if V[:3] == "3d_":
var_is_3d = True
if not var_is_3d:
var = V
vname = V
else:
var = V[3:-3]
vname = V[3:]
pressure = int(V[-3:]) * 100
for n, date in enumerate(date_list):
print date
# Find the file and open it
nc_path, nc_file = findClimoFile(grep + date + "*", directory)
nc = ncgoda(nc_path)
# Read in the variable data
if var == "PRECT_d18O":
nc.PRECT_d18O(box)
elif var == "PRECT_dD":
nc.PRECT_dD(box)
elif var == "PRECT_dxs":
nc.PRECT_dxs(box)
elif var == "QFLX_d18O":
nc.QFLX_d18O(box)
elif var == "QFLX_dD":
nc.QFLX_dD(box)
elif var == "fluxDelta":
nc.fluxDelta(box)
showfig = ARGS.showfig
raw = ARGS.raw
removeMeans = True
if raw:
removeMeans = False
if ARGS.developer_mode:
print "\nRunning in dev mode. No files will be saved, no directories will be created, and all plots will be printed to the screen."
savfig = False
showfig = True
# Extract the dates
dates = camdates(start, end, months, days)
for n, date in enumerate(dates):
# Find the file for this date
cfull_path, cfname = findClimoFile(
"*" + grep_pre + "*" + date + "*" + grep_post + "*", cdir)
tfull_path, tfname = findClimoFile(
"*" + grep_pre + "*" + date + "*" + grep_post + "*", tdir)
if cfname != 0:
print cfname
if tfname != 0:
print tfname
# Open the file
cnc = camgoda(cfull_path)
tnc = camgoda(tfull_path)
is3d, var, vname = cnc.ExtractData(variable, box)
is3d, var, vname = tnc.ExtractData(variable, box)
if n == 0:
nlats, nlons = cnc.data.shape
boxlat = cnc.boxlat
boxlon = cnc.boxlon
top = lat + delta
left = lon - delta
if left < 0:
left += 360
right = lon + delta
if right > 360:
right -= 360
region = [bottom, top, left, right]
box = [int(l) for l in ARGS.box]
southern_lat, northern_lat, left_lon, right_lon = box
if left_lon > right_lon:
left_lon -= 360
for date_idx, date in enumerate(dates):
cpath, cfilename = findClimoFile(grep_pre + '*' + date + '*' + grep_post,
cdir)
tpath, tfilename = findClimoFile(grep_pre + '*' + date + '*' + grep_post,
tdir)
print cfilename
print tfilename
# Open the file
cnc = camgoda(cpath)
tnc = camgoda(tpath)
if date_idx == 0:
data = np.zeros(shape=(len(dates), 2, len(cnc.lat), len(cnc.lon), 2))
data[date_idx, 0, ...] = cnc.ExtractData(lv + "," + fv, returnData=True)
data[date_idx, 1, ...] = tnc.ExtractData(lv + "," + fv, returnData=True)
# Box out the lv
lv_ts = np.nanmean(boxOut(data[..., 0], region), axis=(-2, -1))
# Four proxy region in the warm pool
if (region == "4P") | (region == "FourProxies"):
region_name = "FourProxies"
southern_lat = -25
northern_lat = 30
left_lon = 85
right_lon = 160
box = (southern_lat, northern_lat, left_lon, right_lon)
tloc_var_master = []
cloc_var_master = []
for n, d in enumerate(dates):
# Find the file
cpath, cfilename = findClimoFile('*' + grep + "*" + d + '*', directory = cdir)
tpath, tfilename = findClimoFile('*' + grep + "*" + d + '*', directory = tdir)
print tfilename
print cfilename
# Open the file
cnc = camgoda(cpath)
tnc = camgoda(tpath)
if n == 0:
cnc.ExtractData(v1, box) # This sets boxlat and boxlon
lats = cnc.boxlat
lons = cnc.boxlon
hold = np.zeros(shape = (len(lats), len(lons), len(dates), 2, 2)) # lat, lon, dates, var, state
hold[:,:,n,0,0] = cnc.ExtractData(v1, box, returnData = True)
# Is the variable 2 or 3 dimensions
var_is_3d = False
if V[:3] == "3d_":
var_is_3d = True
if not var_is_3d:
var = V
vname = V
else:
var = V[3:-3]
vname = V[3:]
pressure = int(V[-3:]) * 100
for n, date in enumerate(date_list):
print date
c_nc_path, c_nc_file = findClimoFile(grep + date + "*",
control_directory)
t_nc_path, t_nc_file = findClimoFile(grep + date + "*", test_directory)
#print c_nc_path
#print t_nc_path
c_nc = camgoda(c_nc_path)
t_nc = camgoda(t_nc_path)
# Extract the variable data
# Special variables
if var == "PRECT_d18O":
t_nc.PRECT_d18O(box)
c_nc.PRECT_d18O(box)
elif var == "PRECT_dD":
t_nc.PRECT_dD(box)
c_nc.PRECT_dD(box)
print "Created directory " + "DiffPopMap"
# Create the region directory if it doesn't already exist
if not os.path.exists("DiffPopMap/" + region_name):
os.mkdir("DiffPopMap/" + region_name)
print "Created directory " + "DiffPopMap/" + region_name
# Create grep directory inside region directory
if not os.path.exists("DiffPopMap/" + region_name + "/" + grep):
os.mkdir("DiffPopMap/" + region_name + "/" + grep)
print "Created directory " + "DiffPopMap/" + region_name + "/" + grep
if findFile:
# Look for the climo files in the root directory
print "\nLooking for control " + grep + " files in " + controldir
controldatafname, controlfn = findClimoFile("*" + grep + "*", controldir)
if not controldatafname:
sys.exit()
print "Found control file: " + controlfn
print "\nLooking for test " + grep + " files in " + testdir
testdatafname, testfn = findClimoFile("*" + grep + "*", testdir)
if not testdatafname:
sys.exit()
print "Found test file: " + testfn
else:
print "\nControl file is " + controldatafname
print "\nTest file is " + testdatafname
controlfn = os.path.splitext(os.path.split(controldatafname)[1])[0]
testfn = os.path.splitext(os.path.split(testdatafname)[1])[0]
# Read the data
box = [bottom_lat, top_lat, left_lon, right_lon]
variables = [str(V) for V in ARGS.variable]
savefig = ARGS.savefig
showfig = ARGS.showfig
mkdir = True
if ARGS.developer_mode:
print "\nRunning in dev mode. No files will be saved, no directories will be created, and all plots will be printed to the screen."
savefig = False
showfig = True
mkdir = False
# Find the file
if (cfile is None) or (tfile is None):
print "\nLooking for control " + grep + " files in " + cdir + "..."
cfile, controlfn = findClimoFile("*" + grep + "*", cdir)
if not controldatafname:
sys.exit()
else:
print "Found file " + controlfn
print "\nLooking for test " + grep + " files in " + tdir + "..."
tfile, testfn = findClimoFile("*" + grep + "*", tdir)
if not testdatafname:
sys.exit()
else:
print "Found file " + testfn
else:
controlfn = os.path.splitext(os.path.split(cfile)[1])[0]
testfn = os.path.splitext(os.path.split(tfile)[1])[0]
print "\nControl file is " + controlfn
print "\nRunning in dev mode. No files will be saved, no directories will be created, and all plots will be printed to the screen."
savfig = False
showfig = True
mkdir = False
##################
# Main algorithm #
##################
# Creates the master array of the correct shape
var_master = np.zeros(shape=(len(dates), len(variables)))
long_name = []
units = []
for n, d in enumerate(dates):
# Find the file for this date
full_path, fname = findClimoFile("*" + grep + "*" + d + "*",
directory=ARGS.directory)
if fname != 0:
print fname
# Open the file
nc = camgoda(full_path)
for m, v in enumerate(variables):
# Read the data
var_is_3d, var, pressure = nc.ExtractData(v, box)
data = nc.data
# Average the data
data_avg = np.nanmean(data)
var_master[n, m] = data_avg
if n == 0:
long_name.append(nc.long_name)
units.append(nc.units)
savfig = False
showfig = True
mkdir = False
##################
# Main algorithm #
##################
# Creates the master array of the correct shape
cvar_master = np.zeros(shape = (len(dates), len(variables)))
tvar_master = np.zeros(shape = (len(dates), len(variables)))
long_name = []
units = []
for n, d in enumerate(dates):
# Find the file for this date
cfull_path, cfname = findClimoFile("*"+grep+"*"+d+"*", directory = cdir)
tfull_path, tfname = findClimoFile("*"+grep+"*"+d+"*", directory = tdir)
if cfname != 0:
print cfname
if tfname != 0:
print tfname
# Open the file
cnc = camgoda(cfull_path)
tnc = camgoda(tfull_path)
for m, v in enumerate(variables):
# Read the data
var_is_3d, var, pressure = cnc.ExtractData(v, box)
var_is_3d, var, pressure = tnc.ExtractData(v, box)
cdata = cnc.data
tdata = tnc.data
# Average the data
left += 360
right = lon + delta
if right > 360:
right -= 360
region = [bottom, top, left, right]
box = [int(l) for l in ARGS.box]
# These are mapping variable
southern_lat, northern_lat, left_lon, right_lon = box
if left_lon > right_lon:
left_lon -= 360
for date_idx, date in enumerate(dates):
# Find the file
path, filename = findClimoFile(grep_pre + '*' + date + '*' + grep_post,
directory)
print filename
# Open the file
nc = camgoda(path)
if date_idx == 0:
data = np.zeros(shape=(len(dates), len(nc.lat), len(nc.lon), 2))
data[date_idx, ...] = nc.ExtractData(lv + "," + fv, returnData=True)
#
# Extract the lv timeseries
lv_ts = np.nanmean(boxOut(data[..., 0], region), axis=(-2, -1))
# Box out the fv
fv_boxed_ts, lats, lons = boxOut(data[..., 1], box, returnGrid=True)
corr_array = corr_2d(np.expand_dims(np.expand_dims(lv_ts, -1), -1),
fv_boxed_ts,
showfig = ARGS.showfig
if ARGS.developer_mode:
print "\nRunning in dev mode. No files will be saved, no directories will be created, and all plots will be printed to the screen."
savfig = False
showfig = True
raw = ARGS.raw
removeMeans = True
if raw:
removeMeans = False
# Extract the dates
dates = camdates(start, end, months)
for n, date in enumerate(dates):
# Find the file for this date
full_path, fname = findClimoFile("*"+grep_pre+"*"+date+"*"+grep_post+"*", directory)
if fname != 0:
print fname
# Open the file
nc = camgoda(full_path)
is3d, var, vname = nc.ExtractData(variable, box)
if n == 0:
nlats, nlons = nc.data.shape
boxlat = nc.boxlat
boxlon = nc.boxlon
d = np.zeros(shape = (len(dates), nlats*nlons))
d[n,:] = np.ndarray.flatten(nc.data)
# Compute the amplitude timeseries and EOF spatial distributions of the data array
print "Computing the EOF..."
EOF = Eof(d, center = removeMeans)
