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flightbit/pipeline/rap_wave.py
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''' | |
Generates sounding file and thermal statistics | |
''' | |
import os | |
import pandas as pd | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import seaborn; seaborn.set() | |
snd_cols = ['LEVEL', 'HGT', 'TMP', 'RH', 'UGRD', 'VGRD', 'VVEL'] | |
def valueFromGrib(df_grib, field, level): | |
try: | |
return df_grib[(df_grib.FIELD == field) & (df_grib.LEVEL == level)].iloc[0]['VALUE'] | |
except IndexError: | |
print field, "at", level, "not found." | |
return None | |
def generateRAOB(df_grib, snd_file): | |
snd_time = df_grib.iloc[0]['START'] | |
snd_lon = df_grib.iloc[0]['LON'] | |
snd_lat = df_grib.iloc[0]['LAT'] | |
# Surface heigth | |
snd_hgt = valueFromGrib(df_grib, 'HGT', 'surface') | |
snd_series = [] | |
for col in snd_cols[1:]: | |
snd_series.append(df_grib.loc[df_grib['FIELD'] == col][['LEVEL', 'VALUE']].rename(columns={'VALUE': col})) | |
df_snd = reduce(lambda left, right: pd.merge(left, right, on='LEVEL'), snd_series) | |
# Convert the level to a numeric | |
df_snd['LEVEL'] = df_snd['LEVEL'].map(lambda x: x.rstrip(' mb')) | |
df_snd['LEVEL'] = pd.to_numeric(df_snd['LEVEL']) | |
df_snd = df_snd[(df_snd['HGT'] >= snd_hgt) & (df_snd['LEVEL'] >= 100)].reset_index(drop=True) | |
# Sort by level | |
df_snd = df_snd.sort_values(['LEVEL'], ascending=[0]) | |
# Heigth in feet | |
df_snd['HGT_FT'] = df_snd.HGT * 3.28084 | |
# Round the relative humidity | |
df_snd['RH'] = df_snd['RH'].astype(int) | |
# Wind Speed | |
df_snd['W_SPD_MS'] = (df_snd.UGRD ** 2 + df_snd.VGRD ** 2) ** (0.5) | |
# Wind Direction | |
df_snd['W_DIR'] = np.arctan2(df_snd.UGRD, df_snd.VGRD) * (180. / np.pi) | |
# Temperature in Celcius | |
df_snd['TMP_C'] = df_snd.TMP - 273.15 | |
# Scorer Parameter | |
Ys = [] | |
for i, row in df_snd.iterrows(): | |
if (i < len(df_snd.index) - 1): | |
Ys.append((df_snd.TMP_C.iloc[i + 1] - df_snd.TMP_C.iloc[i]) / (df_snd.HGT.iloc[i] - df_snd.HGT.iloc[i + 1])) | |
df_snd['Y'] = pd.Series(Ys) | |
df_snd['Y2'] = (((0.00986 - df_snd.Y) / df_snd.TMP) * (9.81 / df_snd.W_SPD_MS ** 2) - (1 / 4) * ( | |
(9.81 / 287 - df_snd.Y) / df_snd.TMP) ** 2) * 100000 | |
wave_file = snd_file + ".wave" | |
df_snd.to_csv(wave_file, index=False) | |
# Plot the Scorer Parameter | |
ax = df_snd.plot(x='Y2', y='HGT_FT', xlim=(0,0.3), ylim=(0,18000), title="Scorer Parameter", legend=False) | |
ax.axhline(y=13600, c="blue", linewidth=2.0, zorder=0) | |
fig = ax.get_figure() | |
fig.savefig(snd_file + '.png') | |
if __name__ == '__main__': | |
snd_file = raw_input("File to convert: ") | |
if os.path.isfile(snd_file): | |
df_grib = pd.read_csv(snd_file, | |
names=['START', 'END', 'FIELD', 'LEVEL', 'LON', 'LAT', 'VALUE']) | |
generateRAOB(df_grib, snd_file) | |
else: | |
print "Not a valid file!" |