Update parallel tutorial qmcpy client

tutorial/qmcpy-client-l2-sea.py

@@ -11,39 +11,19 @@
 args = parser.parse_args()
 print(f"Connecting to host URL {args.url}")
 
-# Wrap a given model and fix its last parameters to 0
-class TwoInputModel:
-    def __init__(self, model):
-        self.model = model
-
-    def get_input_sizes(self, config={}):
-        return [2]
-
-    def get_output_sizes(self, config={}):
-        return self.model.get_output_sizes()
-
-    def __call__(self, theta, config={}):
-        return self.model([[theta[0][0], theta[0][1], 0,0,0,0,0,0,0,0,0,0,0,0,0,0]], config)
-
-    def supports_evaluate(self):
-        return True
-
-
 # Set up umbridge model and model config
-l2sea_model = umbridge.HTTPModel(args.url, "forward")
-l2sea_fixed_design_params = TwoInputModel(l2sea_model)
-config = {"fidelity": 7}
+l2sea_model = umbridge.HTTPModel(args.url, "benchmark_UQ")
 
 # Get input dimension from model
-d = l2sea_fixed_design_params.get_input_sizes(config)[0]
+d = l2sea_model.get_input_sizes(config)[0]
 
 # Froud [0.25,0.41]
 # Draft [-6.6, -5.7]
 # Choose a distribution to sample via QMC
 dnb2 = qp.DigitalNetB2(d)
 gauss_sobol = qp.Uniform(dnb2, lower_bound=[0.25,-6.6], upper_bound=[0.41,-5.7])
 
-integrand = UMBridgeWrapper(gauss_sobol, l2sea_fixed_design_params, config, parallel=False)
+integrand = UMBridgeWrapper(gauss_sobol, l2sea_model, config, parallel=1)
 
 qmc_sobol_algorithm = qp.CubQMCSobolG(integrand, abs_tol=1e-1, n_init = 256, n_max = 256)
 solution,data = qmc_sobol_algorithm.integrate()