def screw_around():
pi = robj.r['pi']
print pi
print pi+2
print pi[0]
print pi[0]+2
#create fake binned array
nrow = 5
ncol = 10
counter = 0
binned = np.zeros((nrow, ncol), dtype="float64")
for row in xrange(nrow):
for col in xrange(ncol):
binned[row, col] = counter
counter += 1
#print binned
#get binned array into R data.frame
#vec = robj.FloatVector([1.1, 2.2, 0, 4.4, 5.5, ])
#print binned.shape
print numpy2ri(binned)
rdf = robj.r['data.frame'](numpy2ri(binned), code="ID1000")
#print rdf
# now see if we can get R to use this dataframe
myRcode = """
square <- function(rdf) {
myv = rdf$X2 + rdf$X3
return(myv)
}
doit <- function() {
source("/srv/scratch/carolyn/Dengue_code/Rtest_rpy.R")
run_test_wrap(3)
}
"""
print "wwwwah"
powerpack = SignatureTranslatedAnonymousPackage(myRcode, "powerpack")
print powerpack._rpy2r.keys() #to reveal the functions within powerpack
print powerpack.square(rdf) #to run the function "square" found in powerpack
print powerpack.doit()
def main():
filenames, outdir = parse_arguments() #filenames will be a list
os.chdir(outdir) #change pwd to output directory
#print "filenames", filenames
# will need to get intensity_2D_binned into R data.frame
# intensity_2D_binned was created in my_cython_functions.pyx as follows:
# cdef np.ndarray[np.float_t, ndim=2] my2Da
# my2Da = np.zeros((rt_grid_size, mz_grid_size)) """
#create fake binned array
nrow = 5
ncol = 10
counter = 0
binned = np.zeros((nrow, ncol), dtype="float64")
for row in xrange(nrow):
for col in xrange(ncol):
binned[row, col] = counter
counter += 1
### Option 1 ###
#turn each binned array into one row of what will be an R data.frame
# then add ID to each row and combine these binned arrays
nele = nrow*ncol
rbinned1 = np.reshape(binned, nele)
rbinned1c = np.hstack(( np.array(["ID1001"]), rbinned1 )) #concatenate also works
rbinned2 = np.reshape(binned, nele)
rbinned2c = np.hstack(( np.array(["ID1002"]), rbinned2 ))
stacked = np.vstack((rbinned1c, rbinned2c))
#print stacked
#print stacked.shape #2 by 51
rrdf1 = robj.r['data.frame'](numpy2ri(stacked))
#print rrdf1
### Option 2 ###
#build empty array that is 5 (# mzml files) by 51 (# rt/mz bins + 1 for patient ID)
# fill each row with the binned data
floatD = np.zeros((5,nrow*ncol), dtype="float64")
strD = np.zeros((5,1), dtype='a6') #a6 is the dtype for a 6 character string
respD = np.hstack((strD, floatD))
print respD.shape
for filecount, filename in enumerate(filenames):
if filecount<2:
respD = build_row_of_lcms_matrix(
binned, respD, nrow, ncol, filecount, filename)
#print respD
df2 = robj.r['data.frame'](numpy2ri(respD))
print df2
# now see if we can get R to use this dataframe
myRcode = """
doR <- function(python_respD, lcms_run) {
source("/srv/scratch/carolyn/Dengue_code/prediction_with_LCMS_from_python.R")
run_predictions_wrap(python_respD, lcms_run)
}
"""
#Rpack = SignatureTranslatedAnonymousPackage(myRcode, "Rpack")
#print Rpack._rpy2r.keys() #to reveal the functions within powerpack
#3print Rpack.doR(df2, 1) #to run the function found in powerpack
# now see if we can get R to use this dataframe
myRcode = """
square <- function(rdf) {
myv = rdf$X2 + rdf$X3
return(myv)
}
doit <- function(input) {
source("/srv/scratch/carolyn/Dengue_code/Rtest_rpy.R")
run_test_wrap(input)
}
"""
print "wwwwah"
powerpack = SignatureTranslatedAnonymousPackage(myRcode, "powerpack")
#print powerpack._rpy2r.keys() #to reveal the functions within powerpack
#print powerpack.square(df2) #to run the function "square" found in powerpack
print powerpack.doit(df2)
