Allow imprecision in global codon proportions sum.

libcodonusage/__init__.py

 __copyright__ = "Copyright (C) 2022 Blaise Li"
 __licence__ = "GNU GPLv3"
-__version__ = "0.17"
+__version__ = "0.18"
 from .libcodonusage import (
     aa2colour,
     aa_usage,

libcodonusage/libcodonusage.py

@@ -384,7 +384,12 @@ in the global usage.
     global_proportions = pd.Series(
         normalize(global_usage.values.reshape(1, -1), norm="l1").flatten(),
         index=global_usage.index)
-    assert global_proportions.sum() == 1.
+    # Can be 0.999999999999...
+    # if global_proportions.sum() != 1.:
+    #     display(global_proportions)
+    #     display(global_proportions.sum())
+    assert np.isclose(global_proportions.sum(), 1.)
+    # assert global_proportions.sum() == 1.
     render_md("""
 Codon usage biases in genes can then be computed by subtracting
 the corresponding global proportion to a codon's proportion.