# Grab the file and get its attributes:
shapefile = 'sample:CSC_Boundaries'
attributes = pyGDP.getAttributes(shapefile)
for attr in attributes:
print(attr)
# Grab the values from 'area_name' and 'sample:CSC_Boundaries'
usr_attribute = 'area_name'
values = pyGDP.getValues(shapefile, usr_attribute)
for v in values:
print(v)
usr_value = 'Southwest'
dataSetURI = 'dods://cida.usgs.gov/thredds/dodsC/gmo/GMO_w_meta.ncml'
dataTypes = pyGDP.getDataType(dataSetURI)
for d in dataTypes:
print(d)
dataType = 'Prcp'
# Get available time range on the dataset
timeRange = pyGDP.getTimeRange(dataSetURI, dataType)
for t in timeRange:
print(t)
timeBegin = '1960-01-01T00:00:00.000Z'
timeEnd = '1960-01-21T00:00:00.000Z'
outputPath = pyGDP.submitFeatureWeightedGridStatistics(shapefile,
dataSetURI,
dataType,
timeBegin,
# In[19]:
usr_attribute="hru_id"
usr_values=None
#usr_values = pyGDP.getValues(shapefile, usr_attribute)
#for v in values:
# print v
# In[7]:
# Set our datasetURI
#dataSetURI = 'dods://cida.usgs.gov/thredds/dodsC/prism'
dataSetURI = 'http://thredds.daac.ornl.gov/thredds/dodsC/daymet-agg/daymet-agg.ncml'
# Get the available data types associated with the dataset
datatypes = pyGDP.getDataType(dataSetURI)
for dt in datatypes:
print dt
# In[9]:
# Set the dataType. Note that leaving dataType out below will select all.
# Get available time range on the dataset
dataType='prcp'
timeRange = pyGDP.getTimeRange(dataSetURI, dataType)
for t in timeRange:
print t
# In[14]:
else:
ofp.write('CIDA_output_handle, datatype\n')
# Loop through the datasets (Time periods)
print '\nGetting DataTypes for each URI...'
for URI in dataSetURIs:
# Get list of datatypes based on realization and parameters specified above
datatypes_list = []
# in case the server bombs out, try again
dTypes = False
while not dTypes:
try:
print '\n{}'.format(URI)
dataTypes = pyGDP.getDataType(URI)
dTypes = True
except Exception, e:
print e
print "trying again in a moment..."
time.sleep(5)
print "asking again for dataTypes..."
if len(dataTypes) == 0:
print "Error! no datasets returned."
for d in dataTypes:
for p in parameters:
if realization in d and p in d:
datatypes_list.append(d)
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/days_prcp_abv_cmip5_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/cooling_degree_day_cmip5_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/longest_run_tmax_abv_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/longest_run_prcp_blw_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/heating_degree_day_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/growing_season_lngth_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/growing_degree_day_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/days_tmin_blw_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/days_tmax_abv_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/days_prcp_abv_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/cooling_degree_day_cmip5_hist_der.ncml']
for dataURI in dataURIs:
remote_dataURI=dataURI.replace('http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/','http://cida-eros-thredds3.er.usgs.gov:8080/thredds/dodsC/cmip5_bcca/derivatives/')
print(remote_dataURI)
dataTypes = pyGDP.getDataType(remote_dataURI)
timeRange = pyGDP.getTimeRange(remote_dataURI, dataTypes[0])
if len(dataTypes)==1:
dataTypes=dataTypes[0]
for shapefile in shapefiles.keys():
outputfilename=shapefile.replace('derivative:','')+'_'+dataURI.replace('http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/','')
outputfilename=outputfilename.replace('http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/averages_rcp/ncml/','')
outputfilename=outputfilename.replace('http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/averages_hist/ncml/','')
outputfilename=outputfilename.replace('http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/averages_gmo/ncml/','')
outputfilename=outputfilename.replace('http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/cmip5_obs_der/','')
if not os.path.isfile(outputfilename):
open(outputfilename, 'a').close()
print shapefile
print dataURI
print dataTypes
print timeRange
else:
ofp.write('CIDA_output_handle, datatype\n')
# Loop through the datasets (Time periods)
print '\nGetting DataTypes for each URI...'
for URI in dataSetURIs:
# Get list of datatypes based on realization and parameters specified above
datatypes_list = []
# in case the server bombs out, try again
dTypes = False
while not dTypes:
try:
print '\n{}'.format(URI)
dataTypes = pyGDP.getDataType(URI)
dTypes = True
except Exception, e:
print e
print "trying again in a moment..."
time.sleep(5)
print "asking again for dataTypes..."
if len(dataTypes) == 0:
print "Error! no datasets returned."
for d in dataTypes:
for p in parameters:
if realization in d and p in d:
datatypes_list.append(d)
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/longest_run_prcp_blw_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/heating_degree_day_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/growing_season_lngth_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/growing_degree_day_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/days_tmin_blw_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/days_tmax_abv_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/days_prcp_abv_cmip5_hist_der.ncml',
# 'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/cooling_degree_day_cmip5_hist_der.ncml']
for dataURI in dataURIs:
remote_dataURI = dataURI.replace(
'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/',
'http://cida-eros-thredds3.er.usgs.gov:8080/thredds/dodsC/cmip5_bcca/derivatives/'
)
print(remote_dataURI)
dataTypes = pyGDP.getDataType(remote_dataURI)
timeRange = pyGDP.getTimeRange(remote_dataURI, dataTypes[0])
if len(dataTypes) == 1:
dataTypes = dataTypes[0]
for shapefile in shapefiles.keys():
outputfilename = shapefile.replace(
'derivative:', ''
) + '_' + dataURI.replace(
'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/ncml/',
'')
outputfilename = outputfilename.replace(
'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/averages_rcp/ncml/',
'')
outputfilename = outputfilename.replace(
'http://localhost:8080/thredds/dodsC/Scratch/thredds/bcca/bcca/cmip5/derivatives/averages_hist/ncml/',
'')