suppress warnings, fixup tutorials

Author: ejolly

docs/tutorials/01_DataOperations/plot_download.ipynb

@@ -529,7 +529,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },

docs/tutorials/basic/index.md

@@ -1739,7 +1739,8 @@ def estimate_srm_stats(results, var_name, tailed=1):
                 estimate = results[var_name].mean()
                 standardized = (results[var_name] / results["total_variance"]).mean()
                 se = results[var_name].std() / np.sqrt(len(results[var_name]))
-                t = estimate / se
+                with np.errstate(invalid="ignore", divide="ignore"):
+                    t = estimate / se
                 if tailed == 1:
                     p = 1 - stats.t.cdf(t, len(results[var_name]) - 1)
                 elif tailed == 2:

nltools/data/adjacency.py

@@ -480,7 +480,8 @@ def fisher_r_to_z(r):
         Clips r values to (-1, 1) range to avoid invalid arctanh inputs
     """
     # Clip r to valid range for arctanh to avoid invalid value warnings
-    return np.arctanh(r)
+    with np.errstate(invalid="ignore"):
+        return np.arctanh(r)
 
 
 def fisher_z_to_r(z):
@@ -1003,7 +1004,8 @@ def summarize_bootstrap(data, save_weights=False):
     wstd = data.std()
     wmean = data.mean()
     wz = deepcopy(wmean)
-    wz.data = wmean.data / wstd.data
+    with np.errstate(invalid="ignore", divide="ignore"):
+        wz.data = wmean.data / wstd.data
     wp = deepcopy(wmean)
     wp.data = 2 * (1 - norm.cdf(np.abs(wz.data)))
     # Create outputs

nltools/stats.py

@@ -147,7 +147,6 @@ def test_get_collection_image_metadata_shows_warning(self, mock_fetch_collection
             assert len(result) == 1
 
 
-@pytest.mark.slow
 class TestIntegration:
     """Integration tests that require network access"""