fname = "./logs/sleep/YOUR_TIME.csv"
import pandas as pd
import plotly.express as plt
#df = pd.read_csv(fname, names=["motion", "elapsed", "x_avg", "y_avg", "z_avg", "battery"])
df = pd.read_csv(fname, names=["motion", "elapsed", "heart_rate"])
start_time = int(fname.split("/")[-1].split(".csv")[0])
df["time"] = pd.to_datetime(df["elapsed"]+start_time, unit='s')
df["human_time"] = df["time"].dt.time
month = df.iloc[0]["time"].month_name()
dayname = str(df.iloc[0]["time"].day_name())
daynumber = str(df.iloc[0]["time"].day)
if daynumber == 1:
    daynumber = str(daynumber) + "st"
elif daynumber.endswith("2"):
    daynumber = str(daynumber) + "nd"
elif daynumber.endswith("3"):
    daynumber = str(daynumber) + "rd"
else:
    daynumber = str(daynumber) + "th"
date = f"{month} {daynumber} ({dayname})"
fig = px.line(df,
              x="time",
              y="motion",
              labels={"motion": "Body motion", "time":"Time"},
              title=f"Night starting on {date}")
fig.update_xaxes(type="date",
                 tickformat="%H:%M"
                 )
fig.show()
df_HR = df.set_index("human_time")["heart_rate"]
df_HR = df_HR[~df_HR.isna()]
df_HR.plot()

import array
data = array.array("f", df["motion"])
data = data[:15] # remove the last few data points as the signal
# processor does not yet have access to them when finding best wake up time
##############################################
### PUT LATEST SIGNAL PROCESSING CODE HERE ###
##############################################
from matplotlib import pyplot as plt
plt.plot(data)
for i in x_maximas:
    plt.axvline(x=i,
                color="red",
                linestyle="--"
                )
plt.show()