WIP adjuster
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@@ -1,12 +1,13 @@
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import logging
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from contextlib import suppress
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from dataclasses import InitVar, dataclass, field
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from datetime import datetime, timedelta, tzinfo, date, time
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from datetime import date, datetime, time, timedelta, tzinfo
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from typing import Dict, Iterable
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import astral
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import matplotlib.dates as mdates
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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from astral import Observer, SunDirection
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from astral.sun import elevation, sun, time_at_elevation
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@@ -36,7 +37,7 @@ def get_today_series():
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return days.values
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def times_at_elevation(observer: Observer, elevation, direction, days = None):
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def times_at_elevation(observer: Observer, elevation, direction, days=None):
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kwargs = dict(
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observer=observer,
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elevation=elevation,
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@@ -56,53 +57,16 @@ def times_at_elevation(observer: Observer, elevation, direction, days = None):
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return df
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def get_next_time_at_elevation(*args, **kwargs):
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time = time_at_elevation(*args, **kwargs)
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if time < (now := datetime.now(HOME_TZ)):
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time = time_at_elevation(
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*args,
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date=(now + timedelta(days=1)).date(),
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**kwargs
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)
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return time
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def get_next_sun_time(named_time: str, observer: Observer):
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sun_times_dict = sun(observer, datetime.today().date())
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try:
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time = sun_times_dict[named_time].astimezone()
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except KeyError:
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time = datetime.combine(
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datetime.today().date(),
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datetime.strptime(named_time, '%I:%M:%S%p').time()
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).astimezone()
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if time < (now := datetime.now(HOME_TZ)):
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tomorrow = (now + timedelta(days=1)).date()
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sun_times_dict = sun(observer, tomorrow)
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try:
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time = sun_times_dict[named_time].astimezone()
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except KeyError:
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time = datetime.combine(
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tomorrow,
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datetime.strptime(named_time, '%I:%M:%S%p').time()
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).astimezone()
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return time
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def parse_periods(observer: Observer, periods: Dict, date: date):
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now = datetime.now(HOME_TZ)
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for period in periods:
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if 'time' in period:
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try:
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time = datetime.strptime(period['time'], '%I:%M:%S%p')
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time = datetime.strptime(period['time'], '%I:%M:%S%p').time()
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except:
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sun_dict = sun(observer=observer, date=date, tzinfo=HOME_TZ)
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dt = sun_dict[period['time']]
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else:
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dt = datetime.combine(date, time)
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dt = datetime.combine(date, time, tzinfo=HOME_TZ)
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elif 'elevation' in period:
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if period['direction'] == 'rising':
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@@ -126,6 +90,14 @@ def parse_periods(observer: Observer, periods: Dict, date: date):
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yield res
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def elevation_series(observer: Observer, date, **kwargs):
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times = pd.date_range(start=date, end=(date + timedelta(days=1)), **kwargs)
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elevations = pd.Series(
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[elevation(observer, timestamp) for timestamp in times],
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index=times, name='elevation')
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return elevations
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@dataclass
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class DaylightAdjuster:
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latitude: float
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@@ -136,40 +108,37 @@ class DaylightAdjuster:
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def __post_init__(self, periods: Dict, resolution: int):
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self.logger: logging.Logger = logging.getLogger(type(self).__name__)
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now = datetime.now().astimezone()
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times = pd.date_range(
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start=now, end=now + timedelta(days=1),
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periods=resolution,
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tz=HOME_TZ
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self.period_df: pd.DataFrame = pd.DataFrame([
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p
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for date in get_today_series()
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for p in parse_periods(self.observer, periods, date)
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]).set_index('time').interpolate(method='index').round(0).astype(int)
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self.df = self.period_df.join(pd.concat([
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elevation_series(self.observer, date, periods=1000, tz=HOME_TZ)
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for date in get_today_series()
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]), how='outer')
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self.df = (
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self.df
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.sort_index()
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.interpolate(method='index')
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.bfill().ffill()
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# .round(0).astype(int)
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# .drop_duplicates()
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)
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self.logger.debug(times)
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pytimes = [dt.to_pydatetime() for dt in times]
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el = pd.Series(
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(elevation(self.observer, dt) for dt in pytimes),
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index=times, name='elevation'
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)
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self.logger.debug(el)
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# el.index = el.index.tz_convert(HOME_TZ)
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# el.index = el.index.tz_convert(None)
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self.periods = parse_periods(self.observer, periods)
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# self.df = pd.DataFrame(el)
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self.df = pd.concat([pd.DataFrame(self.periods).set_index('time'), el], axis=1)
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self.df = self.df.sort_index().interpolate().bfill().ffill()
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# self.df.index = self.df.index.to_series().dt.tz_localize(None)
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self.df.index = self.df.index.to_series().dt.tz_localize(None)
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@property
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def observer(self) -> astral.Observer:
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return astral.Observer(self.latitude, self.longitude)
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@property
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def current_settings(self) -> pd.Series:
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return self.df[:datetime.now().astimezone()].iloc[-1].drop('elevation').astype(int).to_dict()
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def current_settings(self) -> Dict:
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now = datetime.now(HOME_TZ)
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self.period_df.loc[now] = np.nan
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return self.period_df.interpolate(method='index').round(0).astype(int).loc[now].to_dict()
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def elevation_fig(self):
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fig, ax = plt.subplots(figsize=(10, 7))
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@@ -191,9 +160,9 @@ class DaylightAdjuster:
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ax2.set_ylabel('Brightness')
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ax2.set_ylim(0, 100)
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# handles.append(ax.axvline(datetime.now().astimezone(),
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# linestyle='--',
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# color='g'))
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handles.append(ax.axvline(datetime.now().astimezone(),
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linestyle='--',
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color='g'))
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# handles.append(ax2.axhline(self.get_brightness(),
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# linestyle='--',
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