def plotAWAP_original(var_time, Dict):
"""
Plot uninterpolated AWAP data.
"""
m
[lonall, latall] = np.meshgrid((Dict['lon']), (Dict['lat']))
x, y = m(lonall, latall)
cs = m.pcolor(x, y, var_time, vmin=Dict['vmin'], vmax=Dict['vmax'])
cbar = m.colorbar(cs, location='right', pad="1%")
cbarLabel = "%s" % (Dict['var_units'])
cbar.set_label(cbarLabel)
return plt
def plotAWAP_original(var_time,Dict):
"""
Plot uninterpolated AWAP data.
"""
m
[lonall,latall] = np.meshgrid((Dict['lon']),(Dict['lat']))
x,y = m(lonall,latall)
cs = m.pcolor(x,y,var_time,vmin=Dict['vmin'],vmax=Dict['vmax'])
cbar = m.colorbar(cs, location='right', pad="1%")
cbarLabel = "%s" %(Dict['var_units'])
cbar.set_label(cbarLabel)
return plt
def plot(var_time, Dict, labels=False, grid=False, oceans=False, cbar=True):
"""
A function to plot and display a basic plot of ACCESS,
AWAP, or HadISST datasets.
Parameters:
-----------
var_time : The variable to be plotted. Use the imported
data from access_prepare_ts, hadisst_prepare,
awap_prepare, access_prepare_pr or access_trimmed.
Dict : a dictionary defining various
variables needed for the dataset to be plotted.
The dictionaries are defined above in the
mapAWAP(), mapACCESSpr(), mapACCESSts(), mapACCESSpr_tr() and
mapHadisst() functions.
labels : (default = False)
Adds axis labels for longitude/latitude if "True".
grid : (default = False)
If set to "True", the a grid is superimposed over
the map at the 1.25 (lat) by 1.875 (lon) degree
resolution. If set to "False", only the latitudes/
longitudes that show the dimensions of the box are
plotted.
If set to "Simple", only the boundary lat/lon
values for the map are shown (no grid-lines).
oceans : (default = False)
If set to "True", ocean regions remain unmaskeded
and are plotted; if set to "False", the oceans are
not plotted.
cbar : (default = True)
Plots a colour-bar if set to "True".
"""
m
[lonall, latall] = np.meshgrid((Dict['lon']), (Dict['lat']))
x, y = m(lonall, latall)
if grid == True:
gridWhole(-47.5, -7.5, 1.25, 112.5, 157.5, 1.875)
gridLabels(-47.5, -7.5, 2.5, 112.5, 159.375, 7.5)
elif grid == 'Simple':
gridLabels(-40.0, 0.0, 10.0, 110.0, 160.0, 10.0)
elif grid == 'Ticks':
gridLabels(-40.0, 0.0, 10.0, 110.0, 160.0, 10.0)
else:
pass
if labels == True and grid == True:
plt.xlabel("Longitude ($^\circ$E)", labelpad=25)
plt.ylabel("Latitude ($^\circ$S)", labelpad=50)
elif labels == True and not grid == True:
plt.xlabel("Longitude ($^\circ$E)", labelpad=25)
plt.ylabel("Latitude ($^\circ$S)", labelpad=30)
else:
pass
if oceans == False:
var_time_land = maskoceans(lonall, latall, var_time)
cs = m.pcolor(x,
y,
var_time_land,
vmin=Dict['vmin'],
vmax=Dict['vmax'],
cmap=plt.cm.get_cmap('RdBu'))
else:
cs = m.pcolor(x, y, var_time, vmin=Dict['vmin'], vmax=Dict['vmax'])
if cbar == True:
cbar = m.colorbar(cs, location='right', pad="1%")
cbarLabel = "%s" % (Dict['var_units'])
cbar.set_label(cbarLabel)
else:
pass
return plt
A function to replace empty longitudinal values in the resampled
AWAP dataset with actual longitudinal values.
"""
start_lon = 112.925 # Check value. Should be 112.5?
newlist_lon = []
for i in range(0, 813):
i = start_lon
newlist_lon.append(i)
start_lon += 0.05
data.variables["longitude"][:] = newlist_lon[:]
return data.variables["longitude"][:]
dict1 = {}
dict1["var_units"] = "Precipitation (mm/day)"
dict1["lat"] = lat()
dict1["lon"] = lon()
dict1["vmin"] = 0.0 # mm/day
dict1["vmax"] = 3.0 # mm/day
[lonall, latall] = np.meshgrid((dict1["lon"]), (dict1["lat"]))
x, y = m(lonall, latall)
# Plots an image of mean precipitation for 1900 (Jan-Dec).
cs = m.pcolor(x, y, awap_data[0, :, :], vmin=dict1["vmin"], vmax=dict1["vmax"])
cbar = m.colorbar(cs, location="right", pad="1%")
cbarLabel = "%s" % (dict1["var_units"])
cbar.set_label(cbarLabel)
plt.show()
"""
A function to replace empty longitudinal values in the resampled
AWAP dataset with actual longitudinal values.
"""
start_lon = 112.925 #Check value. Should be 112.5?
newlist_lon = []
for i in range(0,813):
i = start_lon
newlist_lon.append(i)
start_lon += 0.05
data.variables['longitude'][:] = newlist_lon[:]
return data.variables['longitude'][:]
dict1 = {}
dict1['var_units'] = "Precipitation (mm/day)"
dict1['lat'] = lat()
dict1['lon'] = lon()
dict1['vmin'] = 0.0 # mm/day
dict1['vmax'] = 3.0 # mm/day
[lonall,latall] = np.meshgrid((dict1['lon']),(dict1['lat']))
x,y = m(lonall,latall)
#Plots an image of mean precipitation for 1900 (Jan-Dec).
cs = m.pcolor(x,y,awap_data[0,:,:],vmin=dict1['vmin'],vmax=dict1['vmax'])
cbar = m.colorbar(cs, location='right', pad="1%")
cbarLabel = "%s" %(dict1['var_units'])
cbar.set_label(cbarLabel)
plt.show()
def plot(var_time,Dict,labels=False,grid=False,oceans=False,cbar=True):
"""
A function to plot and display a basic plot of ACCESS,
AWAP, or HadISST datasets.
Parameters:
-----------
var_time : The variable to be plotted. Use the imported
data from access_prepare_ts, hadisst_prepare,
awap_prepare, access_prepare_pr or access_trimmed.
Dict : a dictionary defining various
variables needed for the dataset to be plotted.
The dictionaries are defined above in the
mapAWAP(), mapACCESSpr(), mapACCESSts(), mapACCESSpr_tr() and
mapHadisst() functions.
labels : (default = False)
Adds axis labels for longitude/latitude if "True".
grid : (default = False)
If set to "True", the a grid is superimposed over
the map at the 1.25 (lat) by 1.875 (lon) degree
resolution. If set to "False", only the latitudes/
longitudes that show the dimensions of the box are
plotted.
If set to "Simple", only the boundary lat/lon
values for the map are shown (no grid-lines).
oceans : (default = False)
If set to "True", ocean regions remain unmaskeded
and are plotted; if set to "False", the oceans are
not plotted.
cbar : (default = True)
Plots a colour-bar if set to "True".
"""
m
[lonall,latall] = np.meshgrid((Dict['lon']),(Dict['lat']))
x,y = m(lonall,latall)
if grid == True:
gridWhole(-47.5,-7.5,1.25,112.5,157.5,1.875)
gridLabels(-47.5,-7.5,2.5,112.5,159.375,7.5)
elif grid == 'Simple':
gridLabels(-40.0,0.0,10.0,110.0,160.0,10.0)
elif grid == 'Ticks':
gridLabels(-40.0,0.0,10.0,110.0,160.0,10.0)
else:
pass
if labels == True and grid==True:
plt.xlabel("Longitude ($^\circ$E)",labelpad=25)
plt.ylabel("Latitude ($^\circ$S)",labelpad=50)
elif labels == True and not grid==True:
plt.xlabel("Longitude ($^\circ$E)",labelpad=25)
plt.ylabel("Latitude ($^\circ$S)",labelpad=30)
else:
pass
if oceans == False:
var_time_land = maskoceans(lonall,latall,var_time)
cs = m.pcolor(x,y,var_time_land,vmin=Dict['vmin'],vmax=Dict['vmax'],cmap=plt.cm.get_cmap('RdBu'))
else:
cs = m.pcolor(x,y,var_time,vmin=Dict['vmin'],vmax=Dict['vmax'])
if cbar == True:
cbar = m.colorbar(cs, location='right', pad="1%")
cbarLabel = "%s" %(Dict['var_units'])
cbar.set_label(cbarLabel)
else:
pass
return plt