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1 files changed, 0 insertions, 107 deletions

diff --git a/skewt.py b/skewt.py
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--- a/skewt.py
+++ /dev/null
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-#!/usr/bin/env python3
-
-# https://unidata.github.io/MetPy/latest/examples/plots/Skew-T_Layout.html#sphx-glr-examples-plots-skew-t-layout-py
-
-import matplotlib.gridspec as gridspec
-import matplotlib.pyplot as plt
-
-import csv
-
-import metpy.calc as mpcalc
-from metpy.cbook import get_test_data
-from metpy.plots import add_metpy_logo, Hodograph, SkewT
-from metpy.units import units
-
-import datetime
-import requests
-
-
-STATION=10548
-DATE=(datetime.date.today() - datetime.timedelta(days = 1)).strftime('%Y-%m-%d')
-TIME='23:00:00'
-# http://weather.uwyo.edu/cgi-bin/bufrraob.py?datetime=2023-07-20%2023:00:00&id=10548&type=TEXT:CSV
-URL=f'http://weather.uwyo.edu/cgi-bin/bufrraob.py?datetime={DATE}%20{TIME}&id={STATION}&type=TEXT:CSV'
-print(URL)
-
-result = requests.get(URL)
-RAW_DATA_LINES=result.content.decode('UTF-8').splitlines()
-#RAW_DATA_LINES= open('data.csv').readlines()
-
-p = []
-T = []
-Td = []
-wind_speed = []
-wind_dir = []
-
-csvreader = csv.reader(RAW_DATA_LINES, dialect='excel')
-next(csvreader) # Skip header
-for row in csvreader:
-    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]))
-    wind_speed.append(float(row[12]))
-    wind_dir.append(float(row[11]))
-
-
-p = p * units.hPa
-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)
-
-ground_parcel= mpcalc.parcel_profile(p, T[0], Td[0])
-ccl = mpcalc.ccl(p,T,Td)
-lcl = mpcalc.lcl(p[0],T[0],Td[0])
-
-ccl_ground=mpcalc.dry_lapse(p[:1], ccl[1], ccl[0])
-ccl_ground_parcel= mpcalc.parcel_profile(p, ccl_ground[0], Td[0])
-
-# Create a new figure. The dimensions here give a good aspect ratio
-fig = plt.figure(figsize=(9, 9))
-
-# Grid for plots
-gs = gridspec.GridSpec(3, 3)
-skew = SkewT(fig, rotation=45, subplot=gs[:, :])
-
-# Plot the data using normal plotting functions, in this case using
-# log scaling in Y, as dictated by the typical meteorological plot
-skew.plot(p, T, 'r')
-skew.plot(p, Td, 'g')
-skew.plot(p, ground_parcel, 'b')
-skew.plot(p, ccl_ground_parcel, 'y')
-
-barb_div = int(len(p)/20)
-skew.plot_barbs(p[::barb_div], u[::barb_div], v[::barb_div])
-
-skew.plot(lcl[0], lcl[1], 'o', markerfacecolor='black')
-skew.plot(ccl[0], ccl[1], 'o', markerfacecolor='red')
-
-skew.shade_cape(p,T,ground_parcel)
-skew.shade_cin(p,T,ground_parcel)
-
-skew.ax.set_ylim(1000, 100)
-
-# Add the relevant special lines
-skew.plot_dry_adiabats()
-skew.plot_moist_adiabats()
-skew.plot_mixing_lines()
-
-# Good bounds for aspect ratio
-skew.ax.set_xlim(-30, 40)
-
-# Create a hodograph
-ax = fig.add_subplot(gs[0, -1])
-h = Hodograph(ax, component_range=60.)
-h.add_grid(increment=20)
-h.plot(u[::barb_div], v[::barb_div])
-
-# Show the plot
-plt.show()