Merge pull request #123 from AdamOrmondroyd/cube_samples

FIX: Cube samples in new interface

Author: catherinewatkinson

README.rst

@@ -5,7 +5,7 @@
    :target: https://arxiv.org/abs/1506.00171
    :alt: Open-access paper
 
-PolyChord v 1.22.2
+PolyChord v 1.22.3
 
 Will Handley, Mike Hobson & Anthony Lasenby
 

pypolychord/__init__.py

@@ -1,3 +1,3 @@
-__version__ = "1.22.2"
+__version__ = "1.22.3"
 from pypolychord.settings import PolyChordSettings
 from pypolychord.polychord import run_polychord, run

pypolychord/polychord.py

@@ -552,6 +552,7 @@ def run(loglikelihood, nDims, **kwargs):
         'grade_dims': [nDims],
         'nlives': {},
         'seed': -1,
+        'cube_samples': None,
     }
     default_kwargs['grade_frac'] = ([1.0]*len(default_kwargs['grade_dims'])
                                     if 'grade_dims' not in kwargs else
@@ -573,10 +574,10 @@ def run(loglikelihood, nDims, **kwargs):
                     (kwargs['file_root'] + ".paramnames"))
 
 
-    if 'cube_samples' in kwargs:
-        _make_resume_file(loglikelihood, kwargs['prior'], **kwargs)
-        read_resume = kwargs['read_resume']
-        kwargs['read_resume'] = True
+    read_resume = kwargs['read_resume']
+    if kwargs['cube_samples'] is not None:
+        _make_resume_file(loglikelihood, **kwargs)
+        read_resume = True
 
     def wrap_loglikelihood(theta, phi):
         logL = loglikelihood(theta)
@@ -617,7 +618,7 @@ def wrap_prior(cube, theta):
                      kwargs['cluster_posteriors'],
                      kwargs['write_resume'],
                      kwargs['write_paramnames'],
-                     kwargs['read_resume'],
+                     read_resume,
                      kwargs['write_stats'],
                      kwargs['write_live'],
                      kwargs['write_dead'],
@@ -633,9 +634,6 @@ def wrap_prior(cube, theta):
                      kwargs['seed'],
                      )
 
-    if 'cube_samples' in kwargs:
-        kwargs['read_resume'] = read_resume
-
     try:
         import anesthetic
     except ImportError:

src/polychord/feedback.f90

@@ -28,8 +28,8 @@ subroutine write_opening_statement(settings)
             write(stdout_unit,'("")')
             write(stdout_unit,'("PolyChord: Next Generation Nested Sampling")')
             write(stdout_unit,'("copyright: Will Handley, Mike Hobson & Anthony Lasenby")')
-            write(stdout_unit,'("  version: 1.22.2")')
-            write(stdout_unit,'("  release: 10th Jan 2024")')
+            write(stdout_unit,'("  version: 1.22.3")')
+            write(stdout_unit,'("  release: 22nd Nov 2025")')
             write(stdout_unit,'("    email: wh260@mrao.cam.ac.uk")')
             write(stdout_unit,'("")')
         end if

tests/test_run_pypolychord.py

@@ -70,7 +70,7 @@ def test_run(likelihood, nDims, nDerived):
 
     ns = pypolychord.run(likelihood, nDims, nDerived=nDerived,
                          prior=uniform_prior, paramnames=paramnames,
-                         read_resume=False)
+                         read_resume=False, feedback=0)
     assert isinstance(ns, ac.NestedSamples)
 
 
@@ -128,3 +128,12 @@ def test_grade_dims():
         pypolychord.run(gaussian_likelihood, 5, nDerived=1,
                         prior=uniform_prior, read_resume=False,
                         grade_dims=grade_dims)
+
+
+def test_cube_samples():
+    cube_samples = np.array([[0.1, 0.2, 0.3, 0.4],
+                             [0.5, 0.6, 0.7, 0.8]])
+    pypolychord.run(gaussian_likelihood, 4, nDerived=1,
+                    prior=uniform_prior,
+                    read_resume=False,
+                    cube_samples=cube_samples)