Merge branch 'main' of https://github.com/aangelopoulos/ppi_py

ppi_py/baselines.py

@@ -310,11 +310,13 @@ def classical_logistic_ci(X, Y, alpha=0.1, alternative="two-sided"):
  pointest, np.sqrt(np.diag(cov_mat) / n), alpha, alternative
  )
 
+
 """
  BOOTSTRAP CI
 
 """
 
+
 def classical_bootstrap_ci(
  estimator,
  Y,
@@ -344,11 +346,7 @@ def classical_bootstrap_ci(
  pointest = estimator(Y)
 
  bootstrap_distribution = np.array(
- bootstrap(
- [Y],
- estimator,
- n_resamples=n_resamples
- )
+ bootstrap([Y], estimator, n_resamples=n_resamples)
  )
 
  else:
@@ -357,10 +355,7 @@ def classical_bootstrap_ci(
 
  bootstrap_distribution = np.array(
  bootstrap(
- [X, Y],
- estimator,
- n_resamples=n_resamples,
- paired=[[0, 1]]
+ [X, Y], estimator, n_resamples=n_resamples, paired=[[0, 1]]
  )
  )
 
@@ -377,9 +372,7 @@ def classical_bootstrap_ci(
 
  # Compute the lower and upper bounds depending on the method
  if method == "percentile":
- lower_bound = np.quantile(
- bootstrap_distribution, alpha_lower, axis=0
- )
+ lower_bound = np.quantile(bootstrap_distribution, alpha_lower, axis=0)
  upper_bound = np.quantile(
  bootstrap_distribution, 1 - alpha_upper, axis=0
  )
@@ -405,4 +398,3 @@ def classical_bootstrap_ci(
  raise ValueError(
  "Alternative must be either 'two-sided', 'larger' or 'smaller'."
  )
-