def get_data(usr_case=None):
file_met, usr_case = get_files(usr_case)
index_field, name_field = get_index_field(usr_case)
dfBBY = []
dfCZD = []
dfFRS = []
# period = get_request_dates(usr_case)
for f in file_met:
loc = f[-12:-9]
if loc == "bby":
# elev = 15
# dfBBY.append(mf.parse_surface(
# f, index_field[loc], name_field, elev))
dfBBY.append(mf.parse_surface(f))
elif loc == "czc":
# elev = 462
# dfCZD.append(mf.parse_surface(
# f, index_field[loc], name_field, elev))
dfCZD.append(mf.parse_surface(f))
elif loc == "frs":
# elev = 462
# dfFRS.append(mf.parse_surface(
# f, index_field[loc], name_field, elev))
dfFRS.append(mf.parse_surface(f))
if len(dfBBY) > 1:
meteoBBY = pd.concat(dfBBY)
else:
meteoBBY = dfBBY[0]
if len(dfCZD) > 1:
meteoCZD = pd.concat(dfCZD)
else:
meteoCZD = dfCZD[0]
if len(dfFRS) > 1:
meteoFRS = pd.concat(dfFRS)
else:
try:
meteoFRS = dfFRS[0]
except IndexError:
index = meteoBBY.index
columns = meteoBBY.columns
meteoFRS = pd.DataFrame(index=index, columns=columns)
return meteoBBY, meteoCZD, meteoFRS, usr_case
def get_data(usr_case=None):
file_met, usr_case = get_files(usr_case)
index_field, name_field = get_index_field(usr_case)
dfBBY = []
dfCZD = []
dfFRS = []
# period = get_request_dates(usr_case)
for f in file_met:
loc = f[-12:-9]
if loc == 'bby':
# elev = 15
# dfBBY.append(mf.parse_surface(
# f, index_field[loc], name_field, elev))
dfBBY.append(mf.parse_surface(f))
elif loc == 'czc':
# elev = 462
# dfCZD.append(mf.parse_surface(
# f, index_field[loc], name_field, elev))
dfCZD.append(mf.parse_surface(f))
elif loc == 'frs':
# elev = 462
# dfFRS.append(mf.parse_surface(
# f, index_field[loc], name_field, elev))
dfFRS.append(mf.parse_surface(f))
if len(dfBBY) > 1:
meteoBBY = pd.concat(dfBBY)
else:
meteoBBY = dfBBY[0]
if len(dfCZD) > 1:
meteoCZD = pd.concat(dfCZD)
else:
meteoCZD = dfCZD[0]
if len(dfFRS) > 1:
meteoFRS = pd.concat(dfFRS)
else:
try:
meteoFRS = dfFRS[0]
except IndexError:
index = meteoBBY.index
columns = meteoBBY.columns
meteoFRS = pd.DataFrame(index=index, columns=columns)
return meteoBBY, meteoCZD, meteoFRS, usr_case
def get_surface_data(usr_case, homedir=None):
''' set directory and input files '''
case = 'case' + usr_case.zfill(2)
casedir = homedir + '/' + case
out = os.listdir(casedir)
out.sort()
files = []
for f in out:
if f[-3:] in ['met', 'urf']:
files.append(f)
file_met = []
for f in files:
if f[:3] == 'bby':
file_met.append(casedir + '/' + f)
df = []
for f in file_met:
meteo = mf.parse_surface(f)
df.append(meteo)
if len(df) > 1:
surface = pd.concat(df)
else:
surface = df[0]
return surface
def main(option):
if option == 'compare':
dfBBY = []
dfCZD = []
for f in file_met:
loc = f[-12:-9]
if loc == 'bby':
dfBBY.append(mf.parse_surface(f))
elif loc == 'czc':
dfCZD.append(mf.parse_surface(f))
if len(dfBBY) > 1:
meteoBBY = pd.concat(dfBBY)
else:
meteoBBY = dfBBY[0]
if len(dfCZD) > 1:
meteoCZD = pd.concat(dfCZD)
else:
meteoCZD = dfCZD[0]
make_compare(BBY=meteoBBY, CZD=meteoCZD)
else:
df = []
for f in file_met:
# df.append(mf.parse_surface(f,index_field[usr_loc],name_field,elev[usr_loc]))
df.append(mf.parse_surface(f))
if len(df) > 1:
meteo = pd.concat(df)
else:
meteo = df[0]
make_meteo(meteo)
make_thermo(meteo)
plt.show()
def get_surf(f=None):
surf = mf.parse_surface(f)
sucomp = -surf.wspd * np.sin(np.radians(surf.wdir))
svcomp = -surf.wspd * np.cos(np.radians(surf.wdir))
surf['U'] = sucomp
surf['V'] = svcomp
surf.drop(surf.columns[[0, 1, 2, 5, 6, 7, 8, 9, 10]], axis=1, inplace=True)
g = pd.TimeGrouper('10T')
surfU = surf.U.groupby(g).mean()
surfV = surf.V.groupby(g).mean()
surf10 = pd.DataFrame(data={'U': surfU, 'V': surfV})
return surf10
def get_surf(f=None):
surf = mf.parse_surface(f)
sucomp = -surf.wspd * np.sin(np.radians(surf.wdir))
svcomp = -surf.wspd * np.cos(np.radians(surf.wdir))
surf['U'] = sucomp
surf['V'] = svcomp
surf.drop(surf.columns[[0, 1, 2, 5, 6, 7, 8, 9, 10]], axis=1, inplace=True)
g = pd.TimeGrouper('10T')
surfU = surf.U.groupby(g).mean()
surfV = surf.V.groupby(g).mean()
surf10 = pd.DataFrame(data={'U': surfU, 'V': surfV})
return surf10
def get_pressure(case=None, homedir=None):
from glob import glob
fpath = homedir + '/SURFACE/case{}/bby*'
surf_files = glob(fpath.format(str(case).zfill(2)))
surf_files.sort()
df_list = []
for f in surf_files:
df_list.append(mf.parse_surface(f))
if len(df_list) > 1:
df = pd.concat(df_list)
else:
df = df_list[0]
g = pd.TimeGrouper('60T')
dfg = df['press'].groupby(g).mean()
return dfg
rcParams['mathtext.default'] = 'sf'
def cosd(array):
return np.cos(np.radians(array))
homedir = '/localdata'
topdf = False
case = range(13, 14)
res = 'coarse'
o = 'case{}_total_wind_{}.pdf'
surf_file = '/Users/raulvalenzuela/Data/SURFACE/case13/czc04047.met'
czd = mf.parse_surface(surf_file)
surf_file = '/Users/raulvalenzuela/Data/SURFACE/case13/bby04047.met'
bby = mf.parse_surface(surf_file)
czdh = czd.preciph[~czd.preciph.isnull()]
bbyh = bby.preciph[~bby.preciph.isnull()]
''' creates plot with seaborn style '''
# with sns.axes_style("white"):
# sns.set_style('ticks',
# {'xtick.direction': u'in',
# 'ytick.direction': u'in'}
# )
scale = 1.3
plt.figure(figsize=(8 * scale, 6 * scale))
" first index is mesowest file, second index is \
BBY (1 or more files) "
f = get_filenames(case, homedir)
" parse mesowest data "
meso = mf.parse_mesowest_excel(f[0])
t = get_times(case)
mpress = meso.loc[t[0]:t[1]]['PMSL'].values
mesoidx = meso.loc[t[0]:t[1]].index
" parse surface BBY data "
if len(f[1]) > 1:
' more than one day of obs '
surf = mf.parse_surface(f[1][0])
for ff in f[1][1:]:
surf = surf.append(mf.parse_surface(ff))
else:
' only one day '
surf = mf.parse_surface(f[1][0])
" resample to 1min so we can find \
mesowest index "
surf = surf.resample('1T').interpolate()
" adjust bias is mesowest in case 1 and 2 "
if case in [1, 2]:
bias = 9
else:
'bby': [3, 6, 9, 10, 12, 17, 26],
'czc': [3, 4, 5, 6, 8, 13, 22]
}
else:
index_field = {
'bby': [3, 4, 5, 6, 8, 13, 15],
'czc': [3, 4, 5, 6, 8, 13, 15]
}
''' make dataframe for each station '''
dfBBY = []
dfCZD = []
for f in file_met:
loc = f[-12:-9]
if loc == 'bby':
dfBBY.append(
mf.parse_surface(f, index_field[loc], name_field, elev[loc]))
elif loc == 'czc':
dfCZD.append(
mf.parse_surface(f, index_field[loc], name_field, elev[loc]))
''' concatenate dataframes when there is
more than one day of data '''
if len(dfBBY) > 1:
meteoBBY = pd.concat(dfBBY)
else:
meteoBBY = dfBBY[0]
if len(dfCZD) > 1:
meteoCZD = pd.concat(dfCZD)
else:
meteoCZD = dfCZD[0]
def run(case, tta=None, plot_theory=False, grid=True, ax=None, homedir=None,
color_surf=(0, 0, 0.5, 0.5),color_wp=(0, 0.5, 0, 0.5),
add_date=False, wprof_hgt=None):
" process gapflow analysis"
" first index is mesowest file, second index is \
BBY (1 or more files) "
f = get_filenames(case,homedir)
" parse mesowest data "
meso = mf.parse_mesowest_excel(f[0])
t = get_times(case)
mpress = meso.loc[t[0]: t[1]]['PMSL'].values
mesoidx = meso.loc[t[0]: t[1]].index
" parse surface BBY data "
if len(f[1]) > 1:
' more than one day of obs '
surf = mf.parse_surface(f[1][0])
for ff in f[1][1:]:
surf = surf.append(mf.parse_surface(ff))
else:
' only one day '
surf = mf.parse_surface(f[1][0])
" resample to 1min so we can find \
mesowest index "
surf = surf.resample('1T').interpolate()
" adjust bias is mesowest in case 1 and 2 "
if case in [1, 2]:
bias = 9
else:
bias = 0
spress = surf.loc[mesoidx]['press'].values - bias
" BBY and mesowest pressure difference "
pressDiff = spress - mpress
" BBY surface winds "
swspd = surf.loc[mesoidx]['wspd'].values
swdir = surf.loc[mesoidx]['wdir'].values
ucomp = -swspd*np.sin(np.radians(swdir))
" gapflow dataframe "
d = {'ucomp': ucomp, 'wspd': swspd, 'wdir': swdir,
'pdiff': pressDiff, 'Bpress': spress, 'Kpress': mpress}
gapflow = pd.DataFrame(data=d, index=mesoidx)
" removes rows with NaN "
gapflow = gapflow[np.isfinite(gapflow['Kpress'])]
" add wind profiler data at target altitude "
out = get_windprof(case,
gapflow_time=gapflow.index,
top_hgt_km=wprof_hgt,
homedir=homedir)
wp_wspd, wp_wdir = out
wp_ucomp = -wp_wspd*np.sin(np.radians(wp_wdir))
gapflow['wp_ws'] = wp_wspd
gapflow['wp_wd'] = wp_wdir
gapflow['wp_ucomp'] = wp_ucomp
" Mass etal 95 equation "
# blh = get_BLH(case)
blh = 500 #[m]
massPa, massU = mass_eq(air_density=1.24, BLH=blh)
path = make_polygon(massPa, massU)
gapflow = check_polygon(gapflow, path)
# gapflow['gapflow'] = ((gapflow.poly is True) & (gapflow.wdir <= 120))
# sub = gapflow[(gapflow.poly is True) & (gapflow.wdir <= 120)]
" theoretical lines "
if plot_theory:
if ax is None:
fig, ax = plt.subplots(figsize=(8, 7))
ax.set_xlabel('Pressure difference, BBY-SCK [hPa]')
ax.set_ylabel('BBY zonal wind [m s-1]')
# ax.scatter(gapflow['pdiff'], gapflow['ucomp'],
# color=color_surf, label='surf')
# ax.scatter(gapflow['pdiff'], gapflow['wp_ucomp'],
# color=color_wp, label='wp')
# ax.scatter(sub['pdiff'], sub['ucomp'], color='r')
ax.plot(massPa/100, massU[0], marker=None)
ax.plot(massPa/100, massU[1], linestyle='--', color='r')
ax.plot(massPa/100, massU[2], linestyle='--', color='r')
if grid:
ax.grid(True)
ax.set_xlim([-12, 1])
ax.set_ylim([-20, 15])
ini = mesoidx[0]
end = mesoidx[-1]
date = ini.strftime('%b-%Y ')
beg = ini.strftime('%d')
end = end.strftime('%d')
# ax.text(0.03, 0.76, timetxt.format(str(case).zfill(2),
# date, beg, end),
if add_date is True:
if beg == end:
ax.text(0.03, 0.85,'{} {}'.format(beg,date),
fontsize=12,
transform=ax.transAxes)
else:
ax.text(0.03, 0.85,'{}-{} {}'.format(beg,end,date),
fontsize=12,
transform=ax.transAxes)
return gapflow
name = {"bby": "BodegaBay", "czc": "Cazadero"}
elev = {"bby": 15, "czc": 462}
if usr_case in ["1", "2"]:
index_field = {"bby": [3, 4, 10, 5, 6, 11, 13], "czc": [3, 4, 10, 5, 6, 11, 13]}
elif usr_case in ["3", "4", "5", "6", "7"]:
index_field = {"bby": [3, 6, 9, 10, 12, 17, 26], "czc": [3, 4, 5, 6, 8, 13, 22]}
else:
index_field = {"bby": [3, 4, 5, 6, 8, 13, 15], "czc": [3, 4, 5, 6, 8, 13, 15]}
""" make dataframe for each station """
dfBBY = []
dfCZD = []
for f in file_met:
loc = f[-12:-9]
if loc == "bby":
dfBBY.append(mf.parse_surface(f, index_field[loc], name_field, elev[loc]))
elif loc == "czc":
dfCZD.append(mf.parse_surface(f, index_field[loc], name_field, elev[loc]))
""" concatenate dataframes when there is
more than one day of data """
if len(dfBBY) > 1:
meteoBBY = pd.concat(dfBBY)
else:
meteoBBY = dfBBY[0]
if len(dfCZD) > 1:
meteoCZD = pd.concat(dfCZD)
else:
meteoCZD = dfCZD[0]
rcParams['mathtext.default'] = 'sf'
def cosd(array):
return np.cos(np.radians(array))
homedir = '/localdata'
topdf = False
case = range(13,14)
res = 'coarse'
o = 'case{}_total_wind_{}.pdf'
# surf_file = '/Users/raulvalenzuela/Data/SURFACE/case13/czc04047.met'
surf_file = '/localdata/SURFACE/case13/czc04047.met'
czd = mf.parse_surface(surf_file)
czdh = czd.preciph[~czd.preciph.isnull()]
surf_file = '/localdata/SURFACE/case13/bby04047.met'
bby = mf.parse_surface(surf_file)
bbyh = bby.preciph[~czd.preciph.isnull()]
''' creates plot with seaborn style '''
# with sns.axes_style("white"):
# sns.set_style('ticks',
# {'xtick.direction': u'in',
# 'ytick.direction': u'in'}
# )
scale=1.3
plt.figure(figsize=(8*scale, 6*scale))
