print
# Grab the values from 'OBJECTID' and 'upload:OKCNTYD'
usr_attribute = 'STATE'
values = pyGDP.getValues(shapefile, usr_attribute)
for v in values:
print v
print
# our shapefile = 'upload:OKCNTYD', usr_attribute = 'OBJECTID', and usr_value = 13
# We get the dataset URI that we are interested in
dataSetURIs = pyGDP.getDataSetURI()
for d in dataSetURIs:
print d
# Set our datasetURI
dataSetURI = 'dods://igsarm-cida-thredds1.er.usgs.gov:8080/thredds/dodsC/gmo/GMO_w_meta.ncml'
# Get the available data types associated with the dataset
dataType = 'Prcp'
# Get available time range on the dataset
timeRange = pyGDP.getTimeRange(dataSetURI, dataType)
for t in timeRange:
print t
"""
Instead of submitting in a value, we submit a list of gmlIDs associated
with either a small portion of that value, or multiple values.
"""
values = ['Wisconsin', 'Michigan', 'Minnesota']
path = pyGDP.submitFeatureWeightedGridStatistics(shapefile, dataSetURI, dataType, timeRange[0], timeRange[0], usr_attribute, values)
print path
# 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,
timeEnd,
usr_attribute,
usr_value,
gmlIDs=None,
verbose=True)
geoType = [(-119.871972, 34.420668), (-119.843353, 34.421090),
(-119.844263, 34.406818), (-119.878692, 34.408690)]
baseURI = 'http://cida.usgs.gov/thredds/dodsC/loca_future'
startTime = 1950
endTime = 2100
varID = 'pr_CCSM4_r6i1p1_rcp45'
#['tasmax_CCSM4_r6i1p1_rcp45', 'tasmin_CCSM4_r6i1p1_rcp45']
years = array.array('i', (i for i in range(startTime, endTime + 1)))
fileList = []
for yr in years:
datasetURI = '%s%s%s' % (baseURI, yr, '.nc')
timeRange = pyGDP.getTimeRange(datasetURI, varID)
timeStart = timeRange[0]
timeEnd = timeRange[1]
print "process beginning for %s on year %s'" % (varID, yr)
outputFile_handle = pyGDP.submitFeatureWeightedGridStatistics(
self,
geoType,
dataSetURI,
varID,
startTime,
endTime,
'',
'',
'',
'',
coverage='true',
continue
if restart_from_files:
already_downloaded = [datatype_from_filename(f) for f in os.listdir(outpath)]
datatypes_list = [d for d in datatypes_list if d not in already_downloaded]
if len(datatypes_list) == 0:
print "URI already finished"
continue
# could add something here to print out list of datatypes after restart
# Get time periods to run for list of datatypes
print '\nDataTypes and timeRanges (excluding those already downloaded):'
timeranges=[]
for d in datatypes_list:
timeRange = pyGDP.getTimeRange(URI, d)
timeranges.append(timeRange)
print '{}\t-->\t{} - {}'.format(d, timeRange[0], timeRange[1])
# assumes that time ranges are all the same for all datatypes
# loop to get rid of stupid empties in timeranges list
for n in timeranges:
try:
timeStart = n[0]
timeEnd = n[1]
break
except IndexError:
continue
if TestRun:
# kludgy hard code to test only first timestep for wicci
if timeStart == '1961-01-01T00:00:00Z':
# '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
print shapefiles[shapefile]
datatype_from_filename(f) for f in os.listdir(outpath)
]
datatypes_list = [
d for d in datatypes_list if d not in already_downloaded
]
if len(datatypes_list) == 0:
print "URI already finished"
continue
# could add something here to print out list of datatypes after restart
# Get time periods to run for list of datatypes
print '\nDataTypes and timeRanges (excluding those already downloaded):'
timeranges = []
for d in datatypes_list:
timeRange = pyGDP.getTimeRange(URI, d)
timeranges.append(timeRange)
print '{}\t-->\t{} - {}'.format(d, timeRange[0], timeRange[1])
# assumes that time ranges are all the same for all datatypes
# loop to get rid of stupid empties in timeranges list
for n in timeranges:
try:
timeStart = n[0]
timeEnd = n[1]
break
except IndexError:
continue
if TestRun:
# kludgy hard code to test only first timestep for wicci
if timeStart == '1961-01-01T00:00:00Z':
# '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(