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# MarwanDebbiche/tsgen_typed_generators.py

Created October 15, 2020 21:01
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 import math import numpy as np # type: ignore import pandas as pd # type: ignore from tsgen.time_serie import TimeSerie def affine(start, end, freq, start_y, end_y) -> TimeSerie: """ Generate a linear TimeSerie. """ index = pd.date_range(start=start, end=end, freq=freq) return TimeSerie( index=index, y_values=np.linspace(start_y, end_y, len(index)) ) def constant(start, end, freq, value) -> TimeSerie: """ Generate a constant TimeSerie. """ return affine(start, end, freq, value, value) def cosine(start, end, freq, amp=1, n_periods=1) -> TimeSerie: """ Generate a cosine TimeSerie. """ index = pd.date_range(start=start, end=end, freq=freq) return TimeSerie( index=index, y_values=amp * np.cos(np.linspace(0, 2 * math.pi * n_periods, num=len(index))), ) def sine(start, end, freq, n_periods=1) -> TimeSerie: """ Generate a sine TimeSerie. """ index = pd.date_range(start=start, end=end, freq=freq) return TimeSerie( index=index, y_values=np.sin( np.linspace(0, 2 * math.pi * n_periods, num=len(index)) ), ) def randn(start, end, freq, mean=0, std=1) -> TimeSerie: """ Generate a random normally distributed TimeSerie. """ index = pd.date_range(start=start, end=end, freq=freq) return TimeSerie( index=index, y_values=(std * np.random.randn(len(index)) + mean) )
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