NASA Center for Climate Simulation

# Compute Max to Find High Precipitation Events

import cwt, os

class TestWorkflow:
    plotter = cwt.initialize()
    host ="https://edas.nccs.nasa.gov/wps/cwt"
    wps = cwt.WPS( host, log=True,log_file=os.path.expanduser("~/esgf_api.log"), verify=False )

    def spatial_max( self ):

# Set the domain to be Hawaii to San Francisco, from December 15, 2014 to December 20, 2017

        domain_data = { 'id': 'd0', 'lat': {'start':-90, 'end':90,'crs':'values'},
                        'lon': {'start':0, 'end':360, 'crs':'values'},
                        'time':{'start':'2014-09-01T00:00:00', 'end':'2017-03-31T23:00:00', 'crs':'timestamps'}}

        d0 = cwt.Domain.from_dict(domain_data)

# Set the input data to be 6 hourly CFSR precipition data (variable pr)

        inputs = cwt.Variable("collection://cip_cfsr_6hr", "pr",domain=d0 )

# Set the operation to be "maximum" operating over the xy axes

        op_data = { 'name': "xarray.max", 'axes': "xy" }
        op = cwt.Process.from_dict( op_data ) 
        op.set_inputs( inputs )

# Set the operation to be "sum" operating over the time axes
       
        op_data1 =  { 'name': "xarray.sum", 'axes': "t" }
        op1 =  cwt.Process.from_dict( op_data1 )
        op1.set_inputs( inputs )  

        self.wps.execute( op, domains=[d0], async=True )
        dataPaths_max = self.wps.download_result(op)
       
        self.wps.execute( op1, domains=[d0], async=True )
        dataPaths_sum = self.wps.download_result(op1)
 
# Plot both a precitation vs time and a precipitation over the spatial range plot   

        for dataPath in dataPaths_max:
           self.plotter.mpl_timeplot(dataPath)

        for dataPath in dataPaths_sum:
           self.plotter.mpl_spaceplot(dataPath)

executor = TestWorkflow()
executor.spatial_max()