[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

dodiscover/ci/categorical_test.py

@@ -57,7 +57,7 @@ def power_divergence(
         Returns a tuple (chi, p_value, dof). `chi` is the
         chi-squared test statistic. The `p_value` for the test, i.e. the
         probability of observing the computed chi-square statistic (or an even
-        higher value), given the null hypothesis that X \u27C2 Y | Zs is True.
+        higher value), given the null hypothesis that X \u27c2 Y | Zs is True.
         If boolean = True, returns True if the p_value of the test is greater
         than `significance_level` else returns False.
 
@@ -112,11 +112,11 @@ def power_divergence(
                 # If one of the values is 0 in the 2x2 table.
                 if isinstance(z_state, str):
                     logging.info(
-                        f"Skipping the test {X} \u27C2 {Y} | {Z[0]}={z_state}. Not enough samples"
+                        f"Skipping the test {X} \u27c2 {Y} | {Z[0]}={z_state}. Not enough samples"
                     )
                 else:
                     z_str = ", ".join([f"{var}={state}" for var, state in zip(Z, z_state)])
-                    logging.info(f"Skipping the test {X} \u27C2 {Y} | {z_str}. Not enough samples")
+                    logging.info(f"Skipping the test {X} \u27c2 {Y} | {z_str}. Not enough samples")
 
             if np.isnan(c):
                 raise RuntimeError(

dodiscover/context_builder.py

@@ -198,7 +198,7 @@ def variables(
         self._latent_variables = latents
 
         if data is not None:
-            (observed, latents) = self._interpolate_variables(data, observed, latents)
+            observed, latents = self._interpolate_variables(data, observed, latents)
             self._observed_variables = observed
             self._latent_variables = latents
 

examples/plot_pc_alg.py

@@ -37,7 +37,6 @@
 from dowhy import gcm
 from dowhy.gcm.util.general import set_random_seed
 
-
 # %%
 # Simulate some data
 # ------------------

examples/plot_score_alg.py

@@ -69,7 +69,6 @@
 from dowhy import gcm
 from dowhy.gcm.util.general import set_random_seed
 
-
 # %%
 # Simulate some data
 # ------------------

examples/prior_know_score.py

@@ -20,7 +20,6 @@
 from dowhy import gcm
 from dowhy.gcm.util.general import set_random_seed
 
-
 # %%
 # Simulate some data
 # ------------------