Merge pull request #59 from loosolab/55-tfcomb-changes-numpy-error-ha…

…ndling

Fixes #55 floating-point error handling

CHANGELOG.rst

@@ -1,3 +1,7 @@
+1.0.4 (in progress)
+-------------------
+- Fix for floating-point error handling (#55)
+
 1.0.3 (23-01-2023)
 ------------------
 - Added pyproject.toml to fix error introduced in 1.0.2 when installing with pip

tfcomb/__init__.py

@@ -1,6 +1,6 @@
 from importlib import import_module
 
-__version__ = "1.0.3"
+__version__ = "1.0.4-b"
 
 #Set classes to be available directly from upper tfcomb, i.e. "from tfcomb import CombObj"
 global_classes = ["tfcomb.objects.CombObj",

tfcomb/network.py

@@ -61,7 +61,9 @@ def _establish_node_attributes(table, node):
 
 	for attribute in columns_to_assign:
 		try:
-			p = scipy.stats.chisquare(factorized[node], f_exp=factorized[attribute])[1]
+			# temporary change numpy floating-point error handling
+			with np.errstate(all="raise"):
+				p = scipy.stats.chisquare(factorized[node], f_exp=factorized[attribute])[1]
 		except ValueError: #observed frequencies != expected frequencies
 			p = 0.0 #not correlated
 		except FloatingPointError: #sum of factorized is 0 -> all nan

tfcomb/objects.py

@@ -48,7 +48,6 @@
 from tfcomb.utils import *
 
 
-np.seterr(all='raise') # raise errors for runtimewarnings
 #pd.options.mode.chained_assignment = 'raise' # for debugging
 pd.options.mode.chained_assignment = None
 

tfcomb/utils.py

@@ -1981,7 +1981,9 @@ def get_threshold(data, which="upper", percent=0.05, _n_max=10000, verbosity=0,
 
 		#Catch any exceptions from fitting
 		try:
-			params = distribution.fit(data_finite)
+			# temporary change numpy floating-point error handling
+			with np.errstate(all="raise"):
+				params = distribution.fit(data_finite)
 		except Exception as e:
 			logger.error("Exception ({0}) occurred while fitting data to '{1}' distribution; skipping this distribution. Error message was: {2} ".format(e.__class__.__name__, distribution.name, e))
 			continue