def generate_solutions_tables(self):
''' code from Adam use rpy2 to execute rcode which reads out a solutions file to pandas '''
col_names = [
'alpha', 'tau', 'AT', 'b', 'delta', 'LL', 'mode_curv',
'genome mass', 'sigma.h.hat', 'theta.z.hat', 'sigma.A.hat',
'theta.Q.hat', 'lambda.hat', 'theta.0', 'frac.het', 'SCNA_LL',
'entropy', 'Kar_LL', 'WGD', 'combined_LL', 'SSNV_LL',
'SCNA_Theta_integral', 'dens'
]
# Build R function to be used as a python package
load_RData_func_str = """
load_RData <- function(file_path) {
load(file_path)
head_name <- ls()[1]
file_name <- names(`segobj.list`)[1]
r_data <- `segobj.list`[[file_name]]$mode.res$mode.tab
return(r_data)
}
"""
# Pack the function above as a package
r_pack = SignatureTranslatedAnonymousPackage(load_RData_func_str,
"r_pack")
print 'Generating absolute tables for ' + str(len(
self.data_table)) + ' samples'
pandas2ri.activate()
for index, row in self.data_table.iterrows():
if np.mod(index, 100) == 0:
print str(index) + '/' + str(len(self.data_table))
r_data = r_pack.load_RData(row['absolute_summary_data'])
abs_table = pd.DataFrame(pandas2ri.ri2py(r_data),
columns=col_names)
self.pp_modes_tables[row['pair_id']] = abs_table
pandas2ri.deactivate()
def convertRtoPandas(file_path):
# Pack the function above as a package
r_pack = SignatureTranslatedAnonymousPackage(load_RData_func_str, "r_pack")
pandas2ri.activate()
r_data = r_pack.load_RData(file_path)
py_data = pd.DataFrame(pandas2ri.ri2py(r_data), columns=col_names)
pandas2ri.deactivate()
return py_data
