Created
October 26, 2023 07:19
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Compare two timeseries for distance
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import pandas as pd | |
import numpy as np | |
import math | |
from datetime import datetime, timedelta | |
df1 = pd.DataFrame() | |
df1["time"] = pd.date_range('08/12/2021 00:00:01', periods=6, freq="4S") | |
df1['values'] = [1, 2, 3, 4, 5, 6] | |
df2 = pd.DataFrame() | |
df2["time"] = pd.date_range('08/12/2021', periods=4, freq="6S") | |
df2['values'] = [1, 2, 5, 200] | |
df = pd.merge(df1, df2, how="outer", left_on="time", right_on="time", sort=True) | |
print(df) | |
#df = df.interpolate(method="pad", axis=0) | |
df.ffill(inplace=True) | |
df.dropna(inplace=True) | |
#df.bfill(inplace=True) | |
df["time_to"] = df["time"].shift(-1) | |
df["time_to"].ffill(inplace=True) | |
df["duration"] = df["time_to"] - df["time"] | |
# Note: we do not have to use abs if d is a real distance | |
df["d"] = np.abs(np.arctan(df["values_x"] - df["values_y"]) / (math.pi / 2)) | |
min_time = min(df["time"]) | |
max_time = max(df["time_to"]) | |
total = max_time - min_time | |
total = sum(df["duration"], timedelta()) | |
print(total) | |
df["wd"] = df["d"] * ((df["time_to"] - df["time"]) / total) | |
print(df) | |
t2 = sum(df["wd"]) | |
print(t2) |
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