Fix plot_backtest and plot_backtest_interactive on one-step forecast

[Mr-Geekman]

Before submitting (must do checklist)

• Did you read the contribution guide?
• Did you update the docs? We use Numpy format for all the methods and classes.
• Did you write any new necessary tests?
• Did you update the CHANGELOG?

Proposed Changes

• Process case of horizon=1 and 1 fold separately
• Fix finding next point using pd.date_range

Closing issues

Closes #1122.

[Mr-Geekman]

Script for plotting:

import matplotlib.pyplot as plt
import pandas as pd

from etna.analysis import plot_backtest, plot_backtest_interactive
from etna.datasets import TSDataset
from etna.metrics import MAE
from etna.models import ProphetModel
from etna.pipeline import FoldMask
from etna.pipeline import Pipeline


def main():
    df = pd.read_csv("examples/data/example_dataset.csv")
    df = TSDataset.to_dataset(df)
    ts = TSDataset(df, freq="D")

    # plot with horizon=1, n_folds=1
    pipeline = Pipeline(model=ProphetModel(), horizon=1)
    metrics_df, forecast_df, fold_info_df = pipeline.backtest(ts=ts, metrics=[MAE()], n_folds=1)
    plot_backtest(forecast_df=forecast_df, ts=ts, history_len=10)
    plt.savefig("plot_horizon_1_folds_1.png")
    fig = plot_backtest_interactive(forecast_df=forecast_df, ts=ts, history_len=10)
    fig.write_image("plot_int_horizon_1_folds_1.png")

    # plot with horizon=1, n_folds=3
    pipeline = Pipeline(model=ProphetModel(), horizon=1)
    metrics_df, forecast_df, fold_info_df = pipeline.backtest(ts=ts, metrics=[MAE()], n_folds=3)
    plot_backtest(forecast_df=forecast_df, ts=ts, history_len=10)
    plt.savefig("plot_horizon_1_folds_3.png")
    fig = plot_backtest_interactive(forecast_df=forecast_df, ts=ts, history_len=10)
    fig.write_image("plot_int_horizon_1_folds_3.png")

    # plot with horizon=7, n_folds=3
    pipeline = Pipeline(model=ProphetModel(), horizon=7)
    metrics_df, forecast_df, fold_info_df = pipeline.backtest(ts=ts, metrics=[MAE()], n_folds=3)
    plot_backtest(forecast_df=forecast_df, ts=ts, history_len=10)
    plt.savefig("plot_horizon_7_folds_3.png")
    fig = plot_backtest_interactive(forecast_df=forecast_df, ts=ts, history_len=10)
    fig.write_image("plot_int_horizon_7_folds_3.png")

    # fold mask example
    pipeline = Pipeline(model=ProphetModel(), horizon=14)
    folds = [
        FoldMask(
            first_train_timestamp=None,
            last_train_timestamp=pd.Timestamp("2019-10-19"),
            target_timestamps=[pd.Timestamp("2019-10-26"), pd.Timestamp("2019-10-27"), pd.Timestamp("2019-11-01")],
        ),
        FoldMask(
            first_train_timestamp=None,
            last_train_timestamp=pd.Timestamp("2019-11-02"),
            target_timestamps=[pd.Timestamp("2019-11-06"), pd.Timestamp("2019-11-08"), pd.Timestamp("2019-11-10")],
        ),
        FoldMask(
            first_train_timestamp=None,
            last_train_timestamp=pd.Timestamp("2019-11-16"),
            target_timestamps=[pd.Timestamp("2019-11-20"), pd.Timestamp("2019-11-22"), pd.Timestamp("2019-11-24")],
        ),
    ]
    metrics_df, forecast_df, fold_info_df = pipeline.backtest(ts=ts, metrics=[MAE()], n_folds=folds)

    plot_backtest(forecast_df=forecast_df, ts=ts, history_len=50)
    plt.savefig("plot_masks.png")
    fig = plot_backtest_interactive(forecast_df=forecast_df, ts=ts, history_len=50)
    fig.write_image("plot_int_masks.png")


if __name__ == "__main__":
    main()

[github-actions]

🚀 Deployed on https://deploy-preview-1260--etna-docs.netlify.app

[codecov-commenter]

Codecov Report

Merging #1260 (aa4d99d) into master (e1f642f) will decrease coverage by 0.03%.
The diff coverage is 0.00%.

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@@            Coverage Diff             @@
##           master    #1260      +/-   ##
==========================================
- Coverage   87.99%   87.97%   -0.03%     
==========================================
  Files         186      186              
  Lines       10749    10747       -2     
==========================================
- Hits         9459     9455       -4     
- Misses       1290     1292       +2     

Impacted Files	Coverage Δ
etna/analysis/forecast/plots.py	18.83% <0.00%> (-0.11%)	⬇️

... and 4 files with indirect coverage changes

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