Set width.

monarch-initiative · Sep 26, 2023 · f82825a · f82825a
1 parent 4970780
commit f82825a
Showing 1 changed file with 2 additions and 4 deletions.
diff --git a/docs/tutorial.rst b/docs/tutorial.rst
@@ -63,27 +63,25 @@ For instance, we can partition the patients into two groups based on presence/ab
   >>> from genophenocorr.constants import VariantEffect
   >>> cohort_analysis = CohortAnalysis(cohort, 'NM_1234.5', hpo, include_unmeasured=False)
   >>> frameshift = cohort_analysis.compare_by_variant_type(VariantEffect.FRAMESHIFT_VARIANT)
-  >>> pprint(frameshift) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
+  >>> pprint(frameshift, width=120) # doctest: +NORMALIZE_WHITESPACE
                               With frameshift_variant         Without frameshift_variant
                                                 Count Percent                      Count Percent  p-value
   HP:0001166 (Arachnodactyly)                       4  30.77%                         10  76.92%  0.04718
   HP:0001250 (Seizure)                             11  84.62%                          9  69.23%  0.64472
   HP:0001257 (Spasticity)                           8  61.54%                          9  69.23%  1.00000
-  <BLANKLINE>
 
 
 Or perform similar partitioning based on presence/absence of a *missense* variant:
 
 .. doctest:: tutorial
 
   >>> missense = cohort_analysis.compare_by_variant_type(VariantEffect.MISSENSE_VARIANT)
-  >>> pprint(missense) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
+  >>> pprint(missense, width=120) # doctest: +NORMALIZE_WHITESPACE
                               With missense_variant         Without missense_variant
                                               Count Percent                    Count Percent   p-value
   HP:0001166 (Arachnodactyly)                    13  81.25%                        1  10.00%  0.000781
   HP:0001257 (Spasticity)                        11  68.75%                        6  60.00%  0.692449
   HP:0001250 (Seizure)                           12  75.00%                        8  80.00%  1.000000
-  <BLANKLINE>
 
 
 The tables present the HPO terms that annotate the cohort members and report their counts and p values