Further disable prophet

dash/requirements.txt

@@ -26,7 +26,7 @@ numpy==1.22.4
 openpyxl==3.0.10
 pandas==1.4.2
 plotly==5.8.0
-prophet==1.1
+#prophet==1.1
 python-dateutil==2.8.2
 python-slugify==6.1.2
 pytz==2022.1

updater/models.py

@@ -13,7 +13,7 @@
 
 import torch
 
-from prophet import Prophet
+# from prophet import Prophet
 
 import warnings
 
@@ -681,47 +681,47 @@ class RComb(RDirectForecastModel):
     r_forecast_model_name = "comb"
 
 
-# prophet model
-class FBProphet(ForecastModel):
-    name = "facebook-prophet"
-
-    method = "facebook-prophet"
-
-    def fit(self, y):
-        # rename two column as `date` and `y` per prophet requirement
-        self.y = y.reset_index().rename(columns={"date": "ds", "value": "y"})
-
-        self.model = Prophet().fit(self.y)
-
-    def _make_future(self):
-        """make future dataframe for prediction"""
-        return self.model.make_future_dataframe(periods=self.h).tail(self.h)
-
-    def predict(self):
-        # make future prediction dataframe
-        future = self._make_future()
-        return self.model.predict(future)["yhat"].to_numpy()
-
-    def predict_withci(self):
-        future = self._make_future()
-        forecast_dict = {"forecast": self.predict()}
-
-        for i in range(len(self.level)):
-            self.model.interval_width = self.level[i] * 0.01
-            forecast_df = self.model.predict(future)
-
-            # add intervals
-            forecast_dict[f"LB_{self.level[i]}"] = forecast_df[
-                "yhat_lower"
-            ].to_numpy()
-            forecast_dict[f"UB_{self.level[i]}"] = forecast_df[
-                "yhat_upper"
-            ].to_numpy()
-
-        return forecast_dict
-
-    def description(self):
-        return self.model
+# # prophet model
+# class FBProphet(ForecastModel):
+#     name = "facebook-prophet"
+#
+#     method = "facebook-prophet"
+#
+#     def fit(self, y):
+#         # rename two column as `date` and `y` per prophet requirement
+#         self.y = y.reset_index().rename(columns={"date": "ds", "value": "y"})
+#
+#         self.model = Prophet().fit(self.y)
+#
+#     def _make_future(self):
+#         """make future dataframe for prediction"""
+#         return self.model.make_future_dataframe(periods=self.h).tail(self.h)
+#
+#     def predict(self):
+#         # make future prediction dataframe
+#         future = self._make_future()
+#         return self.model.predict(future)["yhat"].to_numpy()
+#
+#     def predict_withci(self):
+#         future = self._make_future()
+#         forecast_dict = {"forecast": self.predict()}
+#
+#         for i in range(len(self.level)):
+#             self.model.interval_width = self.level[i] * 0.01
+#             forecast_df = self.model.predict(future)
+#
+#             # add intervals
+#             forecast_dict[f"LB_{self.level[i]}"] = forecast_df[
+#                 "yhat_lower"
+#             ].to_numpy()
+#             forecast_dict[f"UB_{self.level[i]}"] = forecast_df[
+#                 "yhat_upper"
+#             ].to_numpy()
+#
+#         return forecast_dict
+#
+#     def description(self):
+#         return self.model
 
 
 class RCES(RSmoothForecastModel):

updater/requirements.txt

@@ -13,7 +13,7 @@ packaging==21.3
 pandas==1.4.2
 patsy==0.5.2
 plotly==5.8.0
-prophet==1.1
+#prophet==1.1
 pycparser==2.21
 pyparsing==3.0.9
 python-dateutil==2.8.2