zx2214008
commented
1 year ago Hi, many thanks for this.
When running the code it fails always on the 2/5
Predicting future Close prices from 2023-01-18 00:00:00 to 2023-01-22 00:00:00 40%|██████████████████████████████████ | 2/5 [00:03<00:05, 1.97s/it]seems that total_data contains NaN values and the score method don't like it. Any idea on how to fix this?
I have switched to downloading the data using yfinance, all the columns have no NaNs so it's not the root of the issue. Is there something I am missing that may cause the ValueError?
Training data period is from 2018-01-02 00:00:00 to 2021-05-18 00:00:00 2023-01-18 10:04:46,223 __main__ INFO >>> Extracting Features 2023-01-18 10:04:46,223 __main__ INFO Features extraction Completed <<< Predicting Close prices from 2021-05-19 00:00:00 to 2023-01-17 00:00:00 100%|█████████████████████████████████████████████████████████████████████████████████| 419/419 [09:17<00:00, 1.33s/it] All predictions saved. The Mean Squared Error for the 419 days considered is: 6.657134688795405 Predicting future Close prices from 2023-01-18 00:00:00 to 2023-01-22 00:00:00 40%|██████████████████████████████████ | 2/5 [00:03<00:05, 1.97s/it] Traceback (most recent call last): File "/home/originn/HMMs_Stock_Market/src/stock_analysis.py", line 470, in <module> main() File "/home/originn/HMMs_Stock_Market/src/stock_analysis.py", line 465, in main use_stock_predictor(company_name, start, end, future, metrics, plot, out_dir) File "/home/originn/HMMs_Stock_Market/src/stock_analysis.py", line 354, in use_stock_predictor future_pred_close = stock_predictor.predict_close_prices_for_future() File "/home/originn/HMMs_Stock_Market/src/stock_analysis.py", line 248, in predict_close_prices_for_future predicted_close_prices.append(self.predict_close_price_fut_days(day_index)) File "/home/originn/HMMs_Stock_Market/src/stock_analysis.py", line 223, in predict_close_price_fut_days ) = self._get_most_probable_outcome(day_index) File "/home/originn/HMMs_Stock_Market/src/stock_analysis.py", line 149, in _get_most_probable_outcome outcome_score.append(self.hmm.score(total_data)) File "/home/originn/HMMs_Stock_Market/venv/lib/python3.10/site-packages/hmmlearn/base.py", line 259, in score return self._score(X, lengths, compute_posteriors=False)[0] File "/home/originn/HMMs_Stock_Market/venv/lib/python3.10/site-packages/hmmlearn/base.py", line 272, in _score X = check_array(X) File "/home/originn/HMMs_Stock_Market/venv/lib/python3.10/site-packages/sklearn/utils/validation.py", line 919, in check_array _assert_all_finite( File "/home/originn/HMMs_Stock_Market/venv/lib/python3.10/site-packages/sklearn/utils/validation.py", line 161, in _assert_all_finite raise ValueError(msg_err) ValueError: Input contains NaN.Shouldn't in
def predict_close_price_fut_days(self, day_index)the self.days be incemented?
I have the same issue as you and fixed it. Change the code from the line 194 to 196 as follows:
second_df = pd.DataFrame(index=future_dates, columns=["Open", "High", "Low", "Close"])
The wrong order make iloc could not local the right cell to replace the opening price for the first day in the future.
Hi, many thanks for this.
When running the code it fails always on the 2/5
seems that total_data contains NaN values and the score method don't like it. Any idea on how to fix this?
I have switched to downloading the data using yfinance, all the columns have no NaNs so it's not the root of the issue. Is there something I am missing that may cause the ValueError?
Shouldn't in
def predict_close_price_fut_days(self, day_index)the self.days be incemented?