diff --git a/src/Class_Mod/RegModels.py b/src/Class_Mod/RegModels.py index 63e740d7f40a1ad9f4d55edd7865c242c16afd8e..49813dbdd93dc5ca4a2a08d0c413a202fb3cf2cb 100644 --- a/src/Class_Mod/RegModels.py +++ b/src/Class_Mod/RegModels.py @@ -98,6 +98,7 @@ class Plsr(Regmodel): ### parameters in common def objective(self, params): + params['n_components'] = int(params['n_components']) x0 = [self._xc, self._xt] x1 = [eval(str(params['normalization'])+"(x0[i])") for i in range(2)] @@ -130,6 +131,10 @@ class Plsr(Regmodel): self._yc = Model.predict(x2[0]) self._yt = Model.predict(x2[1]) self._model = Model + for key,value in params.items(): + try: params[key] = int(value) + except (TypeError, ValueError): params[key] = value + self._best = params self.pretreated = pd.DataFrame(x2[0]) self._sel_ratio = sel_ratio(Model, x2[0]) @@ -197,7 +202,11 @@ class TpeIpls(Regmodel): self._yc = Model.predict(x2[0][:,id]) self._yt = Model.predict(x2[1][:,id]) self._model = Model + for key,value in params.items(): + try: params[key] = int(value) + except (TypeError, ValueError): params[key] = value self._best = params + self.pretreated = pd.DataFrame(x2[0]) self.segments = arrays diff --git a/src/data/models/model_sd_2024_06_07__created_on_Xcal_and_Ycal_data_.pkl b/src/data/models/model_sd_2024_06_07__created_on_Xcal_and_Ycal_data_.pkl new file mode 100644 index 0000000000000000000000000000000000000000..0fa8d65d2256b43f3449286ef19eb701292ac298 Binary files /dev/null and b/src/data/models/model_sd_2024_06_07__created_on_Xcal_and_Ycal_data_.pkl differ diff --git a/src/data/models/model_sd_2024_06_07__on_Xcal_and_Ycal_data_Wavelengths_index.csv b/src/data/models/model_sd_2024_06_07__on_Xcal_and_Ycal_data_Wavelengths_index.csv new file mode 100644 index 0000000000000000000000000000000000000000..08a80dea3691c167a81a8d99332d02772d01cf99 --- /dev/null +++ b/src/data/models/model_sd_2024_06_07__on_Xcal_and_Ycal_data_Wavelengths_index.csv @@ -0,0 +1,4 @@ +;from;to +band1;353;409 +band2;501;882 +band3;1727;2020 diff --git a/src/data/params/Preprocessing.json b/src/data/params/Preprocessing.json new file mode 100644 index 0000000000000000000000000000000000000000..0d814e812cf256fe6987cd6d0eb048d02afc555e --- /dev/null +++ b/src/data/params/Preprocessing.json @@ -0,0 +1 @@ +{"deriv": 0, "n_components": 18, "normalization": "No_transformation", "polyorder": 0, "v1": 752, "v2": 735, "v3": 125, "v4": 1198, "v5": 461, "v6": 522, "window_length": 1} \ No newline at end of file diff --git a/src/pages/2-model_creation.py b/src/pages/2-model_creation.py index ddddd422e0d2879be1dbc0e651a1f826bc9e150a..8c31f316fb407aa9c3dacce3bb285f9f158783ee 100644 --- a/src/pages/2-model_creation.py +++ b/src/pages/2-model_creation.py @@ -293,9 +293,11 @@ if not spectra.empty and not y.empty: M1.write(Reg.best_hyperparams_print) a_Test=Reg.best_hyperparams_print + + with open("data/params/Preprocessing.json", "w") as outfile: + json.dump(Reg.best_hyperparams_, outfile) + - with open("data/params/Preprocessing.json", "w") as outfile: - json.dump(Reg.best_hyperparams_, outfile) ########## M1.write("-- Model performance --") M1.dataframe(metrics(c = [y_train, yc], t = [y_test, yt], method='regression').scores_)