add reader for dnest4

anesthetic/read/chain.py

@@ -5,6 +5,7 @@
 from anesthetic.read.multinest import read_multinest
 from anesthetic.read.ultranest import read_ultranest
 from anesthetic.read.nestedfit import read_nestedfit
+from anesthetic.read.dnest4 import read_dnest4
 from anesthetic.read.csv import read_csv
 
 
@@ -19,6 +20,7 @@ def read_chains(root, *args, **kwargs):
         * `Nested_fit <https://github.com/martinit18/Nested_Fit>`_,
         * `CosmoMC <https://github.com/cmbant/CosmoMC>`_,
         * `Cobaya <https://github.com/CobayaSampler/cobaya>`_,
+        * `DNest4 <https://github.com/eggplantbren/DNest4/tree/master/code>`_,
         * anything `GetDist <https://github.com/cmbant/getdist>`_ compatible,
         * files produced using ``DataFrame.to_csv()`` from anesthetic.
 
@@ -53,7 +55,7 @@ def read_chains(root, *args, **kwargs):
         )
     errors = []
     readers = [
-        read_polychord, read_multinest, read_cobaya, read_ultranest,
+        read_polychord, read_multinest, read_cobaya, read_ultranest, read_dnest4,
         read_nestedfit, read_getdist, read_csv
     ]
     for read in readers:

anesthetic/read/dnest4.py

@@ -0,0 +1,45 @@
+"""Read NestedSamples from dnest4 output files"""
+import os
+import numpy as np
+from anesthetic.samples import MCMCSamples
+
+
+def heuristically_determine_columns(n_params):
+    """
+    heuristically determines column names. If none are given, parameters are named x_i
+    """
+    return [f'x{i}' for i in range(n_params)]
+
+
+def read_dnest4(root,
+                *args,
+                **kwargs):
+    """Read dnest4 output files.
+
+    Parameters
+    ----------
+    levels_file default output name from dnest4
+    sample_file default output name from dnest4
+    sample_info_file default output name from dnest4
+    root : str
+        root specify the directory only, no specific roots,
+        The files read files are levels_file, sample_file and sample_info.
+    """
+    levels_file = 'levels.txt'
+    sample_file = 'sample.txt'
+    sample_info_file = 'sample_info.txt'
+    weights_file = 'weights.txt'
+
+    levels = np.loadtxt(os.path.join(root, levels_file), dtype=float, delimiter=' ', comments='#')
+    samples = np.genfromtxt(os.path.join(root, sample_file), dtype=float, delimiter=' ', comments='#', skip_header=1)
+    sample_info = np.loadtxt(os.path.join(root, sample_info_file), dtype=float, delimiter=' ', comments='#')
+    weights = np.loadtxt(os.path.join(root, weights_file), dtype=float, delimiter=' ', comments='#')
+    n_params = samples.shape[1]
+    columns = heuristically_determine_columns(n_params)
+
+    return MCMCSamples(data=samples,
+                   columns=columns,
+                   weights=weights,
+                   logL=sample_info[:, 1],
+                   labels=columns, *args,
+                   **kwargs)

docs/source/anesthetic.read.rst

@@ -24,6 +24,15 @@ anesthetic.read.cobaya module
    :undoc-members:
    :show-inheritance:
 
+anesthetic.read.dnest4 module
+-----------------------------
+
+.. automodule:: anesthetic.read.dnest4
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+
 
 anesthetic.read.getdist module
 ------------------------------

tests/example_data/dnest4/README.md

@@ -0,0 +1,2 @@
+these results are generated with https://github.com/eggplantbren/DNest4/tree/master/code/Examples/Rosenbrock
+after hard-coding the number of dimensions to 3 and then postprocessing with showresults.p

tests/example_data/dnest4/levels.txt

@@ -0,0 +1,28 @@
+# log_X, log_likelihood, tiebreaker, accepts, tries, exceeds, visits
+0 -1.79769313486e+308 0 34004 34004 11180 29004
+-0.969533002366 -354500.27465 0.184673637139 23998 31610 14123 39627
+-1.992093494 -51190.6265937 0.102641250532 19348 31083 15920 42045
+-2.97105585853 -11243.6222298 0.10325874618 16150 32920 16626 45679
+-3.97897207133 -3228.1447332 0.0925587904123 13328 34880 17901 48344
+-4.97405916511 -1131.35058306 0.852351592573 11151 35275 18846 50013
+-5.95575811056 -427.258976564 0.701862363078 10072 37653 19414 53338
+-6.96396646863 -162.646813112 0.68451125986 9137 39867 21029 56120
+-7.94957402697 -64.8403524809 0.613021892441 8647 43702 20432 61568
+-9.03067901421 -26.3056692322 0.547511916734 7828 44506 24788 61778
+-9.96095625455 -13.8309395233 0.334151142837 8156 49730 25984 71356
+-10.9692987447 -7.50274694105 0.126042530841 7817 52371 33317 75193
+-11.8132222594 -4.65369550562 0.853768724211 8272 60078 29479 90233
+-12.9133196991 -2.48807948192 0.61849557121 7804 61733 25002 88050
+-14.128256649 -1.16046735761 0.99591232612 7330 60886 26282 82727
+-15.2498883059 -0.562856436041 0.130358708691 7127 64485 34548 87606
+-16.1907059421 -0.325470154533 0.755185646839 7784 74101 16481 105486
+-17.8844715844 -0.13177445907 0.64628464408 5675 57277 8900 70597
+-19.6545796919 -0.0423777562198 0.393064674565 3095 33798 8676 39537
+-20.9945860552 -0.0201426854991 0.336737451471 2296 26703 9618 32218
+-22.1297830757 -0.0109547712599 0.186364854844 2101 23981 9711 30437
+-23.2211859552 -0.00633328574242 0.761743194641 1908 22712 7536 29262
+-24.4377625857 -0.00321219414708 0.379439831193 1392 17613 6798 21988
+-25.5351949699 -0.00173432053459 0.0956554015875 1166 15570 3206 19207
+-26.8913310896 -0.000907997439061 0.454404674518 667 8955 1351 9000
+-28.133055436 -0.000638533356738 0.942850144857 290 3915 142 2105
+-29.2339238102 -0.000420761812001 0.219330831487 37 592 0 0