Fix candidates scaling issue and update IPP example

itskalvik · Aug 22, 2024 · 5b9e8ca · 5b9e8ca
1 parent 89888be
commit 5b9e8ca
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Showing 7 changed files with 61 additions and 103 deletions.
diff --git a/benchmarks/plots.ipynb b/benchmarks/plots.ipynb
diff --git a/examples/IPP.ipynb b/examples/IPP.ipynb
diff --git a/setup.py b/setup.py
@@ -1,6 +1,6 @@
 from setuptools import setup, find_packages
 
-__version__ = "1.0.4"
+__version__ = "1.0.5"
 
 setup(
     name='sgptools',

diff --git a/sgptools/models/core/augmented_gpr.py b/sgptools/models/core/augmented_gpr.py
@@ -42,7 +42,7 @@ class AugmentedGPR(GPR):
     def __init__(
         self,
         *args,
-        transform,
+        transform=None,
         **kwargs
     ):
         super().__init__(

diff --git a/sgptools/models/core/augmented_sgpr.py b/sgptools/models/core/augmented_sgpr.py
@@ -52,7 +52,7 @@ class AugmentedSGPR(SGPR):
     def __init__(
         self,
         *args,
-        transform,
+        transform=None,
         inducing_variable_time=None,
         **kwargs
     ):

diff --git a/sgptools/utils/data.py b/sgptools/utils/data.py
@@ -190,6 +190,7 @@ def get_dataset(dataset_type, dataset_path=None,
     X_train = X_scaler.transform(X_train)*10.0
     X_test = X_scaler.transform(X_test)*10.0
     X = X_scaler.transform(X)*10.0
+    candidates = X_scaler.transform(candidates)*10.0
 
     y_scaler = StandardScaler()
     y_scaler.fit(y_train)

diff --git a/sgptools/utils/tsp.py b/sgptools/utils/tsp.py
@@ -25,7 +25,8 @@ def run_tsp(nodes,
             depth=1, 
             resample=None, 
             start_idx=None,
-            end_idx=None):
+            end_idx=None,
+            time_limit=10):
     """Method to run TSP/VRP with arbitrary start and end nodes, 
     and without any distance constraint
     
@@ -38,6 +39,7 @@ def run_tsp(nodes,
                         `resample` number of points
         start_idx (list): Optionl list of start node indices from which to start the solution path 
         end_idx (list): Optionl list of end node indices from which to start the solution path 
+        time_limit (int): TSP runtime time limit in seconds
 
     Returns:
         paths (ndarray): Solution paths
@@ -102,7 +104,7 @@ def distance_callback(from_index, to_index):
     search_parameters.local_search_metaheuristic = (
         routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH
     )
-    search_parameters.time_limit.seconds = 10
+    search_parameters.time_limit.seconds = time_limit
     solution = routing.SolveWithParameters(search_parameters)
 
     paths = None