def plotTile_patches(lonc, latc, lonv, latv, data):
"""
plot the tile using matplotlib patcheCollection
"""
from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection
# need to flip the raster upside down
data = np.flipud(data)
## delta for calculating cell vertices from cell center
dlon = lonc[0] - lonc[1] / 2.
dlat = latc[0] - latc[1] / 2.
#lonp = np.zeros([len(lon), 4])
#latp = np.zeros([len(lat), 4])
patches = []
for i, llon in enumerate(lonc):
for j, llat in enumerate(latc):
lon_w = llon - dlon
lon_e = llon + dlon
lat_n = llat + dlat
lat_s = llat - dlat
## counter-clockwise vertices for each cell
xp = np.asarray([lon_w, lon_e, lon_e, lon_w])
yp = np.asarray([lat_s, lat_n, lat_n, lat_s])
patches.append(Polygon(np.vstack([xp, yp]).T))
pdb.set_trace()
cmap = 'viridis'
pc = PatchCollection(patches, cmap=cmap)
pc.set_array(data.flatten())
pc.set_lw(0.1)
plt.rcParams.update({'font.size': 18})
fig = plt.figure(figsize=(12, 6))
ax = fig.add_subplot(111)
ax.add_collection(pc)
ax.set_xlim([lonv.min(), lonv.max()])
ax.set_ylim([latv.min(), latv.max()])
ax.set_aspect('equal')
plt.show()
def plot_poly(colors,
cells,
nvertices,
x,
y,
xc=None,
yc=None,
xperiod=None,
yperiod=None,
colorbar=True,
cmap='viridis'):
""" from https://gist.github.com/pwolfram/2745eaccaf33f222fed6"""
patches = []
for ii, (ac, nv) in enumerate(zip(cells, nvertices)):
ac = np.asarray(ac[:nv], dtype='int')
xp = x[ac]
yp = y[ac]
if xc is not None:
xp = fix_periodicity(xp, xc[ii], xperiod)
if yc is not None:
yp = fix_periodicity(yp, yc[ii], yperiod)
patches.append(Polygon(zip(xp, yp)))
pc = PatchCollection(patches, cmap=cmap, alpha=1.0)
pc.set_array(colors)
pc.set_edgecolor('face')
pc.set_lw(0.1)
plt.figure()
ax = plt.gca()
ax.add_collection(pc)
ax.set_aspect('equal')
ax.autoscale_view()
if colorbar:
plt.colorbar(pc)
return pc
def plot_target(data_temp, var_temp, start_indices_temp, end_indices_temp,
out_dir_temp):
#Set some strings
if var_temp == 'rad_continuum_o2':
var_string = 'o2_radiance'
var_cbar_string = 'Radiance [Ph s' + r'$^{-1}$' + ' m' + r'$^{-2}$' + ' sr' + r'$^{-1}$' + r'$\mu$' + 'm' + r'$^{-1}$' + ']'
var_title_string = "O" + r'$_2$' + ' A-Band Radiance'
var_cbar = plt.cm.Purples_r
elif var_temp == 'xco2':
var_string = 'xco2'
var_cbar_string = r'$X_{CO_2}$' + ' [ppm]'
var_title_string = r'$X_{CO_2}$'
var_cbar = plt.cm.viridis
elif var_temp == 'dp':
var_string = 'dp'
var_cbar_string = 'dp [hPa]'
var_title_string = 'dp'
var_cbar = plt.cm.RdBu_r
elif var_temp == 'aod_total':
var_string = 'aod'
var_cbar_string = 'AOD'
var_title_string = 'AOD'
var_cbar = plt.cm.magma
else:
print("Please select an appropriate variable...")
############################################
#Plot all the individual TG/AMs!
for i in range(len(start_indices_temp)):
print(
"---------------------------------------------------------------")
print("Plotting TG/AM ", str(i + 1), " of ", len(start_indices_temp))
data_temp2 = data_temp[start_indices_temp[i]:end_indices_temp[i]]
print(data_temp2['target_id'][0], int(data_temp2['orbit'][0]),
data_temp2['sounding_id'][0])
#Remove weird outliers that are far from the actual TG/AM
cluster_input = np.array(
[data_temp2['longitude'], data_temp2['latitude']]).T
try:
clusters = hcluster.fclusterdata(cluster_input,
1.,
criterion='distance')
print("Cluster #s = ", np.bincount(clusters))
#Grab the largest cluster, or any/all clusters greater than 30 soundings
cluster_mask = (clusters == np.argmax(
np.bincount(clusters))) | np.isin(
clusters,
np.where(np.bincount(clusters) > 30)[0])
except:
#If there's exactly one sounding, fclusterdata doesn't work
cluster_mask = np.ones(len(data_temp2), dtype=bool)
#Determine plotting box
N,S,E,W = np.round(max(data_temp2['target_lat'][cluster_mask][0],data_temp2['latitude'][cluster_mask].max())+.25,1),\
np.round(min(data_temp2['target_lat'][cluster_mask][0],data_temp2['latitude'][cluster_mask].min())-.25,1),\
np.round(max(data_temp2['target_lon'][cluster_mask][0],data_temp2['longitude'][cluster_mask].max())+(.25/np.cos(np.deg2rad(max(data_temp2['target_lat'][cluster_mask][0],data_temp2['latitude'][cluster_mask].max())))),1),\
np.round(min(data_temp2['target_lon'][cluster_mask][0],data_temp2['longitude'][cluster_mask].min())-(.25/np.cos(np.deg2rad(min(data_temp2['target_lat'][cluster_mask][0],data_temp2['latitude'][cluster_mask].min())))),1)
#And keep anything within the plotting box
data_temp2 = data_temp2[(data_temp2['latitude'] < N)
& (data_temp2['latitude'] > S) &
(data_temp2['longitude'] < E) &
(data_temp2['longitude'] > W)]
#Get some datetime info from the sounding_id
month_str = calendar.month_abbr[int(
data_temp2['sounding_id'][0].astype(str)[4:6].lstrip("0"))]
day_str, year_str = data_temp2['sounding_id'][0].astype(
str)[6:8].lstrip("0"), data_temp2['sounding_id'][0].astype(
str)[:4].lstrip("0")
hour_str, minute_str = data_temp2['sounding_id'][0].astype(
str)[8:10], data_temp2['sounding_id'][0].astype(str)[10:12]
#Check if the .png exists already. If not, make it!
if os.path.isfile(out_dir_temp + '/' +
data_temp2['production_string'][0].astype(str) +
'/' + var_string + '/OCO3_' +
data_temp2['production_string'][0].astype(str) +
"_" + var_string + '_' +
str(data_temp2['sounding_id'][0])[:8] + '_' +
str(int(data_temp2['orbit'][0])) + "_" +
data_temp2['target_id'][0].astype(str) + '.png'):
print(out_dir_temp + '/' +
data_temp2['production_string'][0].astype(str) + '/' +
var_string + '/OCO3_' +
data_temp2['production_string'][0].astype(str) + "_" +
var_string + '_' + str(data_temp2['sounding_id'][0])[:8] +
'_' + str(int(data_temp2['orbit'][0])) + "_" +
data_temp2['target_id'][0].astype(str) +
'.png already exists!')
else:
fig, ax1 = plt.subplots(figsize=[20, 20])
m1 = Basemap(llcrnrlon=W,
llcrnrlat=S,
urcrnrlon=E,
urcrnrlat=N,
epsg=3857,
resolution='h')
try:
m1.arcgisimage(service='World_Imagery',
xpixels=2000,
verbose=True)
except:
#Sometimes this fails randomly, so try again
time.sleep(20)
m1.arcgisimage(service='World_Imagery',
xpixels=2000,
verbose=True)
m1.drawmeridians(np.linspace(W, E, 6)[1:-1],
labels=[0, 0, 0, 1],
size=24,
color='0.75')
m1.drawparallels(np.linspace(N, S, 6)[1:-1],
labels=[1, 0, 0, 0],
size=24,
color='0.75')
m1.drawcoastlines()
#Map Scale. Have to hack because the Basemap drawmapscale function is broken, but this should work. Cartopy doesn't even have a map scale function.
lat0 = S + (N - S) * 0.04 + 0.02 #0.04
lon0 = W + (E - W) * 0.04
distance = 40. / np.cos(lat0 * np.pi / 180.)
corner_buffered_m1 = m1(lon0, lat0)
corner_buffered_lon, corner_buffered_lat = m1(
corner_buffered_m1[0] + (distance / 2 * 1000),
corner_buffered_m1[1],
inverse=True)
scale = m1.drawmapscale(corner_buffered_lon,
corner_buffered_lat,
corner_buffered_lon,
corner_buffered_lat,
distance,
units='km',
fontcolor='w',
fontsize=16,
yoffset=2000)
scale[3].set_text(40)
#Plot footprints
x1, y1 = m1(data_temp2['vertex_longitude_1'],
data_temp2['vertex_latitude_1'])
x2, y2 = m1(data_temp2['vertex_longitude_2'],
data_temp2['vertex_latitude_2'])
x3, y3 = m1(data_temp2['vertex_longitude_3'],
data_temp2['vertex_latitude_3'])
x4, y4 = m1(data_temp2['vertex_longitude_4'],
data_temp2['vertex_latitude_4'])
patches = []
for i in range(len(x1)):
if (x1[i] == 0.0) | (x2[i] == 0.0) | (x3[i] == 0.0) | (x4[i]
== 0.0):
print("Bad vertex...")
else:
patches += [
Polygon([(x1[i], y1[i]), (x2[i], y2[i]),
(x3[i], y3[i]), (x4[i], y4[i])])
]
p = PatchCollection(patches, alpha=1.)
p.set_array(data_temp2[var_temp])
if var_temp == 'dp':
p.set_clim(
-1 * max(np.abs(np.percentile(data_temp2[var_temp], 10)),
np.abs(np.percentile(data_temp2[var_temp], 90))),
max(np.abs(np.percentile(data_temp2[var_temp], 10)),
np.abs(np.percentile(data_temp2[var_temp], 90))))
elif var_temp == 'aod_total':
p.set_clim(0, max(0.3, np.percentile(data_temp2[var_temp],
90)))
else:
p.set_clim(np.percentile(data_temp2[var_temp], 10),
np.percentile(data_temp2[var_temp], 90))
p.set_lw(1.0)
p.set_cmap(var_cbar)
ax1.add_collection(p)
#Colorbar
divider = make_axes_locatable(ax1)
cax = divider.append_axes("right", size=0.4, pad=0.25)
if var_temp == 'aod_total':
cbar = fig.colorbar(p, extend='max', cax=cax)
else:
cbar = fig.colorbar(p, extend='both', cax=cax)
cbar.set_label(var_cbar_string, size=28, rotation=270, labelpad=35)
cbar.ax.tick_params(labelsize=22)
cbar.ax.yaxis.get_offset_text().set_fontsize(22)
#Title
title = ax1.set_title(
'OCO-3 ' + var_title_string + '\n' +
data_temp2['sounding_operation_mode_string'][0].astype(str) +
' Mode (' +
data_temp2['sounding_pcs_data_source_string'][0].astype(str) +
'), ' + data_temp2['target_id'][0].astype(str) + ', "' +
data_temp2['target_name'][0].astype(str) + '"\n' +
data_temp2['production_string'][0].astype(str) + '\n' +
hour_str + ':' + minute_str + ' UTC ' + day_str + ' ' +
month_str + ' ' + year_str + ', Orbit ' +
str(int(data_temp2['orbit'][0])),
size=30,
y=1.01)
#Time stamp
plt.text(0.99,
0.01,
"Created " + str(datetime.datetime.now().day) + ' ' +
calendar.month_abbr[datetime.datetime.now().month] + ' ' +
str(datetime.datetime.now().year) +
"\nCourtesy NASA/JPL-Caltech (R. R. Nelson)",
ha='right',
va='bottom',
transform=ax1.transAxes,
color='1.0',
size=18)
#Preliminary data stamp
plt.text(0.01,
0.99,
"PRELIMINARY (vEarly)",
ha='left',
va='top',
transform=ax1.transAxes,
color='r',
size=18)
#Globe inset
ax2 = inset_axes(ax1, width=2., height=2.)
m2 = Basemap(projection='ortho',
lat_0=((N + S) / 2.),
lon_0=((E + W) / 2.),
resolution='l')
m2.bluemarble()
x1_globe, y1_globe = m2(((W + E) / 2.), ((N + S) / 2.))
m2.scatter(x1_globe, y1_globe, c='r', s=100, marker='*')
#Mark the target
x1_target, y1_target = m1(data_temp2['target_lon'][0],
data_temp2['target_lat'][0])
ax1.scatter(x1_target, y1_target, c='r', marker="*", s=600)
#Create save directory if it doesn't exist
if not os.path.exists(
out_dir_temp + '/' +
data_temp2['production_string'][0].astype(str) + '/' +
var_string):
os.makedirs(out_dir_temp + '/' +
data_temp2['production_string'][0].astype(str) +
'/' + var_string)
#Save figure
print("Saving as " + out_dir_temp + '/' +
data_temp2['production_string'][0].astype(str) + '/' +
var_string + '/OCO3_' +
data_temp2['production_string'][0].astype(str) + "_" +
var_string + '_' + str(data_temp2['sounding_id'][0])[:8] +
'_' + str(int(data_temp2['orbit'][0])) + "_" +
data_temp2['target_id'][0].astype(str) + '.png')
def plotSparseMatrix(matrix, chrom, vmin, vmax, RF_dict, output_filepath):
"Plots HIFI sparse matrix using Python's Matplotlib module"
plt.ioff() #prevent view window from openning over ssh connection
fig, ax = plt.subplots(figsize=(8, 8))
#create heat map using 'PatchCollection' rectangles and associated coordinates
x = 0.0
patches, colours = [], []
y = sum(RF_dict["y"]["sizes"])
for i, row_height in enumerate(RF_dict["y"]["sizes"]):
y -= row_height
for j, col_width in enumerate(RF_dict["x"]["sizes"]):
colours.append(matrix[i][j])
patch = Rectangle((x, y), col_width, row_height)
patches.append(patch)
x += col_width
x = 0.0
#plot 'PatchCollection' of rectangles
pc = PatchCollection(patches, cmap=cmap)
pc.set_clim([vmin, vmax])
pc.set_array(np.array(colours))
pc.set_edgecolor("face")
pc.set_lw(0.1)
ax.add_collection(pc)
#remove outline from color bar
cbar = plt.colorbar(pc, fraction=0.04575, pad=0.04)
cbar.outline.set_visible(False)
cbar.ax.tick_params(labelsize=16, length=4, width=0.5, color="grey")
ax.tick_params(axis="x",
which="both",
bottom=False,
top=False,
direction="out",
length=4,
width=0.5,
pad=10,
color="grey",
labelsize=16)
ax.xaxis.set_label_position("top")
ax.set_xlabel(RF_dict["x"]["label"], fontsize=16, labelpad=8.25)
ax.xaxis.tick_top()
ax.tick_params(axis="y",
which="both",
left=False,
right=False,
direction="out",
length=4,
width=0.5,
color="grey",
labelsize=16)
ax.set_ylabel(RF_dict["y"]["label"], fontsize=16, labelpad=None)
ax.grid(False)
# remove x and y ticks
plt.xticks([], [])
plt.yticks([], [])
# remove axis edges
for axis in ["bottom", "top", "left", "right"]:
plt.gca().spines[axis].set_visible(False)
ax.set_aspect("equal")
plt.tight_layout()
plt.savefig(output_filepath + ".png",
format="png",
dpi=600,
transparent=False,
bbox_inches="tight")
plt.savefig(output_filepath + ".pdf",
format="pdf",
transparent=False,
bbox_inches="tight")
plt.close()
#save matrix
np.savetxt(output_filepath + ".csv", matrix, delimiter=",")
