black

Author: pdevis

comet_maths/__init__.py

@@ -1,4 +1,5 @@
 """comet_maths - Mathematical algorithms and tools to use within CoMet toolkit."""
+
 from comet_maths.generate_sample.generate_sample import (
     generate_sample,
     generate_error_sample,

comet_maths/generate_sample/generate_sample.py

@@ -1,4 +1,5 @@
 """describe class"""
+
 import copy
 import warnings
 
@@ -512,21 +513,39 @@ def generate_sample_correlated(
             if len(corr_x[i]) == len(u_x[i].ravel()):
                 # cov_x = cm.convert_corr_to_cov(corr_x[i], u_x[i])
                 MC_data = generate_sample_corr(
-                    MCsteps, x[i], u_x[i], corr_x[i], dtype=dtype, pdf_shape=pdf_shape, pdf_params=pdf_params
+                    MCsteps,
+                    x[i],
+                    u_x[i],
+                    corr_x[i],
+                    dtype=dtype,
+                    pdf_shape=pdf_shape,
+                    pdf_params=pdf_params,
                 )
             elif len(corr_x[i]) == len(u_x[i]):
                 MC_data = np.zeros((MCsteps,) + (u_x[i].shape))
                 for j in range(len(u_x[i][0])):
                     # cov_x = cm.convert_corr_to_cov(corr_x[i], u_x[i][:, j])
                     MC_data[:, :, j] = generate_sample_corr(
-                        MCsteps, x[i][:, j], u_x[i][:, j], corr_x[i], dtype=dtype, pdf_shape=pdf_shape, pdf_params=pdf_params
+                        MCsteps,
+                        x[i][:, j],
+                        u_x[i][:, j],
+                        corr_x[i],
+                        dtype=dtype,
+                        pdf_shape=pdf_shape,
+                        pdf_params=pdf_params,
                     )
             elif u_x[i].ndim > 1 and len(corr_x[i]) == len(u_x[i][0]):
                 MC_data = np.zeros((MCsteps,) + (u_x[i].shape))
                 for j in range(len(u_x[i][:, 0])):
                     # cov_x = cm.convert_corr_to_cov(corr_x[i], u_x[i][j])
                     MC_data[:, j, :] = generate_sample_corr(
-                        MCsteps, x[i][j], u_x[i][j], corr_x[i], dtype=dtype, pdf_shape=pdf_shape, pdf_params=pdf_params
+                        MCsteps,
+                        x[i][j],
+                        u_x[i][j],
+                        corr_x[i],
+                        dtype=dtype,
+                        pdf_shape=pdf_shape,
+                        pdf_params=pdf_params,
                     )
             else:
                 raise NotImplementedError(

comet_maths/generate_sample/probability_density_function.py

@@ -1,4 +1,5 @@
 """describe class"""
+
 import warnings
 
 """___Built-In Modules___"""

comet_maths/interpolation/interpolation.py

@@ -1,4 +1,4 @@
-""" Module for interpolation of data and enables propagation of uncertainties through the interpolation."""
+"""Module for interpolation of data and enables propagation of uncertainties through the interpolation."""
 
 from typing import Union, Optional, List, Tuple
 
@@ -108,9 +108,7 @@ def interpolate_1d_along_example(
             plot_residuals=self.plot_residuals,
         )
 
-    def interpolate_1d(
-        self, x_i: np.ndarray, y_i: np.ndarray, x: np.ndarray
-    ) -> Union[
+    def interpolate_1d(self, x_i: np.ndarray, y_i: np.ndarray, x: np.ndarray) -> Union[
         np.ndarray,
         Tuple[np.ndarray, np.ndarray],
         Tuple[np.ndarray, np.ndarray, np.ndarray],