updated black config file to match flake8 config and added changes by…

… black autoformatter

kafe2/config/__init__.py

@@ -25,21 +25,16 @@ class ConfigError(Exception):
 
 class ConfigLookupError(ConfigError):
     def __init__(self, key_path, problematic_key_index):
-        self.message = "Error getting config key for '{}': no node under that path!".format(
-            ", ".join(key_path)
-        )
+        self.message = "Error getting config key for '{}': no node under that path!".format(", ".join(key_path))
         self.message = "Error getting config key for '{}': " "cannot find config node '{}'!".format(
             ", ".join(key_path), key_path[problematic_key_index]
         )
 
 
 class ConfigTypeError(ConfigError):
     def __init__(self, key_path, problematic_key_index):
-        self.message = (
-            "Error getting config key for '{}': "
-            "scalar node '{}' encountered inside path!".format(
-                ", ".join(key_path), key_path[problematic_key_index]
-            )
+        self.message = "Error getting config key for '{}': " "scalar node '{}' encountered inside path!".format(
+            ", ".join(key_path), key_path[problematic_key_index]
         )
 
 
@@ -97,11 +92,7 @@ def kc(*keys):
     if mpl.__version__.startswith("2"):
         kafe2_rc = mpl.rc_params_from_file(os.path.join(__path__[0], "kafe2.matplotlibrc.conf"))
         try:  # look for local config
-            kafe2_rc.update(
-                mpl.rc_params_from_file(
-                    os.path.join(os.getcwd(), "kafe2.matplotlibrc.conf"), use_default_template=False
-                )
-            )
+            kafe2_rc.update(mpl.rc_params_from_file(os.path.join(os.getcwd(), "kafe2.matplotlibrc.conf"), use_default_template=False))
         except IOError:
             pass
     elif mpl.__version__.startswith("3"):
@@ -114,11 +105,7 @@ def kc(*keys):
                 _temp_file.write("\n".encode())
         kafe2_rc = mpl.rc_params_from_file(_temp_file.name)
         try:  # look for local config, assume correct mpl3 handling
-            kafe2_rc.update(
-                mpl.rc_params_from_file(
-                    os.path.join(os.getcwd(), "kafe2.matplotlibrc.conf"), use_default_template=False
-                )
-            )
+            kafe2_rc.update(mpl.rc_params_from_file(os.path.join(os.getcwd(), "kafe2.matplotlibrc.conf"), use_default_template=False))
         except IOError:
             pass
         _temp_file.close()

kafe2/core/confidence.py

@@ -51,9 +51,7 @@ def cl(self) -> float:
     @cl.setter
     def cl(self, new_cl: float):
         if new_cl <= 0 or new_cl >= 1:
-            raise ValueError(
-                "Confidence level must be greater than 0 and less than 1. Got: %g" % (new_cl,)
-            )
+            raise ValueError("Confidence level must be greater than 0 and less than 1. Got: %g" % (new_cl,))
         self._cl = float(new_cl)
         self._sigma = None
 
@@ -87,9 +85,7 @@ def ndim(self):
     @ndim.setter
     def ndim(self, new_ndim):
         if not isinstance(new_ndim, int):
-            raise ValueError(
-                "Number of dimensions must be of type int! Received type: %s" % type(new_ndim)
-            )
+            raise ValueError("Number of dimensions must be of type int! Received type: %s" % type(new_ndim))
         if new_ndim <= 0:
             raise ValueError("Number of dimensions must be greater 0! Received: %d" % (new_ndim,))
         self._ndim = new_ndim

kafe2/core/constraint.py

@@ -121,9 +121,7 @@ def cost(self, parameter_values):
 
 
 class GaussianMatrixParameterConstraint(ParameterConstraint):
-    def __init__(
-        self, indices, values, matrix, matrix_type="cov", uncertainties=None, relative=False
-    ):
+    def __init__(self, indices, values, matrix, matrix_type="cov", uncertainties=None, relative=False):
         """
         Advanced class for applying correlated constraints to several parameters of a fit.
         The order of ``indices``, ``values``, ``matrix``, and ``uncertainties`` must be aligned.
@@ -159,9 +157,7 @@ def __init__(
             pass
         elif matrix_type == "cor":
             if np.any(np.diag(_matrix_array) != 1.0):
-                raise ValueError(
-                    "The correlation matrix has diagonal elements that aren't equal to 1!"
-                )
+                raise ValueError("The correlation matrix has diagonal elements that aren't equal to 1!")
             if np.any(_matrix_array > 1.0):
                 raise ValueError("The correlation matrix has elements greater than 1!")
             if np.any(_matrix_array < -1.0):
@@ -229,9 +225,7 @@ def cov_mat_rel(self):
             if self.matrix_type == "cov":
                 self._cov_mat_rel = self._cov_mat_abs / np.outer(self.values, self.values)
             else:
-                self._cov_mat_rel = self._cor_mat * np.outer(
-                    self.uncertainties_rel, self.uncertainties_rel
-                )
+                self._cov_mat_rel = self._cor_mat * np.outer(self.uncertainties_rel, self.uncertainties_rel)
         return self._cov_mat_rel
 
     @property
@@ -240,9 +234,7 @@ def cor_mat(self):
         if self._cor_mat is None:
             # if the originally specified cov mat was relative, calculate the cor mat based on that
             if self._relative:
-                self._cor_mat = self.cov_mat_rel / np.outer(
-                    self.uncertainties_rel, self.uncertainties_rel
-                )
+                self._cor_mat = self.cov_mat_rel / np.outer(self.uncertainties_rel, self.uncertainties_rel)
             else:
                 self._cor_mat = self.cov_mat / np.outer(self.uncertainties, self.uncertainties)
         return self._cor_mat

kafe2/core/contour.py

@@ -7,9 +7,7 @@ def create_xy_contour(xy_points, sigma):
         xy_points = np.asarray(xy_points)
         _shape = xy_points.shape
         if len(_shape) != 2 or (_shape[0] != 2 and _shape[1] != 2):
-            raise ValueError(
-                "Explicit contours can only be created from iterables with shape (2,n) or (n,2)."
-            )
+            raise ValueError("Explicit contours can only be created from iterables with shape (2,n) or (n,2).")
         if _shape[0] != 2:
             xy_points = xy_points.T
         return Contour(xy_points=xy_points, sigma=sigma)

kafe2/core/error.py

@@ -52,11 +52,7 @@ def __add__(self, other):
         return _new
 
     def __eq__(self, other):
-        return (
-            np.all(self._mat == other.mat)
-            if isinstance(other, CovMat)
-            else np.all(self._mat == other)
-        )
+        return np.all(self._mat == other.mat) if isinstance(other, CovMat) else np.all(self._mat == other)
 
     def __len__(self):
         return self._size
@@ -98,9 +94,7 @@ def mat(self, matrix):
 
         self._mat = np.array(matrix)
         if self._mat.ndim != 2 or self._mat.shape[0] != self._mat.shape[1]:
-            raise ValueError(
-                "Covariance matrix must be square matrix, shape %r given." % (self._mat.shape,)
-            )
+            raise ValueError("Covariance matrix must be square matrix, shape %r given." % (self._mat.shape,))
         self._size = self._mat.shape[0]
         self._cond = None
 
@@ -211,9 +205,7 @@ def reference(self, reference):
             _ref = np.asarray(reference, dtype=float)
             # check for zero-valued references if error is marked 'relative'
             if self.relative and np.any(_ref == 0):
-                warnings.warn(
-                    "Relative error has a reference that contains values equal to zero: %s" % _ref
-                )
+                warnings.warn("Relative error has a reference that contains values equal to zero: %s" % _ref)
             self._reference = _ref
 
         # invalidate error_structures opposite declared relativity type
@@ -314,9 +306,7 @@ def __init__(self, err_val, corr_coeff, relative=False, reference=None, fit_indi
             raise ValueError("Correlation must be between 0 and 1, %g given," % (corr_coeff,))
         err_val = np.asarray(err_val)
         if err_val.ndim != 1:
-            raise ValueError(
-                f"Error must be one-dimensional but received array with {err_val.ndim} dimensions."
-            )
+            raise ValueError(f"Error must be one-dimensional but received array with {err_val.ndim} dimensions.")
         self._corr_coeff = float(corr_coeff)
         self._is_relative = relative
         self.reference = reference
@@ -348,9 +338,7 @@ def _calculate_cov_mat(self):
         """Calculate absolute covariance matrix for error object."""
         if self.relative:
             if self.reference is None:
-                raise AttributeError(
-                    "Requested 'absolute' errors for error object declared 'relative', but 'reference' not set!"
-                )
+                raise AttributeError("Requested 'absolute' errors for error object declared 'relative', but 'reference' not set!")
             _abs_err = self.error_rel * self.reference
         else:
             _abs_err = self.error
@@ -387,9 +375,7 @@ def error(self):
         # calculate relative error from absolute error (if 'reference' is set)
         if self.relative:
             if self.reference is None:
-                raise AttributeError(
-                    "Requested 'absolute' errors for error object declared 'relative', but 'reference' not set!"
-                )
+                raise AttributeError("Requested 'absolute' errors for error object declared 'relative', but 'reference' not set!")
             self._err = self._err_rel * np.abs(self.reference)
         return self._err
 
@@ -400,9 +386,7 @@ def error(self, err_val):
             raise ValueError("Error values must be >= 0. Received: %s" % err_val)
         if self.relative:
             if self.reference is None:
-                raise AttributeError(
-                    "Setting 'absolute' errors for error object declared 'relative', but 'reference' not set!"
-                )
+                raise AttributeError("Setting 'absolute' errors for error object declared 'relative', but 'reference' not set!")
 
             self._err = err_val
             self._err_rel = err_val / np.abs(self.reference)
@@ -439,9 +423,7 @@ def error_rel(self):
         # calculate relative error from absolute error (if 'reference' is set)
         if not self.relative:
             if self.reference is None:
-                raise AttributeError(
-                    "Requested 'relative' errors for error object declared 'absolute', but 'reference' not set!"
-                )
+                raise AttributeError("Requested 'relative' errors for error object declared 'absolute', but 'reference' not set!")
             self._err_rel = self._err / np.abs(self.reference)
         return self._err_rel
 
@@ -455,9 +437,7 @@ def error_rel(self, err_val):
             self._err_rel = err_val
         else:
             if self.reference is None:
-                raise AttributeError(
-                    "Setting 'absolute' errors for error object declared 'relative', but 'reference' not set!"
-                )
+                raise AttributeError("Setting 'absolute' errors for error object declared 'relative', but 'reference' not set!")
             self._err = err_val * self.reference
             self._err_rel = err_val
 
@@ -558,15 +538,9 @@ def __init__(
         err_matrix = np.asarray(err_matrix)
         err_val = err_val if err_val is None else np.asarray(err_val)
         if err_matrix.ndim != 2:
-            raise ValueError(
-                "Error matrix must be two-dimensional but received "
-                f"array with {err_matrix.ndim} dimensions."
-            )
+            raise ValueError("Error matrix must be two-dimensional but received " f"array with {err_matrix.ndim} dimensions.")
         if err_val is not None and err_val.ndim > 1:
-            raise ValueError(
-                "Error array must be scalar or one-dimensional but received "
-                f"array with {err_val.ndim} dimensions."
-            )
+            raise ValueError("Error array must be scalar or one-dimensional but received " f"array with {err_val.ndim} dimensions.")
         self._is_relative = relative
         self.reference = reference
         self._fit_indices = fit_indices
@@ -588,19 +562,14 @@ def __init__(
         elif matrix_type.lower() in ("correlation", "correlations", "cor", "corr"):
             self._matrix_type_at_construction = "correlation"
             if err_val is None:
-                raise ValueError(
-                    "Cannot construct matrix-type error from correlation matrix "
-                    "without an array of error values!"
-                )
+                raise ValueError("Cannot construct matrix-type error from correlation matrix " "without an array of error values!")
             _cm = self._calculate_cov_mat_from_cor_mat_and_error_array(err_val, err_matrix)
             if self.relative:
                 self.cov_mat_rel = _cm
             else:
                 self.cov_mat = _cm
         else:
-            raise ValueError(
-                "Unknown matrix type '%s'. Expected one of: %r" % (matrix_type, ("cov", "cor"))
-            )
+            raise ValueError("Unknown matrix type '%s'. Expected one of: %r" % (matrix_type, ("cov", "cor")))
 
     # -- static methods
 
@@ -613,8 +582,7 @@ def _calculate_cov_mat_from_cor_mat_and_error_array(error_array, corr_mat):
         # TODO: check if corr_mat is symmetric and positive definite (?)
         if error_array.ndim > 0 and error_array.shape[0] != corr_mat.shape[0]:
             raise ValueError(
-                f"Error array has size {error_array.shape[0]} but "
-                f"correlation matrix has size {corr_mat.shape[0]}, must be the same."
+                f"Error array has size {error_array.shape[0]} but " f"correlation matrix has size {corr_mat.shape[0]}, must be the same."
             )
         cov_mat = np.asarray(np.outer(error_array, error_array)) * np.asarray(corr_mat)
         return CovMat(cov_mat)
@@ -645,10 +613,7 @@ def cov_mat(self):
         """"""
         if self.relative:
             if self.reference is None:
-                raise AttributeError(
-                    "Requested 'absolute' covariance matrix for error object declared 'relative', "
-                    "but 'reference' not set!"
-                )
+                raise AttributeError("Requested 'absolute' covariance matrix for error object declared 'relative', " "but 'reference' not set!")
             self._cov_mat = self._calculate_cov_mat_from_cov_rel(self.cov_mat_rel, self.reference)
         return self._cov_mat.mat
 
@@ -663,9 +628,7 @@ def cov_mat_rel(self):
         """"""
         if not self.relative:
             if self.reference is None:
-                raise AttributeError(
-                    "Requested 'relative' covariance matrix for error object declared 'absolute', but 'reference' not set!"
-                )
+                raise AttributeError("Requested 'relative' covariance matrix for error object declared 'absolute', but 'reference' not set!")
             self._cov_mat_rel = self._calculate_cov_mat_rel_from_cov(self.cov_mat, self.reference)
         return self._cov_mat_rel.mat
 
@@ -686,9 +649,7 @@ def error(self):
         if self._err is None:
             if self.relative:
                 if self.reference is None:
-                    raise AttributeError(
-                        "Requested 'absolute' error array for error object declared 'relative', but 'reference' not set!"
-                    )
+                    raise AttributeError("Requested 'absolute' error array for error object declared 'relative', but 'reference' not set!")
             self._err = np.sqrt(np.diag(self.cov_mat))
         return self._err
 
@@ -698,9 +659,7 @@ def error_rel(self):
         if self._err_rel is None:
             if not self.relative:
                 if self.reference is None:
-                    raise AttributeError(
-                        "Requested 'relative' error array for error object declared 'absolute', but 'reference' not set!"
-                    )
+                    raise AttributeError("Requested 'relative' error array for error object declared 'absolute', but 'reference' not set!")
             self._err_rel = np.sqrt(np.diag(self.cov_mat_rel))
         return self._err_rel
 

kafe2/core/fitters/__init__.py

@@ -33,9 +33,7 @@ def get_fitter(fitter_spec):
         _fitter = AVAILABLE_FITTERS.get(fitter_spec, None)
 
     if _fitter is None:
-        raise ValueError(
-            "Unknown fitter '{}'! Available: {}".format(fitter_spec, AVAILABLE_FITTERS.keys())
-        )
+        raise ValueError("Unknown fitter '{}'! Available: {}".format(fitter_spec, AVAILABLE_FITTERS.keys()))
 
     return _fitter