Fix low speed of lagged implementation

[kasyanovse]

Replace chain concatenation with pandas by numpy bulk realization.

[aim-pep8-bot]

Hello @kasyanovse! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

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Comment last updated at 2023-08-15 07:20:28 UTC

[codecov]

Codecov Report

Merging #1144 (6ae8f6c) into master (89ff552) will decrease coverage by 0.21%.
Report is 2 commits behind head on master.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master    #1144      +/-   ##
==========================================
- Coverage   78.67%   78.47%   -0.21%     
==========================================
  Files         131      130       -1     
  Lines        9362     9323      -39     
==========================================
- Hits         7366     7316      -50     
- Misses       1996     2007      +11     

Files Changed	Coverage Δ
...lementations/data_operations/ts_transformations.py	77.65% <100.00%> (-0.77%)	⬇️

... and 16 files with indirect coverage changes

[kasyanovse]

Speed test. Also some models are speeded up too because they use ts_to_table function that is implement in module with lagged.

Code (for IPython)

import numpy as np

from examples.simple.time_series_forecasting.ts_pipelines import ts_polyfit_pipeline, ts_complex_ridge_pipeline
from fedot.core.data.data import InputData
from fedot.core.repository.dataset_types import DataTypesEnum
from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams

series = np.random.rand(100000)
data = InputData(idx=np.arange(series.shape[0]),
               features=series, target=series,
               task=Task(TaskTypesEnum.ts_forecasting,
                         TsForecastingParams(forecast_length=100)),
               data_type=DataTypesEnum.ts)

pipeline = ts_polyfit_pipeline(2)
%timeit pipeline.fit(data)

pipeline = ts_complex_ridge_pipeline()
%timeit pipeline.fit(data)

Results.

1. Old lagged
   1. 2.28 s ± 232 ms for polyfit
   2. 2.39 s ± 62.3 ms for lagged + ridge
2. New lagged
   1. 48.3 ms ± 1.15 ms for polyfit
   2. 605 ms ± 11.3 ms for lagged + ridge

Pipeline with ridge spends half of all time for ridge fitting, therefore speed up is not so high.