Merge pull request #23 from MyPyDavid/fix/make-example-run

Fix/make example run

Author: MyPyDavid

.github/workflows/tox_actions.yml

@@ -27,7 +27,7 @@ jobs:
           - python-version: 3.9
             toxenv: "py39-cover,report" #,codecov"
         exclude:
-          # TODO py39 on windows has errors so we exclude it for now
+          # IDEA py39 on windows has errors so we exclude it for now
           - os: windows-latest
             python-version: 3.9
 

.gitignore

@@ -109,7 +109,7 @@ venv.bak/
 .mypy_cache/
 
 # pycharm
-.idea/
+.todo/
 
 # datafiles and results
 **/results/*

.pre-commit-config.yaml

@@ -49,7 +49,7 @@ repos:
         name: nbqa-black - consistent Python code formatting (notebooks; auto-fixes)
         args: [ --nbqa-mutate ]
         additional_dependencies: [ black==21.5b2 ]
-      # TODO: Disabled for now until it's clear how to add noqa to specific cells of a Jupyter notebook
+      # IDEA: Disabled for now until it's clear how to add noqa to specific cells of a Jupyter notebook
       #- id: nbqa-flake8
       #  name: nbqa-flake8 - Python linting (notebooks)
       #  additional_dependencies: [ flake8==3.9.2 ]

src/raman_fitting/__init__.py

@@ -23,7 +23,7 @@
 
 # VERSION_PATH = config.PACKAGE_ROOT / 'VERSION.txt'
 # with open(VERSION_PATH, 'r') as version_file:
-# TODO change version definitino
+# IDEA change version definitino
 # __version__ = version_file.read().strip()
 
 import logging
@@ -93,15 +93,3 @@
 # Other user-facing functions
 from .api import *
 
-# TODO list:
-# added setup.cfg
-# added unittests
-# added README.md
-# add project.toml only for
-# improved logger, each module needs a getlogger(name)
-# TODO future daemonize the fitting process for using the package and dropping files in the datafiles folder
-# TODO add docs with Sphinx, readthedocs
-# TODO improve AsyncIO into main delegator processes
-# TODO fix plotting because of DeprecationWarning in savefig
-# TODO add database for spectrum data storage
-# TODO future GUI webinterface

src/raman_fitting/config/filepath_helper.py

@@ -117,7 +117,7 @@ def create_dataset_dir(DATASET_DIR):  # pragma: no cover
 """
             )
             sys.exit()
-            # TODO build in daemon version with folder watcher....
+            # IDEA build in daemon version with folder watcher....
         except Exception as exc:
             logger.warning(
                 f"""The datafiles directory could not be created at:

src/raman_fitting/config/filepath_settings.py

@@ -60,7 +60,7 @@
 
 # ADAPT to your own configurations
 if 0:  # pragma: no cover
-    # TODO implement config file handling
+    # IDEA implement config file handling
     # LOCAL_CONFIG_FILE.is_file():
     try:
         # PACKAGE_ROOT, MODEL_DIR are not locally configurated

src/raman_fitting/deconvolution_models/base_model.py

@@ -111,7 +111,7 @@ class BaseModel:
     _SEP = "+"
     _SUFFIX = "_"
 
-    # TODO change include substrate to  has substrate and remove from init
+    # IDEA change include substrate to  has substrate and remove from init
     def __init__(
         self,
         model_name: str = "",
@@ -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/default_peaks/first_order_peaks.py

@@ -139,5 +139,5 @@ def __init__(self):
 
 def test_for_Si_substrate(
     model,
-):  # TODO test fit on spectrum to decide wether Si substrate is required or not
+):  # IDEA test fit on spectrum to decide wether Si substrate is required or not
     """make test fit for only slice 900-1000"""

src/raman_fitting/deconvolution_models/fit_models.py

@@ -14,7 +14,7 @@ class Fitter:
     """
     Fitter class for executing the fitting functions and optimizations
 
-    # TODO implement sensing of spectrum for Si samples
+    IDEA: implement sensing of spectrum for Si samples
     """
 
     fit_windows = ["1st_order", "2nd_order"]
@@ -48,7 +48,7 @@ def spectra(self, value):
             _fit_lbl = "int"
         elif isinstance(value, pd.DataFrame):
             raise AttributeError
-            # TODO implement self.sense_windowname(value)
+            # IDEA implement self.sense_windowname(value)
         else:
             raise ValueError(_errtxt)
 
@@ -112,7 +112,7 @@ def fit_models(self, model_selection):
         self.FitResults.update(**_fittings)
 
     def run_fit(self, model, _data, method="leastsq", **kws):
-        # TODO improve fitting loop so that starting parameters from modelX and modelX+Si are shared, faster...
+        # ideas: improve fitting loop so that starting parameters from modelX and modelX+Si are shared, faster...
         _fit_res, _param_res = {}, {}
         init_params = model.make_params()
         x, y = _data.ramanshift, _data[kws.get("_int_lbl")]
@@ -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:
@@ -206,15 +206,10 @@ def model_result(self, value):
             _mod_lbl = f'Model_{getattr(value,"_modelname")}'
         self.model_name_lbl = _mod_lbl
 
-        # TODO remove
-        # from pprint import pprint
-        # print('=====  /n',value._int_lbl,'/n')
-
         self.raw_data_lbl = value._int_lbl
 
         self._model_result = value
 
-        # TODO rewrite class and attirbuter setter
         self.make_result()
 
     def make_result(self):
@@ -335,7 +330,7 @@ def prep_components(self):
         _fit_comps_data = OrderedDict({"RamanShift": self.model_result.userkws["x"]})
         _fit_comps_data.update(self.model_result.eval_components())
 
-        # TODO take out
+        # IDEA take out
         # print('===/n',self.model_result, '/n')
         # print('===/n',self.model_result.__dict__.keys(), '/n')
 
@@ -344,7 +339,6 @@ def prep_components(self):
             {
                 self.model_name_lbl: self.model_result.best_fit,
                 "residuals": self.model_result.residual,
-                # TODO check attributes of model_result
                 self.model_result._int_lbl: self.model_result.data,
             }
         )
@@ -353,7 +347,7 @@ def prep_components(self):
 
 
 def NormalizeFit(norm_cleaner, plotprint=False):  # pragma: no cover
-    # TODO optional add normalization seperately to Fitter
+    # IDEA: optional add normalization seperately to Fitter
     x, y = norm_cleaner.spec.ramanshift, norm_cleaner.blcorr_desp_intensity
     Model = InitializeModels("2peaks normalization Lorentzian")
     params = Model.make_params()

src/raman_fitting/deconvolution_models/peak_validation.py

@@ -342,7 +342,7 @@ def __getattr__(self, name):
         # raise AttributeError(f'Chosen name "{name}" not in in options: "{", ".join(self.options)}".')
 
     def normalization_model(self):
-        pass  # TODO separate peaks in groups
+        pass  # IDEA separate peaks in groups
 
     def __iter__(self):
         for mod_inst in self.lmfit_models: