def __init__(self,
shell,
Rconverter=Rconverter,
pyconverter=np.asarray,
cache_display_data=False):
"""
Parameters
----------
shell : IPython shell
pyconverter : callable
To be called on values in ipython namespace before
assigning to variables in rpy2.
cache_display_data : bool
If True, the published results of the final call to R are
cached in the variable 'display_cache'.
"""
super(RMagics, self).__init__(shell)
self.cache_display_data = cache_display_data
self.r = ro.R()
self.Rstdout_cache = []
self.pyconverter = pyconverter
self.Rconverter = Rconverter
def r_mannwhitneyu(sample1, sample2, exact=True, alternative="two.sided"):
sample1 = "c({})".format(str(list(sample1))[1:-1])
sample2 = "c({})".format(str(list(sample2))[1:-1])
robjects.R()("""wres <- wilcox.test({}, {}, alternative="{}"{});
rm(sample1);
rm(sample2);""".format(sample1, sample2, alternative,
", exact=TRUE" if exact else ""))
wres = robjects.r['wres']
uval = wres[0][0]
pval = wres[2][0]
return uval, pval
print "cwd is", os.getcwd()
print "uid is", os.getuid()
print "loaded", __file__
print sys.executable
import math
import pandas as pd
from rpy2 import robjects
from rpy2.robjects.packages import importr
from rpy2.robjects import pandas2ri
from rpy2.robjects import numpy2ri
from rpy2.rinterface import RRuntimeError, NULL
print(robjects.R()(".libPaths()"))
base = importr('base')
pandas2ri.activate()
numpy2ri.activate()
robjects.numpy2ri.activate()
ccprofiler = importr('CCprofiler')
print("imported from r:", ccprofiler)
backend_cache = OrderedDict()
def cached_run_secexploerer(protein_ids, id_type):
