Merge pull request #150 from NSAPH-Projects/release_0.1.4

mauriciogtec · web-flow · commit ed8d61dca1e6 · 2023-12-04T16:32:10.000-05:00
Release 0.1.4
diff --git a/benchmarks/conf/algo/dragonspatial.yaml b/benchmarks/conf/algo/dragonspatial.yaml
@@ -15,11 +15,11 @@ tune:
     max_iter:
       _target_: ray.tune.choice
       _args_:
-        - [2_500, 5_000]
+        - [1_000, 5_000]
     hidden_dim:
       _target_: ray.tune.choice
       _args_:
-        - [16, 64]
+        - [16, 32]
     hidden_layers:
       _target_: ray.tune.choice
       _args_:
@@ -28,8 +28,8 @@ tune:
       _target_: ray.tune.loguniform
       _args_: [1e-5, 1e-1]
     dropout:
-      _target_: ray.tune.loguniform
-      _args_: [1e-3, 0.5]
+      _target_: ray.tune.uniform
+      _args_: [1e-2, 0.5]
     lam:
       _target_: ray.tune.loguniform
       _args_: [1e-5, 0.1]
diff --git a/benchmarks/conf/algo/drnetspatial.yaml b/benchmarks/conf/algo/drnetspatial.yaml
@@ -15,11 +15,11 @@ tune:
     max_iter:
       _target_: ray.tune.choice
       _args_:
-        - [2_500, 5_000]
+        - [1_000, 5_000]
     hidden_dim:
       _target_: ray.tune.choice
       _args_:
-        - [16, 64]
+        - [16, 32]
     hidden_layers:
       _target_: ray.tune.choice
       _args_:
@@ -28,8 +28,8 @@ tune:
       _target_: ray.tune.loguniform
       _args_: [1e-5, 1e-1]
     dropout:
-      _target_: ray.tune.loguniform
-      _args_: [1e-3, 0.5]
+      _target_: ray.tune.uniform
+      _args_: [1e-2, 0.5]
     lam:
       _target_: ray.tune.loguniform
       _args_: [1e-5, 0.1]
diff --git a/benchmarks/conf/algo/gcn.yaml b/benchmarks/conf/algo/gcn.yaml
@@ -3,18 +3,25 @@ needs_train_test_split: true
 method:
   _target_: spacebench.algorithms.GCN
   verbose: false
-  epochs: 2_500
 
 tune:
-  param_space:
+  param_space:  
+    epochs:
+      _target_: ray.tune.choice
+      _args_:
+        - [1_000, 2_500]
     hidden_dim:
       _target_: ray.tune.choice
       _args_:
-        - [16, 64]
+        - [16, 32]
     hidden_layers:
       _target_: ray.tune.choice
       _args_:
         - [1, 2]
+    lr:
+      _target_: ray.tune.choice
+      _args_:
+        - [1e-3, 3e-4]
     weight_decay:
       _target_: ray.tune.loguniform
       _args_: [1e-6, 1e-1]
diff --git a/benchmarks/conf/algo/mlp.yaml b/benchmarks/conf/algo/mlp.yaml
@@ -0,0 +1,33 @@
+needs_train_test_split: false
+
+method:
+  _target_: spacebench.algorithms.MLPSpatial
+  spatial_split_kwargs:
+    init_frac: 0.05
+    levels: 0
+    buffer: 1
+    seed: 0
+  lam: 0.0
+  k: 100
+  lr: 0.003
+
+tune:
+  param_space:
+    max_iter:
+      _target_: ray.tune.choice
+      _args_:
+        - [1_000, 5_000]
+    hidden_dim:
+      _target_: ray.tune.choice
+      _args_:
+        - [16, 32]
+    hidden_layers:
+      _target_: ray.tune.choice
+      _args_:
+        - [1, 2]
+    weight_decay:
+      _target_: ray.tune.loguniform
+      _args_: [1e-5, 1e-1]
+    dropout:
+      _target_: ray.tune.uniform
+      _args_: [1e-2, 0.5]
diff --git a/benchmarks/conf/algo/mlpspatial.yaml b/benchmarks/conf/algo/mlpspatial.yaml
@@ -15,11 +15,11 @@ tune:
     max_iter:
       _target_: ray.tune.choice
       _args_:
-        - [2_500, 5_000]
+        - [1_000, 5_000]
     hidden_dim:
       _target_: ray.tune.choice
       _args_:
-        - [16, 64]
+        - [16, 32]
     hidden_layers:
       _target_: ray.tune.choice
       _args_:
@@ -28,8 +28,8 @@ tune:
       _target_: ray.tune.loguniform
       _args_: [1e-5, 1e-1]
     dropout:
-      _target_: ray.tune.loguniform
-      _args_: [1e-3, 0.5]
+      _target_: ray.tune.uniform
+      _args_: [1e-2, 0.5]
     lam:
       _target_: ray.tune.loguniform
       _args_: [1e-5, 0.1]
diff --git a/benchmarks/conf/algo/mlpspatialplus.yaml b/benchmarks/conf/algo/mlpspatialplus.yaml
@@ -2,7 +2,6 @@ needs_train_test_split: false
 
 method:
   _target_: spacebench.algorithms.MLPSpatialPlus
-  max_iter: 2_500
   spatial_split_kwargs:
     init_frac: 0.05
     levels: 0
@@ -13,10 +12,14 @@ method:
 
 tune:
   param_space:
+    max_iter:
+      _target_: ray.tune.choice
+      _args_:
+        - [1_000, 5_000]
     hidden_dim:
       _target_: ray.tune.choice
       _args_:
-        - [16, 64]
+        - [16, 32]
     hidden_layers:
       _target_: ray.tune.choice
       _args_:
@@ -31,7 +34,7 @@ tune:
       _target_: ray.tune.loguniform
       _args_: [1e-5, 0.1]
     dropout:
-      _target_: ray.tune.loguniform
-      _args_: [1e-3, 0.5]
+      _target_: ray.tune.uniform
+      _args_: [1e-2, 0.5]
 
 
diff --git a/benchmarks/conf/algo/spatial.yaml b/benchmarks/conf/algo/spatial.yaml
@@ -1,4 +1,4 @@
-needs_train_test_split: true
+needs_train_test_split: false
 
 method:
   _target_: spacebench.algorithms.Spatial
diff --git a/benchmarks/conf/algo/spatialplus.yaml b/benchmarks/conf/algo/spatialplus.yaml
@@ -1,4 +1,4 @@
-needs_train_test_split: true
+needs_train_test_split: false
 
 method:
   _target_: spacebench.algorithms.SpatialPlus
@@ -13,8 +13,8 @@ tune:
   param_space:
     lam_t:
       _target_: ray.tune.loguniform
-      _args_: [1e-5, 0.1]
+      _args_: [1e-5, 1.0]
     lam_y:
       _target_: ray.tune.loguniform
-      _args_: [1e-5, 0.1]
+      _args_: [1e-5, 1.0]
 
diff --git a/benchmarks/conf/algo/xgboost.yaml b/benchmarks/conf/algo/xgboost.yaml
@@ -8,7 +8,7 @@ tune:
     max_depth:
       _target_: ray.tune.choice
       _args_:
-        - [2, 3, 4]
+        - [2, 3]
     n_estimators:
       _target_: ray.tune.choice
       _args_:
diff --git a/benchmarks/conf/algo/xgboost_coords.yaml b/benchmarks/conf/algo/xgboost_coords.yaml
@@ -0,0 +1,19 @@
+needs_train_test_split: false
+
+method:
+  _target_: spacebench.algorithms.XGBoost
+  coords: true
+
+tune:
+  param_space:
+    max_depth:
+      _target_: ray.tune.choice
+      _args_:
+        - [2, 3]
+    n_estimators:
+      _target_: ray.tune.choice
+      _args_:
+        - [100, 500]
+    learning_rate:
+      _target_: ray.tune.loguniform
+      _args_: [0.01, 1.0]
diff --git a/setup.py b/setup.py
@@ -12,7 +12,7 @@ def read_requirements(file):
 
 setup(
     name="spacebench",
-    version="0.1.3",
+    version="0.1.4",
     author=(
         "Mauricio Tec, Ana Trisovic, Audirac, Michelle, Jie Hu,"
         "Sophie Mirabai Woodward, Naeem Khoshnevis, Francesca Dominici"
diff --git a/spacebench/algorithms/deepspatialplus.py b/spacebench/algorithms/deepspatialplus.py
@@ -511,6 +511,7 @@ def fit(self, dataset: SpaceDataset):
         )
         # 0 coef is intercept, 1,2 are for coords, 3 is treatment
         self.t_coef = (self.params[3] * self.y_std / self.inputs_std[0]).item()
+        self.nn.eval()
 
     def eval(self, dataset: SpaceDataset):
         coords = torch.FloatTensor(dataset.coordinates)
@@ -717,6 +718,8 @@ def fit(self, dataset: SpaceDataset):
 
         # 0 coef is intercept, 1,2 are for coords, 3 is treatment
         self.t_coef = (self.y_params[3] * self.y_std / self.t_mu).item()
+        self.nn_t.eval()
+        self.nn_y.eval()
 
     def eval(self, dataset: SpaceDataset):
         coords = torch.FloatTensor(dataset.coordinates)
@@ -1098,6 +1101,7 @@ def fit(self, dataset: SpaceDataset):
             weight_decay=self.weight_decay,
         )
         # 0 coef is intercept, 1,2 are for coords, 3 is treatment
+        self.nn.eval()
 
     def eval(self, dataset: SpaceDataset):
         coords = torch.FloatTensor(dataset.coordinates)
diff --git a/spacebench/algorithms/pysal_spreg.py b/spacebench/algorithms/pysal_spreg.py
@@ -32,7 +32,7 @@ def fit(self, dataset: SpaceDataset):
         adjmat[np.diag_indices_from(adjmat)] = 0.0
         w = lp.weights.util.full2W(adjmat)
 
-        self.model = spreg.GM_Error(x=x, y=y, w=w)
+        self.model = spreg.GM_Error_Het(x=x, y=y, w=w)
         self.t_coef = self.model.betas[1, 0] * self.sig_y / self.sig_x[0]
 
     def eval(self, dataset: SpaceDataset):
@@ -88,7 +88,7 @@ def fit(self, dataset: SpaceDataset):
         adjmat[np.diag_indices_from(adjmat)] = 0.0
         w = lp.weights.util.full2W(adjmat)
 
-        self.model = spreg.GM_Lag(x=x, y=y, w=w, w_lags=self.w_lags)
+        self.model = spreg.GM_Lag(x=x, y=y, w=w, robust='white', w_lags=self.w_lags)
         self.t_coef = self.model.betas[1, 0] * self.sig_y / self.sig_x[0]
 
     def eval(self, dataset: SpaceDataset):
diff --git a/spacebench/algorithms/spatialplus.py b/spacebench/algorithms/spatialplus.py
@@ -174,11 +174,11 @@ def tps_opt(
         opt.step()
         sched.step(loss)
 
-        # Check for convergence
-        max_grad = params.grad.abs().max()
-        if max_grad < atol:
-            LOGGER.info(f"TPS converged after {it} iterations.")
-            break
+        # # Check for convergence
+        # max_grad = params.grad.abs().max()
+        # if max_grad < atol:
+        #     LOGGER.info(f"TPS converged after {it} iterations.")
+        #     break
 
         it += 1
 

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-needs_train_test_split: true`
	`1`	`+needs_train_test_split: false`
`2`	`2`
`3`	`3`	`method:`
`4`	`4`	`_target_: spacebench.algorithms.Spatial`