def reJoinRepDecoy(self):
"""rebuild the decoys energies of the representative pt in each cluster"""
with open(self.rep_dc_file, "w") as coords_output_buffer:
for file_dic in self.file_list:
for key in file_dic.keys():
print key, "==>", file_dic[key]
decoy_file = file_dic["decoy_file"]
mcc_lst_file = file_dic["mcc_lst_file"]
energy_file = file_dic["energy_file"]
cluster_file = file_dic["cluster_file"]
mcc_matrix_file = file_dic["mcc_matrix_file"]
dc_coord = DecoyCoord(origial_text=decoy_file)
dc_coord.setDecoyUnitLines()
mcc_matrix = np.loadtxt(mcc_matrix_file, skiprows=1)
cluster_array = np.loadtxt(cluster_file, dtype=int)
energy_sheet = pd.read_csv(energy_file, sep="\s", header=None) # separeated by space
energy_sheet.columns = self.energy_columns
mcc_lst = pd.read_csv(mcc_lst_file, names=self.mcc_name)
source_sheet = pd.concat([energy_sheet, mcc_lst], axis=1) # concat along the x axis
for cluster_num, cluster in pick_rep.reGroup(cluster_array):
conf_rep = pick_rep.pickRep(mcc_matrix, cluster)
self.rep_sheet = self.rep_sheet.append(
source_sheet.ix[conf_rep], ignore_index=False
) # append to the rep energy sheet
dc_coord.appendRepCoords(coords_output_buffer, conf_rep) # append to the rep coord file
self.rep_sheet = self.rep_sheet.sort(
columns="mcc", ascending=False
) # resort according mcc value, descending order
self.rep_sheet.to_csv(self.rep_ener_file)
def secondReJoinRepDecoy(self):
"""
rebuild the dataframe of features of the all, high, low decoys
"""
self.buildSecondFn()
self.displaySecondFn()
self.initSecondRepFeatureFrame()
# input
file_dic = self.final_dic
mcc_matrix_file = file_dic['mcc_matrix_file']
features_file = file_dic['features_file']
cluster_file = file_dic['cluster_file']
# output
rep_all_ener_file = file_dic['rep_all_ener_file']
rep_low_ener_file = file_dic['rep_low_ener_file']
rep_high_ener_file = file_dic['rep_high_ener_file']
# loading
mcc_matrix = np.loadtxt(mcc_matrix_file, skiprows=1)
cluster_array = np.loadtxt(cluster_file, dtype=int)
feature_sheet = pd.read_csv(features_file) # separeated by comman, which is default
for cluster_num, cluster in pick_rep.reGroup(cluster_array):
conf_rep = pick_rep.pickRep(mcc_matrix, cluster)
self.all_rep_sheet = self.all_rep_sheet.append(feature_sheet.ix[conf_rep], ignore_index=True) # append to the rep energy sheet
self.all_rep_sheet = self.all_rep_sheet.sort(columns='mcc', ascending=False) # resort according mcc value, descending order
self.high_rep_sheet = self.all_rep_sheet[self.all_rep_sheet['mcc'] > 0.6]
self.low_rep_sheet = self.all_rep_sheet[self.all_rep_sheet['mcc'] < 0.4]
self.all_rep_sheet.to_csv(rep_all_ener_file)
self.high_rep_sheet.to_csv(rep_high_ener_file)
self.low_rep_sheet.to_csv(rep_low_ener_file)
def secondTestReJoinRepDecoy(self):
"""
rebuild the dataframe of features of the all, high, low decoys
"""
self.buildTestSecondFn()
self.displaySecondFn()
self.initSecondRepFeatureFrame()
# input
file_dic = self.final_dic
mcc_matrix_file = file_dic["mcc_matrix_file"]
features_file = file_dic["features_file"]
cluster_file = file_dic["cluster_file"]
mcc_file = file_dic["mcc_file"]
# output
rep_all_ener_file = file_dic["rep_all_ener_file"]
rep_low_ener_file = file_dic["rep_low_ener_file"]
rep_high_ener_file = file_dic["rep_high_ener_file"]
# loading
# mcc_matrix = np.loadtxt(mcc_matrix_file, skiprows=1)
cluster_array = np.loadtxt(cluster_file, dtype=int)
feature_sheet = pd.read_csv(features_file, sep="\s+") # separeated by comman, which is default
mcc_sheet = pd.read_csv(mcc_file, header=None)
mcc_sheet.columns = ["mcc"]
feature_sheet = pd.concat([feature_sheet, mcc_sheet], axis=1)
# import random
# max_conf_num = len(feature_sheet['mcc'])
for cluster_num, cluster in pick_rep.reGroup(cluster_array):
# conf_rep = pick_rep.pickRep(mcc_matrix, cluster)
conf_rep = choice(cluster) - 1
# conf_rep = random.randint(0, max_conf_num)
self.all_rep_sheet = self.all_rep_sheet.append(
feature_sheet.ix[conf_rep], ignore_index=True
) # append to the rep energy sheet
self.all_rep_sheet = self.all_rep_sheet.sort(
columns="mcc", ascending=False
) # resort according mcc value, descending order
self.high_rep_sheet = self.all_rep_sheet[self.all_rep_sheet["mcc"] > 0.6]
self.low_rep_sheet = self.all_rep_sheet[self.all_rep_sheet["mcc"] < 0.4]
self.all_rep_sheet.to_csv(rep_all_ener_file)
self.high_rep_sheet.to_csv(rep_high_ener_file)
self.low_rep_sheet.to_csv(rep_low_ener_file)
