def main(gliders, save_dir, g_t0, g_t1, xlims, ylims):
# initialize keyword arguments for glider functions
gargs = dict()
gargs['time_start'] = g_t0
gargs['time_end'] = g_t1
gargs['filetype'] = 'dataframe'
t0 = g_t0.strftime('%Y-%m-%d')
t1 = g_t1.strftime('%Y-%m-%d')
t = np.arange(xlims['temperature'][0], xlims['temperature'][1], xlims['temperature'][2])
t = np.append(t, xlims['temperature'][1])
s = np.arange(xlims['salinity'][0], xlims['salinity'][1], xlims['salinity'][2])
s = np.append(s, xlims['salinity'][1])
d = np.arange(xlims['density'][0], xlims['density'][1], xlims['density'][2])
d = np.append(d, xlims['density'][1])
for glider in gliders:
sdir_glider = os.path.join(save_dir, glider, 'transects', 'transect-ribbons')
os.makedirs(sdir_glider, exist_ok=True)
glider_df = gld.glider_dataset(glider, **gargs)
# cm = plt.get_cmap('RdYlBu', 10)
# cmap = cmocean.tools.cmap(cmocean.cm.thermal, N=10)
cmdict = cmocean.tools.get_dict(cmocean.cm.thermal, N=t.shape[0]-1)
thermal = LinearSegmentedColormap(cmocean.cm.thermal, segmentdata=cmdict, N=t.shape[0]-1)
cmdict = cmocean.tools.get_dict(cmocean.cm.haline, N=s.shape[0]-1)
haline = LinearSegmentedColormap(cmocean.cm.haline, segmentdata=cmdict, N=s.shape[0]-1)
cmdict = cmocean.tools.get_dict(cmocean.cm.dense, N=d.shape[0]-1)
dense = LinearSegmentedColormap(cmocean.cm.dense, segmentdata=cmdict, N=d.shape[0]-1)
# temperature section... time on x axis.. depth on y axis... color- temperature
fig, ax = plt.subplots(figsize=(16, 8))
plt.scatter(glider_df['time'],
glider_df['depth'],
20,
glider_df['temperature'],
cmap=thermal.reversed(thermal),
vmin=t[0],
vmax=t[-1]
)
plt.ylim(ylims)
cb = plt.colorbar()
cb.ax.tick_params(labelsize=14)
cb.set_label('Temperature (°C)', fontsize=16)
# Add the grid
plt.grid()
plt.xticks(rotation=45, fontsize=16)
plt.yticks(fontsize=16)
xfmt = mdates.DateFormatter('%d-%b-%Y\n%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
plt.title(f'Temperature Section for Glider: {glider}\nStart: {t0}, End: {t1}',
fontsize=20, fontweight='bold')
plt.xlabel('Time (GMT)', fontsize=18, fontweight='bold')
plt.ylabel('Depth (m)', fontsize=18, fontweight='bold')
plt.savefig(f'/Users/mikesmith/Documents/{glider}-temperature-{t0}-{t1}', bbox_inches='tight', pad_inches=0.1, dpi=300)
plt.close()
fig, ax = plt.subplots(figsize=(16, 8))
plt.scatter(glider_df['time'],
glider_df['depth'],
20,
glider_df['salinity'],
cmap=haline.reversed(haline),
vmin=s[0],
vmax=s[-1]
)
plt.ylim(ylims)
cb = plt.colorbar()
cb.ax.tick_params(labelsize=14)
cb.set_label('Salinity (1)', fontsize=16)
plt.grid()
plt.xticks(rotation=45, fontsize=16)
plt.yticks(fontsize=16)
xfmt = mdates.DateFormatter('%d-%b-%Y\n%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
plt.title(f'Salinity Section for Glider: {glider}\nStart: {t0}, End: {t1}', fontsize=20,
fontweight='bold')
plt.xlabel('Time (GMT)', fontsize=18, fontweight='bold')
plt.ylabel('Depth (m)', fontsize=18, fontweight='bold')
plt.savefig(f'/Users/mikesmith/Documents/{glider}-salinity-{t0}-{t1}', bbox_inches='tight', pad_inches=0.1, dpi=300)
plt.close()
# Density profile cross section
fig, ax = plt.subplots(figsize=(16, 8))
plt.scatter(glider_df['time'],
glider_df['depth'],
20,
glider_df['density'],
cmap=dense.reversed(dense),
vmin=d[0],
vmax=d[-1]
)
plt.ylim(ylims)
cb = plt.colorbar()
cb.ax.tick_params(labelsize=14)
cb.set_label('Density (kg m-3)', fontsize=16)
plt.grid()
plt.xticks(rotation=45, fontsize=16)
plt.yticks(fontsize=16)
xfmt = mdates.DateFormatter('%d-%b-%Y\n%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
plt.title(f'Density Section for Glider: {glider}\nStart: {t0}, End: {t1}', fontsize=20,
fontweight='bold')
plt.xlabel('Time (GMT)', fontsize=18, fontweight='bold')
plt.ylabel('Depth (m)', fontsize=18, fontweight='bold')
plt.savefig(f'/Users/mikesmith/Documents/{glider}-density-{t0}-{t1}', bbox_inches='tight', pad_inches=0.1, dpi=300)
plt.close()
# Profile plotting
grouped = glider_df.groupby([pd.Grouper(freq='1D', key='time')])
cmap = get_cmap(len(grouped))
fig, ax = plt.subplots(figsize=(10, 12))
grouped = list(grouped)
for i in range(len(grouped)):
# temperature profile... y axis - depth, x axis. - temperature. color- time
plt.scatter(grouped[i][1]['temperature'],
grouped[i][1]['depth'],
12,
cmap=cmap(i),
label=grouped[i][0].strftime('%Y-%m-%d'))
plt.ylim(ylims)
# plt.xlim([t[0], t[-1]])
plt.xlim([11, 23])
plt.legend(fontsize=14)
# Add the grid
plt.grid()
plt.xticks(fontsize=16)
plt.yticks(fontsize=16)
plt.title(f'Temperature Profile for Glider: {glider}\nStart: {t0}, End: {t1}',
fontsize=20, fontweight='bold')
plt.xlabel('Temperature (°C)', fontsize=18, fontweight='bold')
plt.ylabel('Depth (m)', fontsize=18, fontweight='bold')
plt.savefig(f'/Users/mikesmith/Documents/{glider}-temperature-profile-{t0}-{t1}', bbox_inches='tight', pad_inches=0.1,
dpi=300)
plt.close()
fig, ax = plt.subplots(figsize=(10, 12))
for i in range(len(grouped)):
plt.scatter(grouped[i][1]['salinity'],
grouped[i][1]['depth'],
12,
cmap=i,
label=grouped[i][0].strftime('%Y-%m-%d'))
plt.ylim(ylims)
# plt.xlim([s[0], s[-1]])
plt.xlim([31, 35])
plt.legend(fontsize=14)
# Add the grid
plt.grid()
plt.xticks(fontsize=16)
plt.yticks(fontsize=16)
plt.title(f'Salinity Profile for Glider: {glider}\nStart: {t0}, End: {t1}', fontsize=20,
fontweight='bold')
plt.xlabel('Salinity (1)', fontsize=18, fontweight='bold')
plt.ylabel('Depth (m)', fontsize=18, fontweight='bold')
# plt.show()
plt.savefig(f'/Users/mikesmith/Documents/{glider}-salinity-profile-{t0}-{t1}', bbox_inches='tight', pad_inches=0.1,
dpi=300)
plt.close()
fig, ax = plt.subplots(figsize=(10, 12))
for i in range(len(grouped)):
plt.scatter(grouped[i][1]['density'],
grouped[i][1]['depth'],
12,
cmap=i,
label=grouped[i][0].strftime('%Y-%m-%d'))
plt.ylim(ylims)
plt.xlim([d[0], d[-1]])
plt.legend(fontsize=14)
# Add the grid
plt.grid()
plt.xticks(fontsize=16)
plt.yticks(fontsize=16)
plt.title(f'Density Profile for Glider: {glider}\nStart: {t0}, End: {t1}', fontsize=20,
fontweight='bold')
plt.xlabel('Density (kg m-3)', fontsize=18, fontweight='bold')
plt.ylabel('Depth (m)', fontsize=18, fontweight='bold')
# plt.show()
plt.savefig(f'/Users/mikesmith/Documents/{glider}-density-profile-{t0}-{t1}', bbox_inches='tight', pad_inches=0.1,
dpi=300)
plt.close()
# Change current working directory to parent directory
os.chdir('..')
# Import from functions file
import sys
from AEGW_functions import *
from cmapstore import *
# cmaps
rdbucmap = LinearSegmentedColormap('RDBUcmap',
segmentdata=fetchcmap('RdBunew'),
N=265)
whitehatchescmap_r = LinearSegmentedColormap(
'Whitehatchescmap', segmentdata=fetchcmap('whitehatches'), N=265)
whitehatchescmap = whitehatchescmap_r.reversed()
# matplotlib settings
matplotlib.rcParams['axes.unicode_minus'] = False
########################################################################
####### The settings in this section can be altered by the user ########
########################################################################
# Please note, the plots created by this program use MATLAB files #
# created by Corwin Wright, saved as two separate files for the before #
# and after orbital sections, as a concatenation of AIRS granules #
# 54 + 55 + 56 and 189 + 190 + 191. Below, the original netCDF files #
# are also loaded, in case the user prefers to use these instead. #
########################################################################
# Find directory and read AIRS netCDF data
strdirectory = './AIRS_Data/'
