use glotec instead
This commit is contained in:
parent
8138ea21fc
commit
d4fa375e0b
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@ -7,18 +7,8 @@ EarthData which is done through Selenium and the Chrome browser.
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1. Create an account at <https://urs.earthdata.nasa.gov>
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2. `pip install -r requirements.txt`
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3. `sudo apt-get install p7zip-full redis-server`
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4. `sudo apt-get install dvipng texlive-latex-extra texlive-fonts-recommended cm-super`
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5. `sudo systemctl enable --now redis-server`
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### Google Chrome
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If you don't have Google Chrome installed (used to log into the NASA site), here's how to install it.
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```shell
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wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
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apt install ./google-chrome-stable_current_amd64.deb
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```
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3. `sudo apt-get install redis-server`
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4. `sudo systemctl enable --now redis-server`
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## Run
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@ -29,7 +19,6 @@ LAT_RANGE_MIN=<lower range for lat bounding box> \
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LAT_RANGE_MAX=<upper range for lat bounding box> \
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LON_RANGE_MIN=<lower range for lon bounding box> \
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LON_RANGE_MAX=<upper range for lon bounding box> \
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CDDIS_USERNAME=<username> CDDIS_PASSWORD=<password> \
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MQTT_BROKER_HOST="<Home Assistant IP>" MQTT_BROKER_PORT=1883 MQTT_USERNAME="user" MQTT_PASSWORD="<password>" \
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python3 mqtt.py
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```
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@ -39,24 +28,19 @@ Example systemd service files are provided.
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### Home Assistant MQTT Config
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```yaml
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mqtt:
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- state_topic: "space-weather/vtec"
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name: "VTEC"
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unit_of_measurement: "(10^16 el) / m^2"
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state_class: measurement
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unique_id: space_weather_vtec
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- state_topic: "space-weather/glotec"
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name: "GloTEC"
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unit_of_measurement: "(10^16) / m^-2"
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state_class: measurement
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unique_id: space_weather_glotec
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```
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## Data
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### VTEC
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### GloTEC
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<https://www.spaceweather.gov/products/us-total-electron-content>
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<https://www.swpc.noaa.gov/experimental/glotec>
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Unit: `(10^16 el) / m^2`
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VTEC, or Vertical TEC, is a specific type of TEC measurement that is taken along a path extending
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vertically from the Earth's surface to the edge of the atmosphere. Essentially, VTEC is a subset of TEC, with the
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difference lying in the specific path along which the measurement is taken.
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Unit: `(10^16) / m^-2`
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Updated hourly.
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@ -1,37 +1,21 @@
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import logging
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import os
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import pickle
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import sys
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import time
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from datetime import datetime
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from redis import Redis
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from lib.cddis_fetch import fetch_latest_ionex
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from lib.tecmap import get_tecmaps, parse_ionex_datetime
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from lib.glotec import get_latest_glotec
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logging.basicConfig(level=logging.INFO)
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CDDIS_USERNAME = os.getenv('CDDIS_USERNAME')
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CDDIS_PASSWORD = os.getenv('CDDIS_PASSWORD')
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if not CDDIS_USERNAME or not CDDIS_PASSWORD:
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logging.critical('Must set CDDIS_USERNAME and CDDIS_PASSWORD environment variables')
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sys.exit(1)
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def main():
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redis = Redis(host='localhost', port=6379, db=0)
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redis.flushall()
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while True:
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utc_hr = datetime.utcnow().hour
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logging.info('Fetching latest IONEX data')
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logging.info(f'Using hour {utc_hr}')
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ionex_data = fetch_latest_ionex(CDDIS_USERNAME, CDDIS_PASSWORD)
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parsed_data = []
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for tecmap, epoch in get_tecmaps(ionex_data):
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parsed_dt = parse_ionex_datetime(epoch)
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parsed_data.append((tecmap, parsed_dt))
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redis.set('tecmap_data', pickle.dumps(parsed_data))
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logging.info('Fetching latest GLOTEC data')
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geojson = get_latest_glotec()
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redis.set('glotec', pickle.dumps(geojson))
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logging.info('Scrape complete')
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time.sleep(1800) # 30 minutes
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@ -1,58 +0,0 @@
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import io
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import logging
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import pickle
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import time
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from datetime import datetime
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import schedule
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from PIL import Image
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from redis import Redis
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from lib.tecmap import plot_tec_map
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logging.basicConfig(level=logging.INFO)
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# Entire planet
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LAT_RANGE_MIN = -90
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LAT_RANGE_MAX = 90
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LON_RANGE_MIN = -180
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LON_RANGE_MAX = 180
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def main():
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redis = Redis(host='localhost', port=6379, db=0)
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utc_hr = datetime.utcnow().hour
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logging.info(f'Generating plot for hour {utc_hr}')
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data = redis.get('tecmap_data')
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while data is None:
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logging.warning('Redis has not been populated yet. Is cache.py running? Sleeping 10s...')
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time.sleep(10)
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data = redis.get('tecmap_data')
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ionex_data = pickle.loads(data)
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for tecmap, epoch in ionex_data:
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if epoch.hour == utc_hr:
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plt = plot_tec_map(tecmap, [float(LON_RANGE_MIN), float(LON_RANGE_MAX)], [float(LAT_RANGE_MIN), float(LAT_RANGE_MAX)], timestamp_utc=epoch)[1]
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buf = io.BytesIO()
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plt.savefig(buf, format='png', bbox_inches='tight', pad_inches=0.1, dpi=110)
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plt.close()
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del plt
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buf.seek(0)
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img = Image.open(buf)
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buf = io.BytesIO()
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img.save(buf, format='PNG')
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redis.set('global_map', buf.getvalue())
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buf.close()
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logging.info(f'Finished hour {utc_hr}')
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if __name__ == '__main__':
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main()
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schedule.every().hour.at(':00').do(main)
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while True:
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schedule.run_pending()
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time.sleep(1)
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@ -1,89 +0,0 @@
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import datetime
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import logging
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import subprocess
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import sys
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import tempfile
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from pathlib import Path
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import chromedriver_autoinstaller
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import requests
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from selenium import webdriver
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from selenium.webdriver import Keys
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from selenium.webdriver.chrome.options import Options
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from selenium.webdriver.common.by import By
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from selenium.webdriver.support import expected_conditions as EC
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from selenium.webdriver.support.ui import WebDriverWait
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IONEX_BASE_URL = 'https://cddis.nasa.gov/archive/gnss/products/ionex/'
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def fetch_latest_ionex(username: str, password: str):
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now = datetime.date.today()
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url = IONEX_BASE_URL + str(now.year)
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chromedriver_autoinstaller.install()
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options = Options()
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options.add_argument('--headless=new')
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driver = webdriver.Chrome(options=options)
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driver.get(url)
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# Login
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username_field = WebDriverWait(driver, 30).until(EC.presence_of_element_located((By.ID, "username")))
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username_field.clear()
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username_field.send_keys(username)
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password_field = WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.ID, "password")))
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password_field.clear()
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password_field.send_keys(password)
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password_field.send_keys(Keys.RETURN)
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# Wait until we're redirected to the right page.
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WebDriverWait(driver, 30).until(EC.visibility_of_element_located((By.ID, "parDirTextContainer")))
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# Get the days in the year.
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day_elements = driver.find_elements(By.XPATH, '//div[@class="archiveDir"]/div[@class="archiveDirTextContainer"]/a[@class="archiveDirText"]')
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day_urls = [element.get_attribute('href') for element in day_elements]
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# Load the latest day.
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today_url = day_urls[-2] # last element is predictions for tomorrow so we want the second to last one
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logging.info(f'Using day {today_url.split("/")[-1]}')
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driver.get(today_url)
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# Find our file.
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file_elements = driver.find_elements(By.XPATH, '//a[@class="archiveItemText"]')
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file_urls = [element.get_attribute('href') for element in file_elements]
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found_url = None
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for u in file_urls:
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parts = u.split('/')
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if parts[-1].startswith('c2pg'):
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found_url = u
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break
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if found_url is None:
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print('Did not find c2pg')
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sys.exit(1)
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# Download our file.
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auth_cookie = None
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for cookie in driver.get_cookies():
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if cookie['name'] == 'ProxyAuth':
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auth_cookie = cookie['value']
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break
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if auth_cookie is None:
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print('Did not find ProxyAuth cookie')
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sys.exit(1)
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driver.close()
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del driver
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# Download data.
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zip_data_r = requests.get(found_url, cookies={'ProxyAuth': auth_cookie})
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zip_data_r.raise_for_status()
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# Read data.
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tmp_file = tempfile.NamedTemporaryFile()
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tmp_file.write(zip_data_r.content)
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tmp_dir = tempfile.TemporaryDirectory()
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subprocess.run(["7z", "e", tmp_file.name, f"-o{tmp_dir.name}"], check=True, stdout=subprocess.PIPE)
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p = Path(tmp_dir.name)
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target_file = list(p.iterdir())[-1]
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data = target_file.read_text()
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return data
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@ -0,0 +1,66 @@
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import time
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import cartopy.crs as ccrs
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import matplotlib.pyplot as plt
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import numpy as np
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import requests
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from dateutil.parser import parse
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from dateutil.tz import tzutc, tzlocal
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from matplotlib.colors import LinearSegmentedColormap
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from mpl_toolkits.axes_grid1 import make_axes_locatable
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from scipy.interpolate import griddata
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def get_latest_glotec():
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r = requests.get('https://services.swpc.noaa.gov/experimental/products/glotec/geojson_2d_urt.json')
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r.raise_for_status()
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index_json = r.json()[-1]
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data_url = 'https://services.swpc.noaa.gov' + index_json['url']
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r2 = requests.get(data_url)
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r2.raise_for_status()
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return r2.json()
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def plot_glotec_map(data: dict, lon_range: list, lat_range: list):
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lons = []
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lats = []
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tec_values = []
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for feature in data['features']:
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lon, lat = feature['geometry']['coordinates']
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tec = feature['properties']['tec']
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lons.append(lon)
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lats.append(lat)
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tec_values.append(tec)
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lons = np.array(lons)
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lats = np.array(lats)
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tec_values = np.array(tec_values)
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lon_grid, lat_grid = np.meshgrid(np.linspace(lon_range[0], lon_range[1], 100), np.linspace(lat_range[0], lat_range[1], 100))
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# Interpolate the TEC values onto the regular grid
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tec_grid = griddata((lons, lats), tec_values, (lon_grid, lat_grid), method='linear')
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proj = ccrs.PlateCarree()
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f, ax = plt.subplots(1, 1, subplot_kw=dict(projection=proj))
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colors = ['#33184a', '#4454c3', '#4294ff', '#1ad2d2', '#3cf58e', '#9cfe40', '#dde037', '#fdac34', '#f26014', '#ca2a04', '#7A0403']
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custom_cmap = LinearSegmentedColormap.from_list('custom', colors)
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h = ax.pcolormesh(lon_grid, lat_grid, tec_grid, cmap=custom_cmap, vmin=0, vmax=100, transform=proj)
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ax.coastlines()
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timestamp_utc = parse(data['time_tag'])
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timestamp_local = timestamp_utc.replace(tzinfo=tzutc()).astimezone(tzlocal())
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plt.title(timestamp_local.strftime(f'%H:%M %m-%d-%Y {time.tzname[0]}'), fontsize=12, y=1.04)
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plt.suptitle('Global Total Electron Content', fontsize=16, y=0.87)
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divider = make_axes_locatable(ax)
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ax_cb = divider.new_horizontal(size='5%', pad=0.1, axes_class=plt.Axes)
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f.add_axes(ax_cb)
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cb = plt.colorbar(h, cax=ax_cb)
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plt.rc('text', usetex=True)
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cb.set_label('VTEC ($10^{16}*\\mathrm{m}^{-2}$)')
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return tec_grid, plt
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@ -1,70 +0,0 @@
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import re
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import time
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from datetime import datetime
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import cartopy.crs as ccrs
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import matplotlib.pyplot as plt
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import numpy as np
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from dateutil.tz import tzutc, tzlocal
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from mpl_toolkits.axes_grid1 import make_axes_locatable
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"""
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https://github.com/daniestevez/jupyter_notebooks/blob/master/IONEX.ipynb
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"""
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def parse_ionex_datetime(s: str):
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match = re.match(r'\s*(\d{4})\s*(\d{1,2})\s*(\d{1,2})\s*(\d{1,2})\s*(\d{1,2})\s*(\d{1,2})', s)
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if match:
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year, month, day, hour, minute, second = map(int, match.groups())
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return datetime(year, month, day, hour, minute, second)
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else:
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raise ValueError("Invalid date format")
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def parse_map(tecmap, exponent=-1):
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tecmap = re.split('.*END OF TEC MAP', tecmap)[0]
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return np.stack([np.fromstring(l, sep=' ') for l in re.split('.*LAT/LON1/LON2/DLON/H\\n', tecmap)[1:]]) * 10 ** exponent
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def get_tecmaps(ionex: str):
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for tecmap in ionex.split('START OF TEC MAP')[1:]:
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lines = tecmap.split('\n')
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epoch = lines[1].strip() if len(lines) > 1 else None
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yield parse_map(tecmap), epoch
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def plot_tec_map(tecmap, lon_range: list, lat_range: list, timestamp_utc: datetime = None):
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proj = ccrs.PlateCarree()
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f, ax = plt.subplots(1, 1, subplot_kw=dict(projection=proj))
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# Create arrays of latitudes and longitudes to match the geographical grid of the TEC map data.
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# This is hard coded and should never change.
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lat = np.arange(-87.5, 87.5, 2.5)
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lon = np.arange(-180, 180, 5.0)
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# Create a mask for the data in the lat/lon range
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lon_mask = (lon >= lon_range[0]) & (lon < lon_range[1])
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lat_mask = (lat >= lat_range[0]) & (lat < lat_range[1])
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mask = np.ix_(lat_mask, lon_mask)
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# Select only the data in the lat/lon range
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tecmap_ranged = tecmap[mask]
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# Plot the TEC map
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h = plt.imshow(tecmap_ranged, cmap='viridis', vmin=0, vmax=100, extent=(lon_range[0], lon_range[1], lat_range[0], lat_range[1]), transform=proj)
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# Make graph pretty
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ax.coastlines()
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if timestamp_utc:
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timestamp_local = timestamp_utc.replace(tzinfo=tzutc()).astimezone(tzlocal())
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plt.title(timestamp_local.strftime(f'%H:%M %m-%d-%Y {time.tzname[0]}'), fontsize=12, y=1.04)
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plt.suptitle('Vertical Total Electron Count', fontsize=16, y=0.87)
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divider = make_axes_locatable(ax)
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ax_cb = divider.new_horizontal(size='5%', pad=0.1, axes_class=plt.Axes)
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f.add_axes(ax_cb)
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cb = plt.colorbar(h, cax=ax_cb)
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plt.rc('text', usetex=True)
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cb.set_label('TECU ($10^{16} \\mathrm{el}/\\mathrm{m}^2$)')
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return tecmap_ranged, plt
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@ -8,9 +8,10 @@ from datetime import datetime, timezone
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import numpy as np
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import paho.mqtt.client as mqtt
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from dateutil.parser import parse
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from redis import Redis
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from lib.tecmap import plot_tec_map
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from lib.glotec import plot_glotec_map
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logging.basicConfig(level=logging.INFO)
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@ -30,12 +31,6 @@ if not LAT_RANGE_MIN or not LAT_RANGE_MAX or not LON_RANGE_MIN or not LON_RANGE_
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print(LAT_RANGE_MIN, LAT_RANGE_MAX, LON_RANGE_MIN, LON_RANGE_MAX)
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sys.exit(1)
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CDDIS_USERNAME = os.getenv('CDDIS_USERNAME')
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CDDIS_PASSWORD = os.getenv('CDDIS_PASSWORD')
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if not CDDIS_USERNAME or not CDDIS_PASSWORD:
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logging.critical('Must set CDDIS_USERNAME and CDDIS_PASSWORD environment variables')
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sys.exit(1)
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client = mqtt.Client(client_id=MQTT_CLIENT_ID)
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if MQTT_USERNAME and MQTT_PASSWORD:
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client.username_pw_set(MQTT_USERNAME, MQTT_PASSWORD)
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@ -63,29 +58,25 @@ def main():
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redis = Redis(host='localhost', port=6379, db=0)
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while True:
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data = redis.get('tecmap_data')
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data = redis.get('glotec')
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while data is None:
|
||||
logging.warning('Redis has not been populated yet. Is cache.py running? Sleeping 10s...')
|
||||
time.sleep(10)
|
||||
data = redis.get('tecmap_data')
|
||||
ionex_data = pickle.loads(data)
|
||||
data = redis.get('glotec')
|
||||
geojson = pickle.loads(data)
|
||||
|
||||
utc_hr = datetime.now(timezone.utc).hour
|
||||
logging.info(f'Using hour {utc_hr}')
|
||||
|
||||
avg_tec = None
|
||||
for tecmap, epoch in ionex_data:
|
||||
if epoch.hour == utc_hr:
|
||||
tecmap_ranged, _ = plot_tec_map(tecmap, [float(LON_RANGE_MIN), float(LON_RANGE_MAX)], [float(LAT_RANGE_MIN), float(LAT_RANGE_MAX)])
|
||||
avg_tec = np.mean(tecmap_ranged)
|
||||
logging.info(f'Data timestamp: {epoch.isoformat()}')
|
||||
break
|
||||
glotec_map_ranged, _ = plot_glotec_map(geojson, [float(LON_RANGE_MIN), float(LON_RANGE_MAX)], [float(LAT_RANGE_MIN), float(LAT_RANGE_MAX)])
|
||||
avg_tec = np.mean(glotec_map_ranged)
|
||||
logging.info(f'Data timestamp: {parse(geojson["time_tag"]).isoformat()}')
|
||||
latest = round(avg_tec, 1)
|
||||
publish('vtec', latest)
|
||||
publish('glotec', latest)
|
||||
|
||||
del data
|
||||
del ionex_data
|
||||
del tecmap_ranged
|
||||
del geojson
|
||||
del glotec_map_ranged
|
||||
del avg_tec
|
||||
del latest
|
||||
gc.collect()
|
||||
|
|
|
|||
|
|
@ -12,3 +12,4 @@ flask==3.0.3
|
|||
schedule==1.2.2
|
||||
gunicorn==23.0.0
|
||||
python-dateutil==2.9.0.post0
|
||||
scipy==1.14.1
|
||||
|
|
@ -1,39 +0,0 @@
|
|||
import datetime
|
||||
import io
|
||||
|
||||
import redis
|
||||
from PIL import Image, ImageDraw, ImageFont
|
||||
from flask import Flask, send_file, make_response
|
||||
|
||||
NO_MAP_STR = 'NO GLOBAL MAP AVAILABLE'
|
||||
|
||||
app = Flask(__name__)
|
||||
redis_client = redis.Redis(host='localhost', port=6379)
|
||||
|
||||
|
||||
@app.route('/global')
|
||||
def serve_global_map():
|
||||
global_map_data = redis_client.get('global_map')
|
||||
if global_map_data is None:
|
||||
img = Image.new('RGB', (633, 356), color=(255, 255, 255))
|
||||
d = ImageDraw.Draw(img)
|
||||
fnt = ImageFont.load_default(size=30)
|
||||
w, h = fnt.getbbox(NO_MAP_STR)[2:4]
|
||||
d.text(((500 - w) / 2, (300 - h) / 2), NO_MAP_STR, font=fnt, fill=(0, 0, 0))
|
||||
buf = io.BytesIO()
|
||||
img.save(buf, format='PNG')
|
||||
buf.seek(0)
|
||||
return send_file(buf, mimetype='image/png')
|
||||
|
||||
buf = io.BytesIO(global_map_data)
|
||||
buf.seek(0)
|
||||
response = make_response(send_file(buf, mimetype='image/png'))
|
||||
expires = datetime.datetime.now()
|
||||
expires = expires + datetime.timedelta(minutes=10)
|
||||
response.headers['Cache-Control'] = 'public, max-age=600'
|
||||
response.headers['Expires'] = expires.strftime("%a, %d %b %Y %H:%M:%S GMT")
|
||||
return response
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
app.run()
|
||||
|
|
@ -1,15 +0,0 @@
|
|||
[Unit]
|
||||
Description=Space Weather Global Image Generator
|
||||
After=network.target space-weather-cache.service
|
||||
|
||||
[Service]
|
||||
Type=simple
|
||||
User=homeassistant
|
||||
EnvironmentFile=/etc/secrets/space-weather
|
||||
ExecStart=/srv/ha-noaa-space-weather/venv/bin/python /srv/ha-noaa-space-weather/feeder/global-image.py
|
||||
SyslogIdentifier=space-weather-global-image
|
||||
Restart=on-failure
|
||||
RestartSec=5s
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
|
|
@ -1,16 +0,0 @@
|
|||
[Unit]
|
||||
Description=Space Weather Server
|
||||
After=network.target
|
||||
|
||||
[Service]
|
||||
Type=simple
|
||||
User=homeassistant
|
||||
EnvironmentFile=/etc/secrets/space-weather
|
||||
WorkingDirectory=/srv/ha-noaa-space-weather/feeder
|
||||
ExecStart=/srv/ha-noaa-space-weather/venv/bin/gunicorn --workers 7 --bind 0.0.0.0:5000 server:app --access-logfile '-' --error-logfile '-'
|
||||
SyslogIdentifier=space-weather-server
|
||||
Restart=on-failure
|
||||
RestartSec=5s
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
Loading…
Reference in New Issue