Revert "Previous pull merge timeout. Fixing it."

.github/workflows/run_pytest.yml

@@ -9,7 +9,7 @@ jobs:
   pytesting:
     runs-on: ubuntu-latest
     strategy:
-      fail-fast: true
+      fail-fast: false
       matrix:
         python-version: ["3.8", "3.9", "3.10"]
     steps:
@@ -33,8 +33,7 @@ jobs:
 
     - name: Run pytest
       run: |
-        pytest -n auto --cov --no-cov-on-fail --cov-report=term-missing:skip-covered --cov-report xml:coverage.xml
-      timeout-minutes: 300  # Set the timeout to 1.5 hours for this step
+        pytest -n 2 --cov --no-cov-on-fail --cov-report=term-missing:skip-covered --cov-report xml:coverage.xml
 
     - name: Upload coverage reports to Codecov
       uses: codecov/codecov-action@v3

stemflow/utils/sphere_quadtree.py

@@ -107,7 +107,7 @@ def get_one_ensemble_sphere_quadtree(
     for time_block_index, bin_ in enumerate(temporal_bins):
         time_start = bin_[0]
         time_end = bin_[1]
-        sub_data = data[(data[Temporal1] >= time_start) & (data[Temporal1] < time_end)].copy()
+        sub_data = data[(data[Temporal1] >= time_start) & (data[Temporal1] < time_end)]
         if len(sub_data) == 0:
             continue
 

stemflow/utils/validation.py

@@ -173,17 +173,17 @@ def check_spatial_scale(x_min, x_max, y_min, y_max, grid_length_upper, grid_leng
         warnings.warn(
             "The grid_len_upper_threshold is significantly smaller than the scale of longitude and latitude (x and y). Be sure if this is desired."
         )
-    if (grid_length_upper >= (x_max - x_min)) or (grid_length_upper >= (y_max - y_min)):
+    if (grid_length_upper >= (x_max - x_min) * 100) or (grid_length_upper >= (y_max - y_min) * 100):
         warnings.warn(
-            "The grid_len_upper_threshold is larger than the scale of longitude and latitude (x and y). Be sure if this is desired."
+            "The grid_len_upper_threshold is significantly larger than the scale of longitude and latitude (x and y). Be sure if this is desired."
         )
     if (grid_length_lower <= (x_max - x_min) / 100) or (grid_length_lower <= (y_max - y_min) / 100):
         warnings.warn(
             "The grid_len_lower_threshold is significantly smaller than the scale of longitude and latitude (x and y). Be sure if this is desired."
         )
-    if (grid_length_lower >= (x_max - x_min)) or (grid_length_lower >= (y_max - y_min)):
+    if (grid_length_lower >= (x_max - x_min) * 100) or (grid_length_lower >= (y_max - y_min) * 100):
         warnings.warn(
-            "The grid_len_lower_threshold is larger than the scale of longitude and latitude (x and y). Be sure if this is desired."
+            "The grid_len_lower_threshold is significantly larger than the scale of longitude and latitude (x and y). Be sure if this is desired."
         )
 
 
@@ -192,7 +192,7 @@ def check_temporal_scale(t_min, t_max, temporal_bin_interval):
         warnings.warn(
             "The temporal_bin_interval is significantly smaller than the scale of temporal parameters in provided data. Be sure if this is desired."
         )
-    if temporal_bin_interval >= t_max - t_min:
+    if temporal_bin_interval >= (t_max - t_min) * 100:
         warnings.warn(
-            "The temporal_bin_interval is larger than the scale of temporal parameters in provided data. Be sure if this is desired."
+            "The temporal_bin_interval is significantly larger than the scale of temporal parameters in provided data. Be sure if this is desired."
         )

tests/make_models.py

@@ -32,8 +32,8 @@ def make_STEMClassifier(fold_=2, min_req=1, ensemble_models_disk_saver=False, en
         grid_len=30,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",
@@ -60,8 +60,8 @@ def make_parallel_STEMClassifier(
         grid_len=30,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",
@@ -89,8 +89,8 @@ def make_STEMRegressor(fold_=2, min_req=1, ensemble_models_disk_saver=False, ens
         grid_len=30,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",
@@ -112,12 +112,12 @@ def make_AdaSTEMClassifier(fold_=2, min_req=1, ensemble_models_disk_saver=False,
         save_gridding_plot=True,
         ensemble_fold=fold_,
         min_ensemble_required=min_req,
-        grid_len_upper_threshold=50,
-        grid_len_lower_threshold=20,
+        grid_len_upper_threshold=40,
+        grid_len_lower_threshold=5,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",
@@ -141,12 +141,12 @@ def make_AdaSTEMRegressor(fold_=2, min_req=1, ensemble_models_disk_saver=False,
         save_gridding_plot=True,
         ensemble_fold=fold_,
         min_ensemble_required=min_req,
-        grid_len_upper_threshold=50,
-        grid_len_lower_threshold=20,
+        grid_len_upper_threshold=40,
+        grid_len_lower_threshold=5,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",
@@ -172,12 +172,12 @@ def make_SphereAdaSTEMRegressor(
         save_gridding_plot=True,
         ensemble_fold=fold_,
         min_ensemble_required=min_req,
-        grid_len_upper_threshold=8000,
-        grid_len_lower_threshold=500,
+        grid_len_upper_threshold=5000,
+        grid_len_lower_threshold=100,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",
@@ -198,12 +198,12 @@ def make_SphereAdaClassifier(fold_=2, min_req=1, ensemble_models_disk_saver=Fals
         save_gridding_plot=True,
         ensemble_fold=fold_,
         min_ensemble_required=min_req,
-        grid_len_upper_threshold=8000,
-        grid_len_lower_threshold=500,
+        grid_len_upper_threshold=5000,
+        grid_len_lower_threshold=100,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",
@@ -226,12 +226,12 @@ def make_parallel_SphereAdaClassifier(
         save_gridding_plot=True,
         ensemble_fold=fold_,
         min_ensemble_required=min_req,
-        grid_len_upper_threshold=8000,
-        grid_len_lower_threshold=500,
+        grid_len_upper_threshold=5000,
+        grid_len_lower_threshold=100,
         temporal_start=1,
         temporal_end=366,
-        temporal_step=40,
-        temporal_bin_interval=80,
+        temporal_step=30,
+        temporal_bin_interval=60,
         points_lower_threshold=30,
         Spatio1="longitude",
         Spatio2="latitude",

tests/set_up_data.py

@@ -11,7 +11,7 @@ def get_data():
     data = pickle.load(urlopen(url))
     print("Done.")
     x_names = get_x_names()
-    X = data.drop("count", axis=1)[x_names + ["longitude", "latitude"]].fillna(-1)
+    X = data.drop("count", axis=1)[x_names + ["longitude", "latitude"]]
     y = data["count"].values
 
     assert os.path.exists(len(data) > 0)

tests/test_makegif.py

@@ -6,6 +6,8 @@
 
 from stemflow.utils.plot_gif import make_sample_gif
 
+from .make_models import make_STEMClassifier
+
 size = 5000
 fake_data = pd.DataFrame(
     {
@@ -46,7 +48,7 @@ def test_make_gif():
 
 
 def test_make_gif_changing_ranges():
-    fake_data_ = fake_data[(fake_data["x"] >= 0) & (fake_data["y"] >= 10) & (fake_data["DOY"] >= 20)].copy()
+    fake_data_ = fake_data[(fake_data["x"] >= 0) & (fake_data["y"] >= 10) & (fake_data["DOY"] >= 20)]
 
     tmp_dir = "./stemflow_test_make_gif"
     if not os.path.exists(tmp_dir):