n.b. this is done to solve a memory leak inherant import_FCS_file. Perhaps there is a leak in loadFCS?
@author: ngdavid
"""
from HEADER_Import_FCS import import_FCS_file
from HEADER_ND_Binning import ND_Binning
from HEADER_Generate_HDF5 import Bin_2_HDF5_File
import HEADER_Program_Variables as Prog_Var
import sys
import json
case_num = sys.argv[1]
tubes = json.loads(sys.argv[2])
HDF5_Cases = Bin_2_HDF5_File(Prog_Var.output_file, overwrite=False)
tube, binning = {}, {}
for k in tubes.keys():
tube[k] = import_FCS_file(tubes[k],
Prog_Var.comp_file,
gate_coords=Prog_Var.coords,
limits=True,
strict=False)
binning[k] = ND_Binning(tube[k], Prog_Var.parameters, bins=10)
HDF5_Cases.push_case(case_num,
tube,
binning,
ordering=Prog_Var.Pattern,
saveFCS=False)
print('{} has been pushed to {}'.format(case_num, Prog_Var.output_file))
else:
bin_dict = pd.Series(bins,columns)
elif isinstance(bins,dict):
if bins.keys() not in columns or columns not in bins.keys():
raise RuntimeWarning("The bin keys do not match the provided columns")
else:
raise RuntimeWarning("bin dict not implemented")
else:
raise TypeError("provided bins parameter is not supported")
return bin_dict
def Return_Coordinates(self,index):
"""
Returns the bin parameters
"""
coords = self.histogram.indices[index]
self.x = np.array(np.unravel_index(coords,list(self.bins)),dtype=np.float32).T
return pd.DataFrame(self.x / np.array(self.bins)[np.newaxis],
index = coords,
columns=self.bins.index.values)
if __name__ == "__main__":
from HEADER_Import_FCS import import_FCS_file
filename='/home/ngdavid/Desktop/Ubuntu_Dropbox/Myeloid_Data/Myeloid/12-00005/12-00005_Myeloid 2.fcs'
comp_file='/home/ngdavid/Desktop/Ubuntu_Dropbox/Comp_Libs/M2_Comp_Lib_LSRA.txt'
M4_tube=import_FCS_file(filename,comp_file,limits=True)
parameters = [x for x in M4_tube.data.columns if x not in ['FSC-H','SSC-A','Time']]
binned_data = ND_Binning(M4_tube,parameters,bins=10)
print binned_data.Return_Coordinates([5,6,7,8,9])
"The bin keys do not match the provided columns")
else:
raise RuntimeWarning("bin dict not implemented")
else:
raise TypeError("provided bins parameter is not supported")
return bin_dict
def Return_Coordinates(self, index):
"""
Returns the bin parameters
"""
coords = self.histogram.indices[index]
self.x = np.array(np.unravel_index(coords, list(self.bins)),
dtype=np.float32).T
return pd.DataFrame(self.x / np.array(self.bins)[np.newaxis],
index=coords,
columns=self.bins.index.values)
if __name__ == "__main__":
from HEADER_Import_FCS import import_FCS_file
filename = '/home/ngdavid/Desktop/Ubuntu_Dropbox/Myeloid_Data/Myeloid/12-00005/12-00005_Myeloid 2.fcs'
comp_file = '/home/ngdavid/Desktop/Ubuntu_Dropbox/Comp_Libs/M2_Comp_Lib_LSRA.txt'
M4_tube = import_FCS_file(filename, comp_file, limits=True)
parameters = [
x for x in M4_tube.data.columns if x not in ['FSC-H', 'SSC-A', 'Time']
]
binned_data = ND_Binning(M4_tube, parameters, bins=10)
print binned_data.Return_Coordinates([5, 6, 7, 8, 9])
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 10 12:15:34 2014
Command line file to be accessed via Main.py
n.b. this is done to solve a memory leak inherant import_FCS_file. Perhaps there is a leak in loadFCS?
@author: ngdavid
"""
from HEADER_Import_FCS import import_FCS_file
from HEADER_ND_Binning import ND_Binning
from HEADER_Generate_HDF5 import Bin_2_HDF5_File
import HEADER_Program_Variables as Prog_Var
import sys
import json
case_num = sys.argv[1]
tubes = json.loads(sys.argv[2])
HDF5_Cases = Bin_2_HDF5_File(Prog_Var.output_file,overwrite=False)
tube,binning = {},{}
for k in tubes.keys():
tube[k] = import_FCS_file(tubes[k],Prog_Var.comp_file,gate_coords=Prog_Var.coords,limits=True,strict=False)
binning[k] = ND_Binning(tube[k],Prog_Var.parameters,bins=10)
HDF5_Cases.push_case(case_num,tube,binning,ordering = Prog_Var.Pattern,saveFCS=False)
print('{} has been pushed to {}'.format(case_num,Prog_Var.output_file))
