def main():
## get metadata file file (ghcnd-stations.txt)
click.secho('>>> Get metadata file (ghcnd-stations.txt)', fg='green')
gp.get_ghcnd_stations()
## get inventory file (ghcnd-inventory.txt)
click.secho('>>> Get inventory file (ghcnd-inventory.txt)', fg='green')
gp.get_ghcnd_inventory()
## find stations
click.secho('>>> Find stations... Example: "NEW ORLEANS"', fg='green')
gp.find_station("NEW ORLEANS")
## download
click.secho(
'>>> Download data in csv format after finding the target station ID... Example: "NEW ORLEANS LAKEFRONT AP" ',
fg='green')
gp.output_to_csv("USW00053917")
## read data
click.secho('>>> Read data... Example: "NEW ORLEANS LAKEFRONT AP"',
fg='green')
data = pd.read_csv('USW00053917.csv')
print(data.head())
print(data.tail())
# return
return None
def plot_spatial_freeze(year,element,lower_lon=-125,upper_lon=-65,lower_lat=25,upper_lat=50,dpi=200,proj='merc'):
print("\nPLOT SPATIAL FREEZE")
print("year: ",year)
print("element: ",element)
days_in_year=(datetime(year, 12, 31)-datetime(year, 1, 1)).days+1
divisor=10.
if element != "LAST" and element != "FIRST":
print("Only Derived Elements Available: LAST/FIRST")
return None
if element == "LAST":
# Initialize Colormap Values
cbar_hex = ['#072F6B', '#08529C', '#2171B5', '#176fc1', '#0b8ed8', '#04a1e6', '#19b5f1', '#33bccf', '#66ccce',
'#99dbb8', '#c0e588', '#cce64b' ]
cbar_vals = np.array([1,69,79,89,99,109,119,129,139,149,159,169], dtype='f')
if element == "FIRST":
# Initialize Colormap Values
cbar_hex = ['#993399', '#CC0099', '#FF33CC', '#333399', '#3366FF', '#33CCFF', '#006600', '#339933', '#00CC00',
'#CC9900', '#FF9900', '#FFCC00' ]
cbar_vals = np.array([222,232,242,252,262,272,282,292,302,312,322,332], dtype='f')
# Set Up Colormap based element-based values
cmap=mcolors.ListedColormap(cbar_hex, N=len(cbar_vals))
norm = mcolors.BoundaryNorm(cbar_vals, cmap.N)
minimum = min(cbar_vals); maximum = max(cbar_vals) # set range.
cmap.set_under("#ffffff")
cmap.set_over("#ffffff")
extend="both"
#################################################
# Read in GHCND-D Inventory File to get
# stations that have element requested
print("GETTING STATIONS")
ghcnd_stations=gp.get_ghcnd_inventory()
num_stns=ghcnd_stations.shape[0]
ghcnd_valid_id = np.empty(num_stns,dtype='S11')
ghcnd_freeze_day = np.zeros((num_stns),dtype='f')
ghcnd_values = np.zeros((num_stns),dtype='f')-(9999.0)
ghcnd_lats = np.zeros((num_stns),dtype='f')-(9999.0)
ghcnd_lons = np.zeros((num_stns),dtype='f')-(9999.0)
#################################################
# Read in GHCN-D data
print("READING IN DATA")
gp.get_data_year(str(year))
infile = str(year)+".csv.gz"
file_handle = gzip.open(infile, 'rb')
ghcnd_contents = file_handle.readlines()
file_handle.close()
print("SORTING")
ghcnd_contents=np.sort(ghcnd_contents)
print("GOING THROUGH DATA")
# Go through GHCN-D Data
station_counter=-1
old_id = "XXXXXXXXXXX"
num_valid=0
for counter in xrange(len(ghcnd_contents)):
ghcnd_line = ghcnd_contents[counter].split(',')
if ghcnd_line[2] == "TMIN":
if old_id != ghcnd_line[0]:
station_counter = station_counter+1
num_valid=num_valid+1
ghcnd_valid_id[station_counter] = ghcnd_line[0]
day_in_year=datetime(int(ghcnd_line[1][0:4]),int(ghcnd_line[1][4:6]),int(ghcnd_line[1][6:8])).timetuple().tm_yday
if ghcnd_line[3] != "-9999" and ghcnd_line[5].strip()=='':
tmin_value = (float(ghcnd_line[3])/divisor)
if element == "LAST":
if tmin_value <=0 and day_in_year <= 169:
ghcnd_freeze_day[station_counter]=day_in_year
if element == "FIRST":
if tmin_value <=0 and day_in_year >= 222 and ghcnd_freeze_day[station_counter] == 0:
ghcnd_freeze_day[station_counter]=day_in_year
old_id=ghcnd_line[0]
ghcnd_derived_lats = np.zeros((num_valid),dtype='f')-(9999.0)
ghcnd_derived_lons = np.zeros((num_valid),dtype='f')-(9999.0)
ghcnd_derived_values = np.zeros((num_valid),dtype='f')-(9999.0)
for station_counter in xrange(0,num_valid):
ghcnd_meta = ghcnd_stations[ghcnd_stations[:,0] == ghcnd_valid_id[station_counter]]
ghcnd_derived_lats[station_counter]=float(ghcnd_meta[0][1])
ghcnd_derived_lons[station_counter]=float(ghcnd_meta[0][2])
ghcnd_derived_values[station_counter]=ghcnd_freeze_day[station_counter]
# Sort from lowest to highest (so higher values are plotted over lower values)
sorted=np.ma.argsort(ghcnd_derived_values)
ghcnd_derived_values=ghcnd_derived_values[sorted]
ghcnd_derived_lats=ghcnd_derived_lats[sorted]
ghcnd_derived_lons=ghcnd_derived_lons[sorted]
#################
# PLOT
print("PLOTTING (POINT DATA)")
plt.figure(num=1, figsize=(10, 6), dpi=dpi, facecolor='w', edgecolor='k')
# Create Mercator Basemaps
map_points = Basemap(projection=proj,llcrnrlon=lower_lon,llcrnrlat=lower_lat,
urcrnrlon=upper_lon,urcrnrlat=upper_lat, resolution='h')
# draw coastlines, country boundaries, fill continents.
map_points.drawcoastlines(linewidth=0.25)
map_points.drawcountries(linewidth=0.25)
map_points.drawstates(linewidth=0.25)
# Plot Data
x, y = map_points(ghcnd_derived_lons,ghcnd_derived_lats)
map_points.scatter(x,y,c=ghcnd_derived_values,s=10,cmap=cmap,vmin=minimum,vmax=maximum,linewidths=.1)
# Adds the colormap legend
cmleg = np.zeros((1,len(cbar_vals)),dtype='f')
for i in xrange(0,(len(cbar_vals))):
cmleg[0,i] = float(cbar_vals[i])
# Add Colorbar
cmap_legend=plt.imshow(cmleg, cmap=cmap, norm=norm)
cbar = map_points.colorbar(location='bottom',pad="5%",ticks=cbar_vals,extend=extend)
cbar.ax.tick_params(labelsize=10)
cbar.set_label('Day of Year')
# Set Labels Based on Element
if element == "LAST":
cbar.ax.set_xticklabels(['Jan-1', 'Mar-10', 'Mar-20', 'Mar-30', 'Apr-10', 'Apr-20', 'Apr-30', 'May-10', 'May-20', 'May-30', 'Jun-10', 'Jun-20'], rotation=30)
# add title
plt.title('Last Freeze date for '+str(year))
# Save to file
plt.savefig('POINT_LAST-FRZ_'+str(year)+'.png', format='png', dpi=dpi)
if element == "FIRST":
cbar.ax.set_xticklabels(['Aug-10', 'Aug-20', 'Aug-31', 'Sep-10', 'Sep-20', 'Sep-30', 'Oct-10', 'Oct-20', 'Oct-31', 'Nov-10', 'Nov-20', 'Nov-30'], rotation=30)
# add title
plt.title('First Freeze date for '+str(year))
# Save to file
plt.savefig('POINT_FIRST-FRZ_'+str(year)+'.png', format='png', dpi=dpi)
plt.clf()
return None
def plot_spatial_derived(year,element,lower_lon=-125,upper_lon=-65,lower_lat=25,upper_lat=50,dpi=200,proj='merc'):
print("\nPLOT SPATIAL DERIVED")
print("year: ",year)
print("element: ",element)
days_in_year=(datetime(year, 12, 31)-datetime(year, 1, 1)).days+1
if element != "GDD" and element != "HDD" and element != "CDD":
print("Only Derived Elements Available: GDD/HDD/CDD")
return None
# Set info based on Element
if element == "GDD" or element == "HDD" or element == "CDD":
divisor=10.
if element == "HDD":
# Initialize Colormap Values (Reds to Blues)
cbar_hex = ['#A60F14', '#a4262c', '#db1e26', '#f1471c', '#f57215', '#f89d0e', '#fcc707', '#fede27', '#f3f01d',
'#cce64b', '#c0e588', '#99dbb8', '#66ccce', '#33bccf', '#19b5f1', '#04a1e6', '#0b8ed8', '#176fc1',
'#2171B5', '#08529C', '#072F6B' ]
if element == "CDD" or element == "GDD":
# Initialize Colormap Values (Blues to Reds)
cbar_hex = ['#072F6B', '#08529C', '#2171B5', '#176fc1', '#0b8ed8', '#04a1e6', '#19b5f1', '#33bccf', '#66ccce',
'#99dbb8', '#c0e588', '#cce64b', '#f3f01d', '#fede27', '#fcc707', '#f89d0e', '#f57215', '#f1471c',
'#db1e26', '#a4262c', '#A60F14' ]
cbar_vals = np.array([0,100,200,300,400,500,600,700,800,900,1000,1100,1200,1300,1400,1500,1600,1700,1800,1900,2000], dtype='f')
# Set Up Colormap based element-based values
cmap=mcolors.ListedColormap(cbar_hex, N=len(cbar_vals))
norm = mcolors.BoundaryNorm(cbar_vals, cmap.N)
minimum = min(cbar_vals); maximum = max(cbar_vals) # set range.
cmap.set_under("#ffffff")
cmap.set_over("#5F0000")
extend="max"
#################################################
# Read in GHCND-D Inventory File to get
# stations that have element requested
print("GETTING STATIONS")
ghcnd_stations=gp.get_ghcnd_inventory()
num_stns=ghcnd_stations.shape[0]
ghcnd_valid_id = np.empty(num_stns,dtype='S11')
ghcnd_tmax = np.zeros((num_stns,days_in_year),dtype='f')-(9999.0)
ghcnd_tmin = np.zeros((num_stns,days_in_year),dtype='f')-(9999.0)
ghcnd_lats = np.zeros((num_stns,days_in_year),dtype='f')-(9999.0)
ghcnd_lons = np.zeros((num_stns,days_in_year),dtype='f')-(9999.0)
#################################################
# Read in GHCN-D data
print("READING IN DATA")
gp.get_data_year(str(year))
infile = str(year)+".csv.gz"
file_handle = gzip.open(infile, 'rb')
ghcnd_contents = file_handle.readlines()
file_handle.close()
print("SORTING")
ghcnd_contents=np.sort(ghcnd_contents)
print("GOING THROUGH DATA")
# Go through GHCN-D Data
station_counter=-1
old_id = "XXXXXXXXXXX"
num_valid=0
for counter in xrange(len(ghcnd_contents)):
ghcnd_line = ghcnd_contents[counter].split(',')
if ghcnd_line[2] == "TMAX" or ghcnd_line[2] == "TMIN":
if old_id != ghcnd_line[0]:
station_counter = station_counter+1
num_valid=num_valid+1
ghcnd_valid_id[station_counter] = ghcnd_line[0]
#print(station_counter,ghcnd_valid_id[station_counter])
day_in_year=datetime(int(ghcnd_line[1][0:4]),int(ghcnd_line[1][4:6]),int(ghcnd_line[1][6:8])).timetuple().tm_yday-1
# Get TMAX/TMIN and its associated lats/lons
if ghcnd_line[2] == "TMAX" and ghcnd_line[3] != "-9999" and ghcnd_line[5].strip()=='':
ghcnd_tmax[station_counter,day_in_year] = (float(ghcnd_line[3])/divisor)
if ghcnd_line[2] == "TMIN" and ghcnd_line[3] != "-9999" and ghcnd_line[5].strip()=='':
ghcnd_tmin[station_counter,day_in_year] = (float(ghcnd_line[3])/divisor)
old_id=ghcnd_line[0]
print("CREATING ACCUMULATIONS")
ghcnd_derived_lats = np.zeros((num_valid),dtype='f')-(9999.0)
ghcnd_derived_lons = np.zeros((num_valid),dtype='f')-(9999.0)
ghcnd_derived_values = np.zeros((num_valid),dtype='f')-(9999.0)
for station_counter in xrange(0,num_valid):
ghcnd_meta = ghcnd_stations[ghcnd_stations[:,0] == ghcnd_valid_id[station_counter]]
ghcnd_derived_lats[station_counter]=float(ghcnd_meta[0][1])
ghcnd_derived_lons[station_counter]=float(ghcnd_meta[0][2])
ghcnd_value = np.zeros((days_in_year),dtype='f')-(9999.0)
non_missing=np.where(np.logical_and(ghcnd_tmax[station_counter] != -9999, ghcnd_tmin[station_counter] != -9999))
ghcnd_value[non_missing] = (ghcnd_tmax[station_counter,non_missing] + ghcnd_tmin[station_counter,non_missing]) / 2.
if element == "GDD":
base=10.000
ghcnd_value[non_missing] = ghcnd_value[non_missing] - base
if element == "HDD":
base=18.333
ghcnd_value[non_missing] = base - ghcnd_value[non_missing]
if element == "CDD":
base=18.333
ghcnd_value[non_missing] = ghcnd_value[non_missing] - base
non_zero=np.where(ghcnd_value > 0)
ghcnd_derived_values[station_counter]=np.sum(ghcnd_value[non_zero])
# Sort from lowest to highest (so higher values are plotted over lower values)
sorted=np.ma.argsort(ghcnd_derived_values)
ghcnd_derived_values=ghcnd_derived_values[sorted]
ghcnd_derived_lats=ghcnd_derived_lats[sorted]
ghcnd_derived_lons=ghcnd_derived_lons[sorted]
#################
# PLOT
print("PLOTTING (POINT DATA)")
plt.figure(num=1, figsize=(10, 6), dpi=dpi, facecolor='w', edgecolor='k')
# Create Mercator Basemaps
map_points = Basemap(projection=proj,llcrnrlon=lower_lon,llcrnrlat=lower_lat,
urcrnrlon=upper_lon,urcrnrlat=upper_lat, resolution='h')
# draw coastlines, country boundaries, fill continents.
map_points.drawcoastlines(linewidth=0.25)
map_points.drawcountries(linewidth=0.25)
map_points.drawstates(linewidth=0.25)
# Plot Data
x, y = map_points(ghcnd_derived_lons,ghcnd_derived_lats)
map_points.scatter(x,y,c=ghcnd_derived_values,s=10,cmap=cmap,vmin=minimum,vmax=maximum,linewidths=.1)
# Adds the colormap legend
cmleg = np.zeros((1,len(cbar_vals)),dtype='f')
for i in xrange(0,(len(cbar_vals))):
cmleg[0,i] = float(cbar_vals[i])
# Add Colorbar
cmap_legend=plt.imshow(cmleg, cmap=cmap, norm=norm)
cbar = map_points.colorbar(location='bottom',pad="5%",ticks=cbar_vals,extend=extend)
cbar.ax.tick_params(labelsize=10)
cbar.set_label('Degree Days ('+str(base)+' $^\circ$C)')
# add title
plt.title(element+' data for '+str(year))
# Save to file
plt.savefig('POINT_'+element+'_'+str(year)+'.png', format='png', dpi=dpi)
plt.clf()
return None
def plot_spatial(year,month,day,element,lower_lon=-125,upper_lon=-65,lower_lat=25,upper_lat=50,dpi=200,proj='merc'):
print("\nPLOT SPATIAL")
if month < 10:
month="0"+str(month)
if day < 10:
day="0"+str(day)
print("year: ",year)
print("month: ",month)
print("day: ",day)
print("element: ",element)
plot_date=str(year)+str(month)+str(day)
if element != "TMAX" and element != "TMIN" and element != "TAVG" and element != "PRCP" and element != "SNOW" and element != "SNWD":
print("Only Elements Available: TMAX/TMIN/TAVG/PRCP/SNOW/SNWD")
return None
# Set info based on Element
if element == "TMAX" or element == "TMIN" or element == "TAVG":
divisor=10.
unit='$^\circ$F'
# Initialize Colormap Values
cbar_hex = ['#072F6B', '#08529C', '#2171B5', '#176fc1', '#0b8ed8', '#04a1e6', '#19b5f1', '#33bccf', '#66ccce',
'#99dbb8', '#c0e588', '#cce64b', '#f3f01d', '#fede27', '#fcc707', '#f89d0e', '#f57215', '#f1471c',
'#db1e26', '#a4262c', '#A60F14' ]
cbar_vals = np.array([0,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100], dtype='f')
# Set Up Colormap based element-based values
cmap=mcolors.ListedColormap(cbar_hex, N=len(cbar_vals))
norm = mcolors.BoundaryNorm(cbar_vals, cmap.N)
minimum = min(cbar_vals); maximum = max(cbar_vals) # set range.
cmap.set_under("#071E46")
cmap.set_over("#5F0000")
extend="both"
if element == "PRCP":
divisor=10.
unit='inches'
# Initialize Colormap Values
cbar_hex = [ '#33ffff', '#0099ff', '#0033cc', '#33ff00', '#33cc00','#336600', '#ffff33', '#cc9900', '#ff9900',
'#ff0000','#cc0000', '#990000', '#ff00ff', '#9900ff', '#9900ff' ]
cbar_vals = np.array([0.01,0.10,0.25,0.50,0.75,1.0,1.5,2.0,2.5,3.0,4.0,5.0,6.0,8.0,10.0], dtype='f')
# Set Up Colormap based element-based values
cmap=mcolors.ListedColormap(cbar_hex, N=len(cbar_vals))
norm = mcolors.BoundaryNorm(cbar_vals, cmap.N)
minimum = min(cbar_vals); maximum = max(cbar_vals) # set range.
cmap.set_over("#ffffff")
extend="max"
if element == "SNOW" or element == "SNWD":
divisor=1.
unit='inches'
# Initialize Colormap Values
cbar_hex = [ '#EDFAC2', '#CDFFCD', '#99ff99', '#53bd9f', '#32a696', '#3296b4', '#0570b0', '#05508c', '#0a1f96',
'#6a2c5a', '#6a2c5a' ]
cbar_vals = np.array([0.01,1.,2.,3.,4.,5.,10.,15.,20.,30.,40.], dtype='f')
# Set Up Colormap based element-based values
cmap=mcolors.ListedColormap(cbar_hex, N=len(cbar_vals))
norm = mcolors.BoundaryNorm(cbar_vals, cmap.N)
minimum = min(cbar_vals); maximum = max(cbar_vals) # set range.
cmap.set_over("#2c0246")
extend="max"
#################################################
# Read in GHCND-D Inventory File to get
# stations that have element requested
print("GETTING STATIONS THAT MATCH ELEMENT: ",element)
ghcnd_inventory=gp.get_ghcnd_inventory()
ghcnd_stations = ghcnd_inventory[ghcnd_inventory[:,3] == element]
num_stns=ghcnd_stations.shape[0]
ghcnd_values = np.zeros((num_stns),dtype='f')-(9999.0)
ghcnd_lats = np.zeros((num_stns),dtype='f')-(9999.0)
ghcnd_lons = np.zeros((num_stns),dtype='f')-(9999.0)
#################################################
# Read in GHCN-D data
print("READING IN DATA")
gp.get_data_year(str(year))
infile = str(year)+".csv.gz"
file_handle = gzip.open(infile, 'rb')
ghcnd_contents = file_handle.readlines()
file_handle.close()
valid_stns=0
for counter in xrange(len(ghcnd_contents)):
ghcnd_line = ghcnd_contents[counter].split(',')
if ghcnd_line[1] == plot_date and ghcnd_line[2] == element:
# Get Data Value
ghcnd_values[valid_stns] = (float(ghcnd_line[3])/divisor)
# Get Lat/Lon
ghcnd_meta = ghcnd_stations[ghcnd_stations[:,0] == ghcnd_line[0]]
ghcnd_lats[valid_stns]=float(ghcnd_meta[0][1])
ghcnd_lons[valid_stns]=float(ghcnd_meta[0][2])
valid_stns=valid_stns+1
# Sort from lowest to highest (so higher values are plotted over lower values)
sorted=np.ma.argsort(ghcnd_values)
ghcnd_values=ghcnd_values[sorted]
ghcnd_lats=ghcnd_lats[sorted]
ghcnd_lons=ghcnd_lons[sorted]
# Convert to Imperial Units and mask data where needed
if element == "TMAX" or element == "TMIN" or element == "TAVG":
ghcnd_values = (ghcnd_values * 1.8) + 32. # C to F
else:
ghcnd_values = (ghcnd_values * 0.03937) # mm to inch
ghcnd_values = ma.masked_where(ghcnd_values < 0.01, ghcnd_values)
# Don't Plot Missing Data
valid=np.where(np.logical_and(ghcnd_lats!=-9999,ghcnd_lons!=-9999))
#################
# PLOT
print("PLOTTING (POINT DATA)")
plt.figure(num=1, figsize=(10, 6), dpi=dpi, facecolor='w', edgecolor='k')
# Create Mercator Basemaps
map_points = Basemap(projection=proj,llcrnrlon=lower_lon,llcrnrlat=lower_lat,
urcrnrlon=upper_lon,urcrnrlat=upper_lat, resolution='h')
# draw coastlines, country boundaries, fill continents.
map_points.drawcoastlines(linewidth=0.25)
map_points.drawcountries(linewidth=0.25)
map_points.drawstates(linewidth=0.25)
# Plot Data
x, y = map_points(ghcnd_lons[valid],ghcnd_lats[valid])
map_points.scatter(x,y,c=ghcnd_values[valid],s=10,cmap=cmap,vmin=minimum,vmax=maximum,linewidths=0.1)
# Adds the colormap legend
cmleg = np.zeros((1,len(cbar_vals)),dtype='f')
for i in xrange(0,(len(cbar_vals))):
cmleg[0,i] = float(cbar_vals[i])
# Add Colorbar
cmap_legend=plt.imshow(cmleg, cmap=cmap, norm=norm)
cbar = map_points.colorbar(location='bottom',pad="5%",ticks=cbar_vals,extend=extend)
cbar.ax.tick_params(labelsize=10)
cbar.set_label(unit)
# add title
plt.title(element+' data for '+str(year)+' '+str(month)+' '+str(day))
# Save to file
plt.savefig('POINT_'+str(element)+'_'+str(plot_date)+'.png', format='png', dpi=dpi)
plt.clf()
return None