def plot_precip():
print(" PRECIP")
# Set Figure Size (1000 x 800)
plt.figure(figsize=(width,height),frameon=False)
rainc = nc.variables['RAINC']
rainnc = nc.variables['RAINNC']
# First, find out if this is first time or not
# Based on skip. This should be total from each output time
if time == 0:
prev_total = rainc[time] + rainnc[time]
else:
prev_total = rainc[time-1] + rainnc[time-1]
total_accum = rainc[time] + rainnc[time]
precip_tend = total_accum - prev_total
# Convert from mm to in
precip_tend = precip_tend * .0393700787
units = 'in'
PCP_LEVELS = [0.01,0.03,0.05,0.10,0.15,0.20,0.25,0.30,0.40,0.50,0.60,0.70,0.80,0.90,1.00,1.25,1.50,1.75,2.00,2.50]
PRECIP=plt.contourf(x,y,precip_tend,PCP_LEVELS,cmap=coltbls.precip1())
#plt.jet()
title = '%s Hour Precip' % skip
prodid = 'precip'
drawmap(PRECIP, title, prodid, units)
def plot_precip():
print(" PRECIP")
# Set Figure Size (1000 x 800)
pylab.figure(figsize=(width,height),frameon=False)
rainc = nc.variables['RAINC']
rainnc = nc.variables['RAINNC']
# First, find out if this is first time or not
if time == 0:
prev_total = rainc[time] + rainnc[time]
else:
prev_total = rainc[time-1] + rainnc[time-1]
total_accum = rainc[time] + rainnc[time]
precip_tend = total_accum - prev_total
# Convert from mm to in
precip_tend = precip_tend * .0393700787
units = 'in'
PCP_LEVELS = [0.01,0.03,0.05,0.10,0.15,0.20,0.25,0.30,0.40,0.50,0.60,0.70,0.80,0.90,1.00,1.25,1.50,1.75,2.00,2.50]
PRECIP=pylab.contourf(x,y,precip_tend,PCP_LEVELS,cmap=coltbls.precip1())
#pylab.jet()
title = '%s Hour Precip' % skip
prodid = 'precip'
drawmap(PRECIP, title, prodid, units)
def plot_pwat():
print(" PRECIP. WATER")
# Set Figure Size (1000 x 800)
plt.figure(figsize=(width, height), frameon=False)
g = 9.81
P = nc.variables['P']
PB = nc.variables['PB']
Qv = nc.variables['QVAPOR']
# First we need an array of pressures
Pr = P[time] + PB[time]
print "SHAPE Pr: ", np.shape(Pr)
Qvap = Qv[time, :, :, :]
print "SHAPE Qvap: ", np.shape(Qvap)
# Now go through each point
for j in range(len(Pr[0])):
currow_pwat = []
for i in range(len(Pr[0, 0])):
curcol_pwat = []
for k in range(len(Pr) - 1):
curdp = (Pr[k, j, i] - Pr[k + 1, j, i]) * 0.01
curpwat = curdp * Qvap[k, j, i]
curcol_pwat.append(curpwat)
np_curcol_pwat = np.array(curcol_pwat)
point_pwat = np.sum(curcol_pwat)
currow_pwat.append(point_pwat)
np_currow_pwat = np.array(currow_pwat)
if j == 0:
total_pwat = np_currow_pwat
else:
total_pwat = np.row_stack((np_currow_pwat, total_pwat))
pwat = np.divide(total_pwat, g)
print "Len j: ", len(Pr)
print "Len i: ", len(Pr[0])
print "SHAPE: ", np.shape(pwat)
print "MAX: ", np.max(pwat)
PCP_LEVELS = [
0.01, 0.03, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.40, 0.50, 0.60, 0.70,
0.80, 0.90, 1.00, 1.25, 1.50, 1.75, 2.00, 2.50
]
PWAT_LEVS = [
0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5,
1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.1, 2.3, 2.4, 2.5
]
PWAT = plt.contourf(x, y, pwat, PCP_LEVELS, cmap=coltbls.precip1())
units = 'mm'
title = 'Precipitable Water (in)'
prodid = 'pwat'
drawmap(PWAT, title, prodid, units)
def plot_pwat():
print(" PRECIP. WATER")
# Set Figure Size (1000 x 800)
plt.figure(figsize=(width,height),frameon=False)
g = 9.81
P = nc.variables['P']
PB = nc.variables['PB']
Qv = nc.variables['QVAPOR']
# First we need an array of pressures
Pr = P[time] + PB[time]
print "SHAPE Pr: ", np.shape(Pr)
Qvap = Qv[time,:,:,:]
print "SHAPE Qvap: ", np.shape(Qvap)
# Now go through each point
for j in range(len(Pr[0])):
currow_pwat = []
for i in range(len(Pr[0,0])):
curcol_pwat = []
for k in range(len(Pr)-1):
curdp = (Pr[k,j,i] - Pr[k+1,j,i]) * 0.01
curpwat = curdp * Qvap[k,j,i]
curcol_pwat.append(curpwat)
np_curcol_pwat = np.array(curcol_pwat)
point_pwat = np.sum(curcol_pwat)
currow_pwat.append(point_pwat)
np_currow_pwat = np.array(currow_pwat)
if j == 0:
total_pwat = np_currow_pwat
else:
total_pwat = np.row_stack((np_currow_pwat, total_pwat))
pwat = np.divide(total_pwat,g)
print "Len j: ", len(Pr)
print "Len i: ", len(Pr[0])
print "SHAPE: ", np.shape(pwat)
print "MAX: ", np.max(pwat)
PCP_LEVELS = [0.01,0.03,0.05,0.10,0.15,0.20,0.25,0.30,0.40,0.50,0.60,0.70,0.80,0.90,1.00,1.25,1.50,1.75,2.00,2.50]
PWAT_LEVS = [0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0,1.1,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,2.0,2.1,2.1,2.3,2.4,2.5]
PWAT=plt.contourf(x,y,pwat,PCP_LEVELS,cmap=coltbls.precip1())
units = 'mm'
title = 'Precipitable Water (in)'
prodid = 'pwat'
drawmap(PWAT, title, prodid, units)
def plot_precip(self,imagename='precip.png', title='',timestep=0):
"""plot accumulated precipitation
Optional input:
--------
imagename = 'your file name.png', defaults to vapor.png'
title = 'your title' defaults to none
timestep = integer. If there are multiple time periods per file then
choose your timestep, defaults to 0'
Returns:
--------
contour plot of accumulated precipitaiton
"""
pl.figure(6)
pl.clf()
try:
rainnc_full=self.variable_dict['RAINNC']
except ValueError:
print 'you do not have any non-convective rain data'
rainnc_full = None
except KeyError:
rainnc_full=self.get_var('RAINNC')
try:
rainc_full=self.variable_dict['RAINC']
except KeyError:
rainc_full=self.get_var('RAINC')
except ValueError:
print 'you do not have any convective rain data'
rainc_full = None
times=self.get_var('Times')
if (timestep == 0):
start_time =0
end_time = len(times)
else:
start_time=timestep
end_time=timestep+1
try:
m=self.map_proj
x=self.map_x
y=self.map_y
except:
self.bmap()
m=self.map_proj
x=self.map_x
y=self.map_y
for the_time in range(start_time,end_time):
time=times[the_time]
pl.clf()
if (rainnc_full == None) & (rainc_full == None):
print 'you have no precipitation data at all, quitting'
return None
if (rainnc_full == None) & (rainc_full != None):
rain_total = rainc_full[the_time,:,:]
if (rainc_full == None) & (rainnc_full != None):
rain_total = rainnc_full[the_time,:,:]
if (rainc_full != None) & (rainnc_full != None):
rain_total=rainnc_full[the_time,:,:] + rainc_full[the_time,:,:]
custom_map=pl.get_cmap('jet',lut=22)
PCP_LEVELS = [0.01,0.03,0.05,0.10,0.15,0.20,0.25,0.30,0.40,0.50,0.60,0.70,0.80,0.90,1.00,1.25,1.50,1.75,2.00,2.50]
max_precip = n.max(rain_total)
scaling_factor = n.ceil(max_precip/PCP_LEVELS[-1])
if scaling_factor > 0.0:
for cont in range(len(PCP_LEVELS)):
PCP_LEVELS[cont]=PCP_LEVELS[cont]*scaling_factor
m.contourf(x,y,rain_total[:,:],PCP_LEVELS,cmap = coltbls.precip1())
self.map_lines()
pl.colorbar(orientation='horizontal')
pl.title(title)
pl.savefig(self.plot_directory+'/'+imagename)
