
                 if self.N > 1 and noNull[0].shape[0] != noNull[0].shape[1]:
                     raise ValueError("Smearing matrices are not NxN.")
-                if (not all([item.shape == noNull[0].shape for item in noNull])):
+                if not all([item.shape == noNull[0].shape for item in noNull]):
                     raise ValueError("Items in data_input are not of identical shape." + str(noNull))
             else:
                 raise TypeError("'data_input' contains item of wrong type.")
@@ -236,7 +238,7 @@ def symmetric(self):
                 newcontent.append(None)
             else:
                 newcontent.append(0.5 * (self.content[t] + self.content[self.T - t]))
-        if (all([x is None for x in newcontent])):
+        if all([x is None for x in newcontent]):
             raise ValueError("Corr could not be symmetrized: No redundant values")
         return Corr(newcontent, prange=self.prange)
 
@@ -300,7 +302,7 @@ def matrix_symmetric(self):
             return 0.5 * (Corr(transposed) + self)
 
     def GEVP(self, t0, ts=None, sort="Eigenvalue", vector_obs=False, **kwargs):
-        r'''Solve the generalized eigenvalue problem on the correlator matrix and returns the corresponding eigenvectors.
+        r"""Solve the generalized eigenvalue problem on the correlator matrix and returns the corresponding eigenvectors.
 
         The eigenvectors are sorted according to the descending eigenvalues, the zeroth eigenvector(s) correspond to the
         largest eigenvalue(s). The eigenvector(s) for the individual states can be accessed via slicing
@@ -333,12 +335,12 @@ def GEVP(self, t0, ts=None, sort="Eigenvalue", vector_obs=False, **kwargs):
            Method used to solve the GEVP.
            - "eigh": Use scipy.linalg.eigh to solve the GEVP. (default for vector_obs=False)
            - "cholesky": Use manually implemented solution via the Cholesky decomposition. Automatically chosen if vector_obs==True.
-        '''
+        """
 
         if self.N == 1:
             raise ValueError("GEVP methods only works on correlator matrices and not single correlators.")
         if ts is not None:
-            if (ts <= t0):
+            if ts <= t0:
                 raise ValueError("ts has to be larger than t0.")
 
         if "sorted_list" in kwargs:
@@ -786,7 +788,7 @@ def root_function(x, d):
             raise ValueError('Unknown variant.')
 
     def fit(self, function, fitrange=None, silent=False, **kwargs):
-        r'''Fits function to the data
+        r"""Fits function to the data
 
         Parameters
         ----------
@@ -799,7 +801,7 @@ def fit(self, function, fitrange=None, silent=False, **kwargs):
             If not specified, self.prange or all timeslices are used.
         silent : bool
             Decides whether output is printed to the standard output.
-        '''
+        """
         if self.N != 1:
             raise ValueError("Correlator must be projected before fitting")
 
@@ -878,6 +880,8 @@ def show(self, x_range=None, comp=None, y_range=None, logscale=False, plateau=No
         comp : Corr or list of Corr
             Correlator or list of correlators which are plotted for comparison.
             The tags of these correlators are used as labels if available.
+        y_range : list
+            list of two values, determining the range of the y-axis e.g. [0, 12].
         logscale : bool
             Sets y-axis to logscale.
         plateau : Obs
@@ -1093,7 +1097,7 @@ def __eq__(self, y):
 
     def __add__(self, y):
         if isinstance(y, Corr):
-            if ((self.N != y.N) or (self.T != y.T)):
+            if (self.N != y.N) or (self.T != y.T):
                 raise ValueError("Addition of Corrs with different shape")
             newcontent = []
             for t in range(self.T):
@@ -1338,21 +1342,21 @@ def __rtruediv__(self, y):
 
     @property
     def real(self):
-        def return_real(obs_OR_cobs):
-            if isinstance(obs_OR_cobs.flatten()[0], CObs):
-                return np.vectorize(lambda x: x.real)(obs_OR_cobs)
+        def return_real(obs_or_cobs):
+            if isinstance(obs_or_cobs.flatten()[0], CObs):
+                return np.vectorize(lambda x: x.real)(obs_or_cobs)
             else:
-                return obs_OR_cobs
+                return obs_or_cobs
 
         return self._apply_func_to_corr(return_real)
 
     @property
     def imag(self):
-        def return_imag(obs_OR_cobs):
-            if isinstance(obs_OR_cobs.flatten()[0], CObs):
-                return np.vectorize(lambda x: x.imag)(obs_OR_cobs)
+        def return_imag(obs_or_cobs):
+            if isinstance(obs_or_cobs.flatten()[0], CObs):
+                return np.vectorize(lambda x: x.imag)(obs_or_cobs)
             else:
-                return obs_OR_cobs * 0  # So it stays the right type
+                return obs_or_cobs * 0  # So it stays the right type
 
         return self._apply_func_to_corr(return_imag)
 
@@ -1396,7 +1400,7 @@ def prune(self, Ntrunc, tproj=3, t0proj=2, basematrix=None):
         if basematrix is None:
             basematrix = self
         if Ntrunc >= basematrix.N:
-            raise ValueError('Cannot truncate using Ntrunc <= %d' % (basematrix.N))
+            raise ValueError('Cannot truncate using Ntrunc <= %d' % basematrix.N)
         if basematrix.N != self.N:
             raise ValueError('basematrix and targetmatrix have to be of the same size.')
 
@@ -1495,7 +1499,7 @@ def eigv(x, **kwargs):
             def matmul(*operands):
                 return np.linalg.multi_dot(operands)
         N = Gt.shape[0]
-        output = [[] for j in range(N)]
+        output = [[] for _ in range(N)]
         if chol_inv is None:
             chol = cholesky(G0)  # This will automatically report if the matrix is not pos-def
             chol_inv = inv(chol)

pyerrors/dirac.py

@@ -32,8 +32,8 @@ def epsilon_tensor(i, j, k):
     elem : int
         Element (i,j,k) of the epsilon tensor of rank 3
     """
-    test_set = set((i, j, k))
-    if not (test_set <= set((1, 2, 3)) or test_set <= set((0, 1, 2))):
+    test_set = {i, j, k}
+    if not (test_set <= {1, 2, 3} or test_set <= {0, 1, 2}):
         raise ValueError("Unexpected input", i, j, k)
 
     return (i - j) * (j - k) * (k - i) / 2
@@ -50,8 +50,8 @@ def epsilon_tensor_rank4(i, j, k, o):
     elem : int
         Element (i,j,k,o) of the epsilon tensor of rank 4
     """
-    test_set = set((i, j, k, o))
-    if not (test_set <= set((1, 2, 3, 4)) or test_set <= set((0, 1, 2, 3))):
+    test_set = {i, j, k, o}
+    if not (test_set <= {1, 2, 3, 4} or test_set <= {0, 1, 2, 3}):
         raise ValueError("Unexpected input", i, j, k, o)
 
     return (i - j) * (j - k) * (k - i) * (i - o) * (j - o) * (o - k) / 12

pyerrors/fits.py

@@ -71,7 +71,7 @@ def __repr__(self):
 
 
 def least_squares(x, y, func, priors=None, silent=False, **kwargs):
-    r'''Performs a non-linear fit to y = func(x).
+    r"""Performs a non-linear fit to y = func(x).
         ```
 
     Parameters
@@ -224,7 +224,7 @@ def func_b(a, x):
     chisquare/d.o.f.: 0.5388013574561786 # random
     fit parameters [1.11897846 0.96361162 0.92325319] # random
 
-    '''
+    """
     output = Fit_result()
 
     if (isinstance(x, dict) and isinstance(y, dict) and isinstance(func, dict)):
@@ -504,7 +504,7 @@ def chisqfunc_compact(d):
 
 
 def total_least_squares(x, y, func, silent=False, **kwargs):
-    r'''Performs a non-linear fit to y = func(x) and returns a list of Obs corresponding to the fit parameters.
+    r"""Performs a non-linear fit to y = func(x) and returns a list of Obs corresponding to the fit parameters.
 
     Parameters
     ----------
@@ -553,7 +553,7 @@ def func(a, x):
     -------
     output : Fit_result
         Parameters and information on the fitted result.
-    '''
+    """
 
     output = Fit_result()
 

pyerrors/input/__init__.py

@@ -1,10 +1,10 @@
-r'''
+r"""
 `pyerrors` includes an `input` submodule in which input routines and parsers for the output of various numerical programs are contained.
 
 # Jackknife samples
 For comparison with other analysis workflows `pyerrors` can also 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.
-'''
+"""
 from . import bdio as bdio
 from . import dobs as dobs
 from . import hadrons as hadrons

pyerrors/input/dobs.py

@@ -85,7 +85,7 @@ def _dict_to_xmlstring_spaces(d, space='  '):
     return o
 
 
-def create_pobs_string(obsl, name, spec='', origin='', symbol=[], enstag=None):
+def create_pobs_string(obsl, name, spec='', origin='', symbol=None, enstag=None):
     """Export a list of Obs or structures containing Obs to an xml string
     according to the Zeuthen pobs format.
 
@@ -113,6 +113,8 @@ def create_pobs_string(obsl, name, spec='', origin='', symbol=[], enstag=None):
         XML formatted string of the input data
     """
 
+    if symbol is None:
+        symbol = []
     od = {}
     ename = obsl[0].e_names[0]
     names = list(obsl[0].deltas.keys())
@@ -176,7 +178,7 @@ def create_pobs_string(obsl, name, spec='', origin='', symbol=[], enstag=None):
     return rs
 
 
-def write_pobs(obsl, fname, name, spec='', origin='', symbol=[], enstag=None, gz=True):
+def write_pobs(obsl, fname, name, spec='', origin='', symbol=None, enstag=None, gz=True):
     """Export a list of Obs or structures containing Obs to a .xml.gz file
     according to the Zeuthen pobs format.
 
@@ -206,6 +208,8 @@ def write_pobs(obsl, fname, name, spec='', origin='', symbol=[], enstag=None, gz
     -------
     None
     """
+    if symbol is None:
+        symbol = []
     pobsstring = create_pobs_string(obsl, name, spec, origin, symbol, enstag)
 
     if not fname.endswith('.xml') and not fname.endswith('.gz'):
@@ -309,7 +313,7 @@ def read_pobs(fname, full_output=False, gz=True, separator_insertion=None):
     full_output : bool
         If True, a dict containing auxiliary information and the data is returned.
         If False, only the data is returned as list.
-    separatior_insertion: str or int
+    separator_insertion: str or int
         str: replace all occurences of "separator_insertion" within the replica names
         by "|%s" % (separator_insertion) when constructing the names of the replica.
         int: Insert the separator "|" at the position given by separator_insertion.
@@ -409,7 +413,7 @@ def import_dobs_string(content, full_output=False, separator_insertion=True):
     full_output : bool
         If True, a dict containing auxiliary information and the data is returned.
         If False, only the data is returned as list.
-    separatior_insertion: str, int or bool
+    separator_insertion: str, int or bool
         str: replace all occurences of "separator_insertion" within the replica names
         by "|%s" % (separator_insertion) when constructing the names of the replica.
         int: Insert the separator "|" at the position given by separator_insertion.
@@ -677,7 +681,7 @@ def _dobsdict_to_xmlstring_spaces(d, space='  '):
     return o
 
 
-def create_dobs_string(obsl, name, spec='dobs v1.0', origin='', symbol=[], who=None, enstags=None):
+def create_dobs_string(obsl, name, spec='dobs v1.0', origin='', symbol=None, who=None, enstags=None):
     """Generate the string for the export of a list of Obs or structures containing Obs
     to a .xml.gz file according to the Zeuthen dobs format.
 
@@ -708,6 +712,8 @@ def create_dobs_string(obsl, name, spec='dobs v1.0', origin='', symbol=[], who=N
     xml_str : str
         XML string generated from the data
     """
+    if symbol is None:
+        symbol = []
     if enstags is None:
         enstags = {}
     od = {}
@@ -866,7 +872,7 @@ def create_dobs_string(obsl, name, spec='dobs v1.0', origin='', symbol=[], who=N
     return rs
 
 
-def write_dobs(obsl, fname, name, spec='dobs v1.0', origin='', symbol=[], who=None, enstags=None, gz=True):
+def write_dobs(obsl, fname, name, spec='dobs v1.0', origin='', symbol=None, who=None, enstags=None, gz=True):
     """Export a list of Obs or structures containing Obs to a .xml.gz file
     according to the Zeuthen dobs format.
 
@@ -900,6 +906,8 @@ def write_dobs(obsl, fname, name, spec='dobs v1.0', origin='', symbol=[], who=No
     -------
     None
     """
+    if symbol is None:
+        symbol = []
     if enstags is None:
         enstags = {}
 

pyerrors/input/hadrons.py

@@ -245,7 +245,7 @@ def extract_t0_hd5(path, filestem, ens_id, obs='Clover energy density', fit_rang
     return fit_t0(t2E_dict, fit_range, plot_fit=kwargs.get('plot_fit'))
 
 
-def read_DistillationContraction_hd5(path, ens_id, diagrams=["direct"], idl=None):
+def read_DistillationContraction_hd5(path, ens_id, diagrams=None, idl=None):
     """Read hadrons DistillationContraction hdf5 files in given directory structure
 
     Parameters
@@ -265,6 +265,8 @@ def read_DistillationContraction_hd5(path, ens_id, diagrams=["direct"], idl=None
         extracted DistillationContration data
     """
 
+    if diagrams is None:
+        diagrams = ["direct"]
     res_dict = {}
 
     directories, idx = _get_files(path, "data", idl)
@@ -486,7 +488,7 @@ def read_Bilinear_hd5(path, filestem, ens_id, idl=None):
     return result_dict
 
 
-def read_Fourquark_hd5(path, filestem, ens_id, idl=None, vertices=["VA", "AV"]):
+def read_Fourquark_hd5(path, filestem, ens_id, idl=None, vertices=None):
     """Read hadrons FourquarkFullyConnected hdf5 file and output an array of CObs
 
     Parameters
@@ -508,6 +510,8 @@ def read_Fourquark_hd5(path, filestem, ens_id, idl=None, vertices=["VA", "AV"]):
         extracted fourquark matrizes
     """
 
+    if vertices is None:
+        vertices = ["VA", "AV"]
     files, idx = _get_files(path, filestem, idl)
 
     mom_in = None
@@ -596,7 +600,7 @@ def _get_lorentz_names(name):
     assert len(name) == 2
 
     if 'S' in name or 'P' in name:
-        if not set(name) <= set(['S', 'P']):
+        if not set(name) <= {'S', 'P'}:
             raise Exception("'" + name + "' is not a Lorentz scalar")
 
         g_names = {'S': 'Identity',
@@ -605,7 +609,7 @@ def _get_lorentz_names(name):
         res.append((g_names[name[0]], g_names[name[1]]))
 
     else:
-        if not set(name) <= set(['V', 'A']):
+        if not set(name) <= {'V', 'A'}:
             raise Exception("'" + name + "' is not a Lorentz scalar")
 
         for ind in lorentz_index:

pyerrors/input/openQCD.py

@@ -596,7 +596,9 @@ def _parse_array_openQCD2(d, n, size, wa, quadrupel=False):
     return arr
 
 
-def _find_files(path, prefix, postfix, ext, known_files=[]):
+def _find_files(path, prefix, postfix, ext, known_files=None):
+    if known_files is None:
+        known_files = []
     found = []
     files = []
 
@@ -1268,7 +1270,7 @@ def read_ms5_xsf(path, prefix, qc, corr, sep="r", **kwargs):
                 idl_wanted = True
                 if 'idl' in kwargs:
                     idl_wanted = (cnfg in expected_idl[repnum])
-                    left_idl = left_idl - set([cnfg])
+                    left_idl = left_idl - {cnfg}
                 if idl_wanted:
                     cnfgs[repnum].append(cnfg)