Updated docstrings

handley-lab · Sep 19, 2024 · 7a10785 · 7a10785
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diff --git a/anesthetic/tension.py b/anesthetic/tension.py
@@ -3,38 +3,42 @@
 from scipy.stats import chi2
 
 
-def tension_stats(A, B, AB, nsamples=None, beta=None):  # noqa: D301
+def stats(A, B, AB, nsamples=None, beta=None):  # noqa: D301
     """Compute tension statistics between two samples.
 
     Using nested sampling we can compute:
 
     - ``logR``: Logarithmic of R statistic
 
       .. math::
-        \\log R = \\log Z_\\mathrm{AB} - \\log Z_\\mathrm{A}
-                     - \\log Z_\\mathrm{B}
+        \\log \mathcal{R} = \\log \mathcal{Z}_\\mathrm{AB} 
+                            - \\log \mathcal{Z}_\\mathrm{A}
+                            - \\log \mathcal{Z}_\\mathrm{B}
 
     - ``logI``: Logarithmic of information ratio
 
       .. math::
-        \\log I = D_\\mathrm{KL}^A + D_\\mathrm{KL}^B - D_\\mathrm{KL}^{AB}
+        \\log \mathcal{I} = \mathcal{D}_\\mathrm{KL}^A 
+                            + \mathcal{D}_\\mathrm{KL}^B 
+                            - \mathcal{D}_\\mathrm{KL}^{AB}
 
     - ``logS``: Logarithmic of suspiciousness
 
       .. math::
-        \\log S = \\log L_\\mathrm{AB} - \\log
-        L_\\mathrm{A} - \\log L_\\mathrm{B}
+        \\log \mathcal{S} = \\log \mathcal{L}_\\mathrm{AB} 
+                            - \\log \mathcal{L}_\\mathrm{A} 
+                            - \\log \mathcal{L}_\\mathrm{B}
 
     - ``d_G``: Gaussian model dimensionality
       (or posterior variance of the log-likelihood)
 
       .. math::
-        d_\\mathrm{G}/2 = \\mathrm{var}(\\log L)_P
+        d_\\mathrm{G}/2 = \\mathrm{var}(\\log \mathcal{L})_\mathcal{P}
 
     - ``p``: p-value for the tension between two samples
 
       .. math::
-        p = \\int_{d_\\mathrm{G} - 2 \\log S}^{\\infty} \\chi^2 (x)dx
+        p = \\int_{d_\\mathrm{G} - 2 \\log \mathcal{S}}^{\\infty} \\chi^2 (x)dx
 
     Parameters
     ----------
@@ -72,15 +76,15 @@ def tension_stats(A, B, AB, nsamples=None, beta=None):  # noqa: D301
 
     logR = statsAB.logZ-statsA.logZ-statsB.logZ
     samples_stats['logR'] = logR
-    samples_stats.set_label('logR', r'$\log{R}$')
+    samples_stats.set_label('logR', r'$\log\mathcal{R}$')
 
     logI = statsA.D_KL + statsB.D_KL - statsAB.D_KL
     samples_stats['logI'] = logI
-    samples_stats.set_label('logI', r'$\log{I}$')
+    samples_stats.set_label('logI', r'$\log\mathcal{I}$')
 
     logS = statsAB.logL_P - statsA.logL_P - statsB.logL_P
     samples_stats['logS'] = logS
-    samples_stats.set_label('logS', r'$\log{S}$')
+    samples_stats.set_label('logS', r'$\log\mathcal{S}$')
 
     d_G = statsA.d_G + statsB.d_G - statsAB.d_G
     samples_stats['d_G'] = d_G

diff --git a/tests/example_data/.DS_Store b/tests/example_data/.DS_Store
diff --git a/tests/test_tension.py b/tests/test_tension.py
@@ -1,7 +1,7 @@
 from anesthetic.examples.perfect_ns import correlated_gaussian
 import numpy as np
 from numpy.linalg import inv, solve, slogdet
-from anesthetic.tension import tension_stats
+from anesthetic.tension import stats
 
 
 def test_tension_stats_compatiable_gaussian():
@@ -32,8 +32,7 @@ def test_tension_stats_compatiable_gaussian():
 
     nsamples = 1000
     beta = 1
-    samples_stats = tension_stats(samplesA, samplesB, samplesAB,
-                                  nsamples, beta)
+    samples_stats = stats(samplesA, samplesB, samplesAB, nsamples, beta)
 
     logR_std = samples_stats.logR.std()
     logR_mean = samples_stats.logR.mean()
@@ -51,8 +50,9 @@ def test_tension_stats_compatiable_gaussian():
     logI_exact = -d/2 - 1/2 * slogdet(2*np.pi*(covA+covB))[1] + np.log(V)
     assert logI_mean - 3 * logI_std < logI_exact < logI_mean + 3 * logI_std
 
-    assert samples_stats.get_labels().tolist() == ([r'$\log{R}$',
-                                                    r'$\log{I}$', r'$\log{S}$',
+    assert samples_stats.get_labels().tolist() == ([r'$\log\mathcal{R}$',
+                                                    r'$\log\mathcal{I}$',
+                                                    r'$\log\mathcal{S}$',
                                                     r'$d_\mathrm{G}$', r'$p$'])
 
 
@@ -85,8 +85,7 @@ def test_tension_stats_incompatiable_gaussian():
 
     nsamples = 1000
     beta = 1
-    samples_stats = tension_stats(samplesA, samplesB, samplesAB,
-                                  nsamples, beta)
+    samples_stats = stats(samplesA, samplesB, samplesAB, nsamples, beta)
 
     logR_std = samples_stats.logR.std()
     logR_mean = samples_stats.logR.mean()
@@ -104,6 +103,7 @@ def test_tension_stats_incompatiable_gaussian():
     logI_exact = -d/2 - 1/2 * slogdet(2*np.pi*(covA+covB))[1] + np.log(V)
     assert logI_mean - 3 * logI_std < logI_exact < logI_mean + 3 * logI_std
 
-    assert samples_stats.get_labels().tolist() == ([r'$\log{R}$',
-                                                    r'$\log{I}$', r'$\log{S}$',
+    assert samples_stats.get_labels().tolist() == ([r'$\log\mathcal{R}$',
+                                                    r'$\log\mathcal{I}$',
+                                                    r'$\log\mathcal{S}$',
                                                     r'$d_\mathrm{G}$', r'$p$'])