[med-svn] [Git][med-team/python-nanomath][upstream] New upstream version 1.2.1+ds
Nilesh Patra (@nilesh)
gitlab at salsa.debian.org
Sun May 16 14:29:54 BST 2021
Nilesh Patra pushed to branch upstream at Debian Med / python-nanomath
Commits:
461e5d26 by Nilesh Patra at 2021-05-16T18:56:01+05:30
New upstream version 1.2.1+ds
- - - - -
4 changed files:
- PKG-INFO
- nanomath.egg-info/PKG-INFO
- nanomath/nanomath.py
- nanomath/version.py
Changes:
=====================================
PKG-INFO
=====================================
@@ -1,6 +1,6 @@
Metadata-Version: 1.2
Name: nanomath
-Version: 1.2.0
+Version: 1.2.1
Summary: A few simple math function for other Oxford Nanopore processing scripts
Home-page: https://github.com/wdecoster/nanomath
Author: Wouter De Coster
=====================================
nanomath.egg-info/PKG-INFO
=====================================
@@ -1,6 +1,6 @@
Metadata-Version: 1.2
Name: nanomath
-Version: 1.2.0
+Version: 1.2.1
Summary: A few simple math function for other Oxford Nanopore processing scripts
Home-page: https://github.com/wdecoster/nanomath
Author: Wouter De Coster
=====================================
nanomath/nanomath.py
=====================================
@@ -53,6 +53,11 @@ class Stats(object):
col="quals",
values=["quals", "lengths"])
self._reads_above_qual = [reads_above_qual(df, q) for q in self._qualgroups]
+ else:
+ self._top5_lengths = get_top_5(df=df,
+ col="lengths",
+ values=["lengths"],
+ fill='quals')
def long_features_as_string(self):
"""formatting long features to a string to print for legacy stats output"""
@@ -95,12 +100,16 @@ class Stats(object):
def unwind_long_features_top5(self, feature, name):
"""for tsv stats output"""
+ if feature not in self.__dict__:
+ return
for entry, label in zip(self.__dict__[feature], range(1, 6)):
self.__dict__[name + ':' + str(label)] = '{} ({})'.format(round(entry[0], ndigits=1),
round(entry[1], ndigits=1))
def unwind_long_features_above_qual(self, feature, name):
"""for tsv stats output"""
+ if feature not in self.__dict__:
+ return
for entry, label in zip(self.__dict__[feature],
['>Q{}:'.format(q) for q in self._qualgroups]):
numberAboveQ, megAboveQ = entry
@@ -148,13 +157,20 @@ def ave_qual(quals, qround=False, tab=errs_tab(128)):
return None
-def get_top_5(df, col, values):
+def get_top_5(df, col, values, fill=False):
if "readIDs" in df:
values.append("readIDs")
- return df.sort_values(col, ascending=False) \
- .head(5)[values] \
- .reset_index(drop=True) \
- .itertuples(index=False, name=None)
+ if fill:
+ return df.sort_values(col, ascending=False) \
+ .head(5)[values] \
+ .assign(fill=[0]*5) \
+ .reset_index(drop=True) \
+ .itertuples(index=False, name=None)
+ else:
+ return df.sort_values(col, ascending=False) \
+ .head(5)[values] \
+ .reset_index(drop=True) \
+ .itertuples(index=False, name=None)
def reads_above_qual(df, qual):
=====================================
nanomath/version.py
=====================================
@@ -1 +1 @@
-__version__ = "1.2.0"
+__version__ = "1.2.1"
View it on GitLab: https://salsa.debian.org/med-team/python-nanomath/-/commit/461e5d26467062fbb1c665e294418b4ec57eea30
--
View it on GitLab: https://salsa.debian.org/med-team/python-nanomath/-/commit/461e5d26467062fbb1c665e294418b4ec57eea30
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