From 87dfb06337b6a72b868c057a9c22dc7d4bcb0d3d Mon Sep 17 00:00:00 2001
From: Jonas Gunz <himself@jonasgunz.de>
Date: Mon, 20 Nov 2023 21:03:59 +0100
Subject: wyoming soundign aggregator

---
 aggregator/wyoming_sounding.py | 108 +++++++++++++++++++++++++++++++++++++++++
 plotter/vertical_from_grib.py  |   9 ++--
 2 files changed, 114 insertions(+), 3 deletions(-)
 create mode 100755 aggregator/wyoming_sounding.py

diff --git a/aggregator/wyoming_sounding.py b/aggregator/wyoming_sounding.py
new file mode 100755
index 0000000..111e219
--- /dev/null
+++ b/aggregator/wyoming_sounding.py
@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+import os
+import datetime
+import requests
+
+import csv
+
+import xarray as xr
+
+import numpy as np
+
+from metpy.units import units
+import metpy.calc as mpcalc
+
+import misc
+
+def get_current_run():
+    date=(datetime.date.today() - datetime.timedelta(days = 1)).strftime('%Y-%m-%d')
+    # TODO we also want noon
+    hour='23:00:00'
+    return (hour, date)
+
+def download_wyoming_csv(station, date, hour, target):
+    url=f'http://weather.uwyo.edu/cgi-bin/bufrraob.py?datetime={date}%20{hour}&id={station}&type=TEXT:CSV'
+    result = requests.get(url)
+
+    if result.status_code >= 400:
+        raise Exception('Failed to Download sounding csv!')
+
+    with open(target, 'w') as f:
+        f.write(result.text)
+
+def load_wyoming_csv(filepath, hour, date):
+    p = []
+    T = []
+    Td = []
+    wind_speed = []
+    wind_dir = []
+    r = []
+
+    with open(filepath,'r', newline='') as f:
+        reader = csv.reader(f)
+        next(reader) # Skip header
+        for row in reader:
+            if sum(map(lambda s : len(s.strip()) == 0, row)):
+                # skip any line with empty values
+                continue
+
+            if float(row[3]) in p: # Skip double p entries
+                continue
+
+            p.append(float(row[3]))
+            T.append(float(row[5]))
+            Td.append(float(row[6]))
+            r.append(float(row[8]))
+            wind_speed.append(float(row[12]))
+            wind_dir.append(float(row[11]))
+
+    T = T * units.degC
+    Td = Td * units.degC
+    wind_speed = wind_speed * units.knots
+    wind_dir = wind_dir * units.degrees
+    u, v = mpcalc.wind_components(wind_speed, wind_dir)
+
+    time = np.datetime64(f'{date}T{hour}')
+
+    # recreate the structure a DWD GRIB produces
+    return xr.Dataset(
+        {
+            "t": (["step", "isobaricInhPa"], [T.to(units.kelvin).magnitude]),
+            "td": (["step", "isobaricInhPa"], [Td.to(units.kelvin).magnitude]),
+            "r": (["step", "isobaricInhPa"], [r]),
+            "u": (["step", "isobaricInhPa"], [u.to('m/s').magnitude]),
+            "v": (["step", "isobaricInhPa"], [v.to('m/s').magnitude]),
+        },
+        coords={
+            "isobaricInhPa":  p,
+            "step": [np.timedelta64(0, 'ns')],
+            "valid_time": (['step'], [time]),
+            "time": time,
+        },
+        attrs={
+            "source": "uwyo.edu",
+        }
+    )
+
+def load_data(name, output, station):
+    hour, date = get_current_run()
+    misc.create_output_dir(output)
+
+    target = os.path.join(output, f'{name}_{date}_{hour}.csv')
+
+    if not os.path.exists(target):
+        download_wyoming_csv(station, date, hour, target)
+    else:
+        print(f'{target} alreasy exists. Using the cached version.')
+
+    return load_wyoming_csv(target, hour, date)
+
+config_debug = {
+    'output': 'wyoming_test',
+    'station': '10548'
+}
+
+if __name__ == '__main__':
+    ds = load_data('test_wyoming_sounding', **config_debug)
+    print(ds)
+    print(ds.coords['step'])
diff --git a/plotter/vertical_from_grib.py b/plotter/vertical_from_grib.py
index 726c8be..79c367f 100755
--- a/plotter/vertical_from_grib.py
+++ b/plotter/vertical_from_grib.py
@@ -34,9 +34,12 @@ def run(data, plots, output='.'):
 
     return index
 
-def _plot(data, output, lat, lon, name, analysis=None):
-    for_temp = data.sel(latitude=lat, longitude = lon, method='nearest')
-    for_temp = for_temp[['r', 't', 'u', 'v']]
+def _plot(data, output, name, lat=None, lon=None, analysis=None):
+    for_temp = data[['r', 't', 'u', 'v']]
+
+    if not (lat is None and lon is None):
+        for_temp = for_temp.sel(latitude=lat, longitude=lon, method='nearest')
+
     index = []
 
     for step in for_temp.coords['step']:
-- 
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