fix code smells

Author: MyPyDavid

src/raman_fitting/deconvolution_models/base_model.py

@@ -220,14 +220,14 @@ def add_substrate(self):
 
     def validate_model_name_input(self, value):
         """checks if given input name is valid"""
-        if not type(value) == str:
+        if type(value) != str:
             raise TypeError(
                 f'Given name "{value}" for model_name should be a string insteady of type({type(value).__name__})'
             )
         elif not value:
             warn(f'\n\tThis name "{value}" is an empty string', BaseModelWarning)
             return value
-        elif not "+" in value:
+        elif "+" not in value:
             warn(
                 f'\n\tThis name "{value}" does not contain the separator "+". (could be just 1 Peak)',
                 BaseModelWarning,

src/raman_fitting/deconvolution_models/fit_models.py

@@ -131,7 +131,7 @@ def run_fit(self, model, _data, method="leastsq", **kws):
     def get_int_label(self, value):
         _lbl = ""
         if isinstance(value, pd.DataFrame):
-            cols = [i for i in value.columns if not "ramanshift" in i]
+            cols = [i for i in value.columns if "ramanshift" not in i]
             if len(cols) == 0:
                 _lbl = ""
             if len(cols) == 1:

src/raman_fitting/delegating/main_delegator.py

@@ -247,20 +247,6 @@ def simple_process_sample_wrapper(self, *sID_args, **kwargs):
             self._failed_samples.append((e, sID_args, kwargs))
         return exporter_sample
 
-    def _process_sample_wrapper(self, fn, *args, **kwargs):
-        logger.warning(
-            f"{self._cqnm} process_sample_wrapper args:\n\t - {fn}\n\t - {args}\n\t - {kwargs.keys()}"
-        )
-        exp_sample = None
-        try:
-            exp_sample = fn(self, *args, **kwargs)
-            self.export_collect.append(exp_sample)
-        except Exception as e:
-            logger.warning(
-                f"{self._cqnm} process_sample_wrapper exception on call {fn}: {e}"
-            )
-            self._failed_samples.append((e, args, kwargs))
-
     def test_positions(
         self, sGrp_grp, sIDnm, grp_cols=["FileStem", "SamplePos", "FilePath"]
     ):

src/raman_fitting/exporting/plotting.py

@@ -117,6 +117,7 @@ def fit_spectrum_plot(
     plot_Residuals=True,
 ):  # pragma: no cover
 
+    modname_2 = peak2
     #%%
     sID = res1_peak_spec.extrainfo["SampleID"]
     SampleBgmean_col = res1_peak_spec.raw_data_col
@@ -178,14 +179,15 @@ def fit_spectrum_plot(
         c="grey",
         alpha=0.5,
     )
-    ax2ndRes.plot(
-        FitData_2nd["RamanShift"],
-        FitData_2nd[res2_peak_spec.raw_data_col] - FitData_2nd[Model_data_col_2nd],
-        label="Residual",
-        lw=3,
-        c="k",
-        alpha=0.8,
-    )
+    if plot_Residuals:
+        ax2ndRes.plot(
+            FitData_2nd["RamanShift"],
+            FitData_2nd[res2_peak_spec.raw_data_col] - FitData_2nd[Model_data_col_2nd],
+            label="Residual",
+            lw=3,
+            c="k",
+            alpha=0.8,
+        )
 
     for fit_comp_col_2nd in compscols_2nd:  # automatic color cycle 'cyan' ...
         ax2nd.plot(
@@ -227,14 +229,16 @@ def fit_spectrum_plot(
         c="grey",
         alpha=0.8,
     )
-    axRes.plot(
-        FitData_1st["RamanShift"],
-        FitData_1st[res1_peak_spec.raw_data_col] - FitData_1st[Model_data_col_1st],
-        label="Residual",
-        lw=3,
-        c="k",
-        alpha=0.8,
-    )
+    
+    if plot_Residuals:
+        axRes.plot(
+            FitData_1st["RamanShift"],
+            FitData_1st[res1_peak_spec.raw_data_col] - FitData_1st[Model_data_col_1st],
+            label="Residual",
+            lw=3,
+            c="k",
+            alpha=0.8,
+        )
 
     for fit_comp_col_1st in compscols_1st:  # automatic color cycle 'cyan' ...
         ax.plot(

src/raman_fitting/indexing/filedata_parser.py

@@ -10,10 +10,7 @@
 
 import numpy as np
 import pandas as pd
-# from pandas.core.base import DataError
-# from pandas.core.frame import DataFrame
 
-# from .. import __package_name__
 
 logger = logging.getLogger(__name__)
 
@@ -121,7 +118,7 @@ def spectrum_parser(self, filepath: Path):
     def use_np_loadtxt(self, filepath, usecols=(0, 1), **kwargs):
 
         try:
-            loaded_array = np.loadtxt(filepath, usecols=(0, 1), **kwargs)
+            loaded_array = np.loadtxt(filepath, usecols=usecols, **kwargs)
         except IndexError:
             logger.debug(f"IndexError called np genfromtxt for {filepath}")
             loaded_array = np.genfromtxt(filepath, invalid_raise=False)

src/raman_fitting/processing/spectrum_constructor.py

@@ -89,7 +89,7 @@ def load_data_delegator(self):
         if self.info:
             FP_from_info = self.info.get("FilePath", None)
             if FP_from_info:
-                if not Path(FP_from_info) == self.file:
+                if Path(FP_from_info) != self.file:
                     raise ValueError(
                         f"Mismatch in value for FilePath:\{self.file} != {FP_from_info}"
                     )
@@ -307,7 +307,7 @@ def check_members(spectra: List[SpectrumDataLoader]):
         _false_spectra = [
             spec
             for spec in spectra
-            if not type(spec) == SpectrumDataLoader or not hasattr(spec, "clean_data")
+            if type(spec) != SpectrumDataLoader or not hasattr(spec, "clean_data")
         ]
         if _false_spectra:
             logger.warning(