Merge branch 'master' into tbas_adapter

tinkoff-ai · Jun 3, 2022 · 698c22c · 698c22c
2 parents ae8b9d3 + d85c7f0
commit 698c22c
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Showing 4 changed files with 20 additions and 23 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -41,22 +41,22 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - 
 ### Fixed
 -
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+- 
+- Fix bug when `ts.plot` does not save figure ([#714](https://github.com/tinkoff-ai/etna/pull/714))
+- 
+- 
 - Fix bug in plot_clusters ([#675](https://github.com/tinkoff-ai/etna/pull/675))
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+- 
 - Fix bugs and documentation for cross_corr_plot ([#691](https://github.com/tinkoff-ai/etna/pull/691))
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+- 
+- 
 - Fix bugs and documentation for plot_backtest and plot_backtest_interactive ([#700](https://github.com/tinkoff-ai/etna/pull/700))
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+- 
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+- Fix tiny prediction intervals ([#722](https://github.com/tinkoff-ai/etna/pull/722))
+- 
+- 
+- 
 
 ## [1.9.0] - 2022-05-17
 ### Added

diff --git a/etna/datasets/tsdataset.py b/etna/datasets/tsdataset.py
@@ -495,8 +495,6 @@ def plot(
             ax[i].set_title(segment)
             ax[i].grid()
 
-        plt.show()
-
     @staticmethod
     def to_flatten(df: pd.DataFrame) -> pd.DataFrame:
         """Return pandas DataFrame with flatten index.

diff --git a/etna/pipeline/base.py b/etna/pipeline/base.py
@@ -13,7 +13,6 @@
 
 import numpy as np
 import pandas as pd
-import scipy
 from joblib import Parallel
 from joblib import delayed
 from scipy.stats import norm
@@ -231,11 +230,11 @@ def _forecast_prediction_interval(
             - self.ts[forecasts.index.min() : forecasts.index.max(), :, "target"]
         )
 
-        se = scipy.stats.sem(residuals)
+        sigma = np.std(residuals.values, axis=0)
         borders = []
         for quantile in quantiles:
             z_q = norm.ppf(q=quantile)
-            border = predictions[:, :, "target"] + se * z_q
+            border = predictions[:, :, "target"] + sigma * z_q
             border.rename({"target": f"target_{quantile:.4g}"}, inplace=True, axis=1)
             borders.append(border)
 

diff --git a/tests/test_pipeline/conftest.py b/tests/test_pipeline/conftest.py
@@ -1,8 +1,8 @@
 from typing import Tuple
 
+import numpy as np
 import pandas as pd
 import pytest
-import scipy
 from numpy.random import RandomState
 from scipy.stats import norm
 
@@ -68,10 +68,10 @@ def splited_piecewise_constant_ts(
     segment_2 = [constant_2_1] * first_constant_len + [constant_2_2] * horizon * 2
 
     quantile = norm.ppf(q=(1 + INTERVAL_WIDTH) / 2)
-    se_1 = scipy.stats.sem([0.0] * horizon * 2 + [constant_1_1 - constant_1_2] * horizon)
-    se_2 = scipy.stats.sem([0.0] * horizon * 2 + [constant_2_1 - constant_2_2] * horizon)
-    lower = [x - se_1 * quantile for x in segment_1] + [x - se_2 * quantile for x in segment_2]
-    upper = [x + se_1 * quantile for x in segment_1] + [x + se_2 * quantile for x in segment_2]
+    sigma_1 = np.std([0.0] * horizon * 2 + [constant_1_1 - constant_1_2] * horizon)
+    sigma_2 = np.std([0.0] * horizon * 2 + [constant_2_1 - constant_2_2] * horizon)
+    lower = [x - sigma_1 * quantile for x in segment_1] + [x - sigma_2 * quantile for x in segment_2]
+    upper = [x + sigma_1 * quantile for x in segment_1] + [x + sigma_2 * quantile for x in segment_2]
 
     ts_range = list(pd.date_range("2020-01-03", freq="1D", periods=len(segment_1)))
     lower_p = (1 - INTERVAL_WIDTH) / 2