Merge pull request #108 from MarkDana/fix-a-numerical-issue-in-fisherz

Fix a numerical issue in fisherz

Author: kunwuz

causallearn/utils/cit.py

@@ -163,6 +163,7 @@ def __call__(self, X, Y, condition_set=None):
         except np.linalg.LinAlgError:
             raise ValueError('Data correlation matrix is singular. Cannot run fisherz test. Please check your data.')
         r = -inv[0, 1] / sqrt(inv[0, 0] * inv[1, 1])
+        if abs(r) >= 1: r = (1. - np.finfo(float).eps) * np.sign(r) # may happen when samplesize is very small or relation is deterministic
         Z = 0.5 * log((1 + r) / (1 - r))
         X = sqrt(self.sample_size - len(condition_set) - 3) * abs(Z)
         p = 2 * (1 - norm.cdf(abs(X)))
@@ -382,6 +383,7 @@ def __call__(self, X, Y, condition_set=None):
         except np.linalg.LinAlgError:
             raise ValueError('Data correlation matrix is singular. Cannot run fisherz test. Please check your data.')
         r = -inv[0, 1] / sqrt(inv[0, 0] * inv[1, 1])
+        if abs(r) >= 1: r = (1. - np.finfo(float).eps) * np.sign(r) # may happen when samplesize is very small or relation is deterministic
         Z = 0.5 * log((1 + r) / (1 - r))
         X = sqrt(len(test_wise_deletion_XYcond_rows_index) - len(condition_set) - 3) * abs(Z)
         p = 2 * (1 - norm.cdf(abs(X)))