def submitCustomBioclim(processid="org.n52.wps.server.r.gridded_bioclim",
outputfname=None,
verbose=False,
**kwargs):
'''Makes a call to the WPS algorithm wrapping an R script which generates
custom Bioclim variables. The processid is the locator of our R script.
defaults to: org.n52.wps.server.r.gridded_bioclim
outputfname is the path to save the returned zip to
the remaining argumnets are:
OPeNDAP_URI: A locator of a valid OPenDAP dataset
defaults to: https://cida.usgs.gov/thredds/dodsC/prism
tmax_var: the name of the max temp variable
defaults to
tmin_var: the name of the min temp variable
prcp_var: the name of the prcp vaiable,
tave_var: the name of the tave_var
defaults to "Null"
bioclims: A list of integers (1-19) of the bioclim vars to return
start: The year to begin with
end: The year to end with
bbox_in: The bounding box to use
four item tuple (max long, min lat, min long, max lat)
'''
_validate_bioclim_inputs(outputfname, verbose=verbose, **kwargs)
inputs = _parse_bioclim_inputs(**kwargs)
output = _execute_request._executeRequest(processid, inputs, "name",
verbose, outputfname)
return output
def submitCustomBioclim(processid="org.n52.wps.server.r.gridded_bioclim",
outputfname=None, verbose=False, **kwargs):
'''Makes a call to the WPS algorithm wrapping an R script which generates
custom Bioclim variables. The processid is the locator of our R script.
defaults to: org.n52.wps.server.r.gridded_bioclim
outputfname is the path to save the returned zip to
the remaining argumnets are:
OPeNDAP_URI: A locator of a valid OPenDAP dataset
defaults to: http://cida.usgs.gov/thredds/dodsC/prism
tmax_var: the name of the max temp variable
defaults to
tmin_var: the name of the min temp variable
prcp_var: the name of the prcp vaiable,
tave_var: the name of the tave_var
defaults to "Null"
bioclims: A list of integers (1-19) of the bioclim vars to return
start: The year to begin with
end: The year to end with
bbox_in: The bounding box to use
four item tuple (max long, min lat, min long, max lat)
'''
_validate_bioclim_inputs(outputfname, verbose=verbose, **kwargs)
inputs = _parse_bioclim_inputs(**kwargs)
output=_execute_request._executeRequest(processid, inputs, "name", verbose, outputfname)
return output
def submitFeatureCoverageWCSIntersection(geoType,
dataSetURI,
varID,
attribute='the_geom',
value=None,
gmlIDs=None,
verbose=False,
coverage='true',
WFS_URL=None,
outputfname=None,
sleepSecs=10):
"""
Makes a featureCoverageWCSIntersection algorithm call.
"""
featureCollection = _get_geotype._getFeatureCollectionGeoType(
geoType, attribute, value, gmlIDs, WFS_URL)
if featureCollection is None:
return
processid = 'gov.usgs.cida.gdp.wps.algorithm.FeatureCoverageIntersectionAlgorithm'
inputs = [("DATASET_URI", dataSetURI), ("DATASET_ID", varID),
("REQUIRE_FULL_COVERAGE", coverage),
("FEATURE_COLLECTION", featureCollection)]
output = "OUTPUT"
return _execute_request._executeRequest(processid, inputs, output, verbose,
outputfname, sleepSecs)
def submitFeatureCoverageWCSIntersection(geoType, dataSetURI, varID, attribute='the_geom', value=None, gmlIDs=None, verbose=False, coverage='true', WFS_URL=None, outputfname=None, sleepSecs=10):
"""
Makes a featureCoverageWCSIntersection algorithm call.
"""
featureCollection = _get_geotype._getFeatureCollectionGeoType(geoType, attribute, value, gmlIDs, WFS_URL)
if featureCollection is None:
return
processid = 'gov.usgs.cida.gdp.wps.algorithm.FeatureCoverageIntersectionAlgorithm'
inputs = [("DATASET_URI", dataSetURI),
("DATASET_ID", varID),
("REQUIRE_FULL_COVERAGE",coverage),
("FEATURE_COLLECTION", featureCollection)]
output = "OUTPUT"
return _execute_request._executeRequest(processid, inputs, output, verbose, outputfname, sleepSecs)
def submitFeatureWeightedGridStatistics(geoType, dataSetURI, varID, startTime,
endTime, attribute, value, gmlIDs,
verbose, coverage, delim, stat, grpby,
timeStep, summAttr, weighted, WFS_URL,
outputfname, sleepSecs):
"""
Makes a featureWeightedGridStatistics algorithm call.
The web service interface implemented is summarized here:
https://my.usgs.gov/confluence/display/GeoDataPortal/Generating+Area+Weighted+Statistics+Of+A+Gridded+Dataset+For+A+Set+Of+Vector+Polygon+Features
Note that varID and stat can be a list of strings.
"""
# test for dods:
dataSetURI = _execute_request.dodsReplace(dataSetURI)
log.info('Generating feature collection.')
featureCollection = _get_geotype._getFeatureCollectionGeoType(
geoType, attribute, value, gmlIDs, WFS_URL)
if featureCollection is None:
return
processid = 'gov.usgs.cida.gdp.wps.algorithm.FeatureWeightedGridStatisticsAlgorithm'
if weighted == False:
processid = 'gov.usgs.cida.gdp.wps.algorithm.FeatureGridStatisticsAlgorithm'
solo_inputs = [("FEATURE_ATTRIBUTE_NAME", attribute),
("DATASET_URI", dataSetURI), ("TIME_START", startTime),
("TIME_END", endTime),
("REQUIRE_FULL_COVERAGE", str(coverage).lower()),
("DELIMITER", delim), ("GROUP_BY", grpby),
("SUMMARIZE_TIMESTEP", str(timeStep).lower()),
("SUMMARIZE_FEATURE_ATTRIBUTE", str(summAttr).lower()),
("FEATURE_COLLECTION", featureCollection)]
if isinstance(stat, list):
num_stats = len(stat)
if num_stats > 7:
raise Exception('Too many statistics were submitted.')
else:
num_stats = 1
if isinstance(varID, list):
num_varIDs = len(varID)
else:
num_varIDs = 1
inputs = [('', '')] * (len(solo_inputs) + num_varIDs + num_stats)
count = 0
rmvCnt = 0
for solo_input in solo_inputs:
if solo_input[1] != None:
inputs[count] = solo_input
count += 1
else:
rmvCnt += 1
del inputs[count:count + rmvCnt]
if num_stats > 1:
for stat_in in stat:
if stat_in not in [
"MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM",
"COUNT"
]:
raise Exception(
'The statistic %s is not in the allowed list: "MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM", "COUNT"'
% stat_in)
inputs[count] = ("STATISTICS", stat_in)
count += 1
elif num_stats == 1:
if stat not in [
"MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM",
"COUNT"
]:
raise Exception(
'The statistic %s is not in the allowed list: "MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM", "COUNT"'
% stat)
inputs[count] = ("STATISTICS", stat)
count += 1
if num_varIDs > 1:
for var in varID:
inputs[count] = ("DATASET_ID", var)
count += 1
elif num_varIDs == 1:
inputs[count] = ("DATASET_ID", varID)
output = "OUTPUT"
return _execute_request._executeRequest(processid, inputs, output, verbose,
outputfname, sleepSecs)
def submitFeatureWeightedGridStatistics(geoType, dataSetURI, varID, startTime, endTime, attribute, value, gmlIDs,
verbose, coverage, delim, stat, grpby, timeStep, summAttr, weighted, WFS_URL, outputfname, sleepSecs):
"""
Makes a featureWeightedGridStatistics algorithm call.
The web service interface implemented is summarized here:
https://my.usgs.gov/confluence/display/GeoDataPortal/Generating+Area+Weighted+Statistics+Of+A+Gridded+Dataset+For+A+Set+Of+Vector+Polygon+Features
Note that varID and stat can be a list of strings.
"""
# test for dods:
dataSetURI = _execute_request.dodsReplace(dataSetURI)
log.info('Generating feature collection.')
featureCollection = _get_geotype._getFeatureCollectionGeoType(geoType, attribute, value, gmlIDs, WFS_URL)
if featureCollection is None:
return
processid = 'gov.usgs.cida.gdp.wps.algorithm.FeatureWeightedGridStatisticsAlgorithm'
if weighted==False:
processid = 'gov.usgs.cida.gdp.wps.algorithm.FeatureGridStatisticsAlgorithm'
solo_inputs = [("FEATURE_ATTRIBUTE_NAME",attribute),
("DATASET_URI", dataSetURI),
("TIME_START",startTime),
("TIME_END",endTime),
("REQUIRE_FULL_COVERAGE",str(coverage).lower()),
("DELIMITER",delim),
("GROUP_BY", grpby),
("SUMMARIZE_TIMESTEP", str(timeStep).lower()),
("SUMMARIZE_FEATURE_ATTRIBUTE",str(summAttr).lower()),
("FEATURE_COLLECTION", featureCollection)]
if isinstance(stat, list):
num_stats=len(stat)
if num_stats > 7:
raise Exception('Too many statistics were submitted.')
else:
num_stats=1
if isinstance(varID, list):
num_varIDs=len(varID)
else:
num_varIDs=1
inputs = [('','')]*(len(solo_inputs)+num_varIDs+num_stats)
count=0
rmvCnt=0
for solo_input in solo_inputs:
if solo_input[1]!=None:
inputs[count] = solo_input
count+=1
else:
rmvCnt+=1
del inputs[count:count+rmvCnt]
if num_stats > 1:
for stat_in in stat:
if stat_in not in ["MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM", "COUNT"]:
raise Exception('The statistic %s is not in the allowed list: "MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM", "COUNT"' % stat_in)
inputs[count] = ("STATISTICS",stat_in)
count+=1
elif num_stats == 1:
if stat not in ["MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM", "COUNT"]:
raise Exception('The statistic %s is not in the allowed list: "MEAN", "MINIMUM", "MAXIMUM", "VARIANCE", "STD_DEV", "SUM", "COUNT"' % stat)
inputs[count] = ("STATISTICS",stat)
count+=1
if num_varIDs > 1:
for var in varID:
inputs[count] = ("DATASET_ID",var)
count+=1
elif num_varIDs == 1:
inputs[count] = ("DATASET_ID",varID)
output = "OUTPUT"
return _execute_request._executeRequest(processid, inputs, output, verbose, outputfname, sleepSecs)
