Mercurial > repos > immport-devteam > flow_overview

comparison flow_overview/flowstatlib.py @ 0:8283ff163ba6 draft

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author immport-devteam
date Mon, 27 Feb 2017 12:54:37 -0500
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-1:000000000000 0:8283ff163ba6
1 ######################################################################
2 # Copyright (c) 2016 Northrop Grumman.
3 # All rights reserved.
4 ######################################################################
5 from __future__ import print_function
6 import sys
7 import pandas as pd
8 from scipy.stats import gmean
9 from argparse import ArgumentParser
10
11
12 def gen_overview_stats(file_name):
13 flow_stats = {}
14 fcs = pd.read_table(file_name)
15 (events, columns) = fcs.shape
16 flow_stats['fcs'] = fcs
17 flow_stats['events'] = events
18 flow_stats['columns'] = columns - 1
19 flow_stats['data'] = fcs.iloc[:, :-1]
20 flow_stats['population'] = fcs.iloc[:, -1:].iloc[:, 0]
21 flow_stats['population_freq'] = flow_stats['population'].value_counts()
22 flow_stats['population_sample'] = (flow_stats['population_freq'] * (20000/float(events))).round(decimals=0)
23 flow_stats['population_freq_sort'] = flow_stats['population_freq'].sort_index()
24 flow_stats['population_per'] = (flow_stats['population'].value_counts(normalize=True) * 100).round(decimals=2)
25 flow_stats['population_per_sort'] = flow_stats['population_per'].sort_index()
26 flow_stats['population_all'] = pd.concat([flow_stats['population_freq_sort'], flow_stats['population_per_sort']], axis=1)
27 flow_stats['population_all'].columns = ['Count', 'Percentage']
28 flow_stats['min'] = flow_stats['data'].values.min()
29 flow_stats['max'] = flow_stats['data'].values.max()
30 flow_stats['markers'] = list(flow_stats['data'].columns)
31 flow_stats['mfi'] = fcs.groupby('Population').mean().round(decimals=2)
32 flow_stats['mfi_pop'] = pd.merge(flow_stats['mfi'], flow_stats['population_all'], left_index=True, right_index=True)
33 flow_stats['mfi_pop']['Population'] = flow_stats['mfi_pop'].index
34 flow_stats['gmfi'] = fcs.groupby('Population').agg(lambda x: gmean(list(x))).round(decimals=2)
35 flow_stats['gmfi_pop'] = pd.merge(flow_stats['gmfi'], flow_stats['population_all'], left_index=True, right_index=True)
36 flow_stats['gmfi_pop']['Population'] = flow_stats['gmfi_pop'].index
37 flow_stats['mdfi'] = fcs.groupby('Population').median().round(decimals=2)
38 flow_stats['mdfi_pop'] = pd.merge(flow_stats['mdfi'], flow_stats['population_all'], left_index=True, right_index=True)
39 flow_stats['mdfi_pop']['Population'] = flow_stats['mdfi_pop'].index
40
41 #
42 # If the number of events is less than 20000, then return
43 # the complete data set,
44 # Otherwise sample the data to only return 20000 events.
45 if events <= 20000:
46 flow_stats['sample'] = fcs
47 else:
48 fcs_np = fcs.values
49 sample_data = []
50 pop_found = {}
51 for i in range(0, events):
52 population_number = fcs_np[i][columns-1]
53 if population_number in pop_found:
54 if pop_found[population_number] < flow_stats['population_sample'][population_number]:
55 pop_found[population_number] += 1
56 sample_data.append(fcs_np[i])
57 else:
58 pop_found[population_number] = 1
59 sample_data.append(fcs_np[i])
60 flow_stats['sample'] = pd.DataFrame(sample_data)
61 flow_stats['sample'].columns = fcs.columns
62
63 flow_stats['sample_data'] = flow_stats['sample'].iloc[:, :-1]
64 flow_stats['sample_population'] = flow_stats['sample'].iloc[:, -1:].iloc[:, 0]
65
66 return flow_stats
67
68
69 if __name__ == '__main__':
70 parser = ArgumentParser(
71 prog="flowstats",
72 description="Gets statistics on FLOCK run")
73
74 parser.add_argument(
75 '-i',
76 dest="input_file",
77 required=True,
78 help="File locations for flow clr file.")
79
80 parser.add_argument(
81 '-o',
82 dest="out_file",
83 required=True,
84 help="Path to the directory for the output file.")
85 args = parser.parse_args()
86
87 flow_stats = gen_overview_stats(args.input_file)
88 with open(args.out_file, "w") as outf:
89 outf.write("Events: ", flow_stats['events'])
90 outf.write("Min: ", flow_stats['min'])
91 outf.write("Max: ", flow_stats['max'])
92 outf.write("Columns: ", flow_stats['columns'])
93 outf.write("Markers: ", flow_stats['markers'])
94 outf.write("Population: ", flow_stats['population'])
95 outf.write("Population Freq: ", flow_stats['population_freq'])
96 outf.write("Population Sample: ", flow_stats['population_sample'])
97 outf.write("Population Per: ", flow_stats['population_per'])
98 outf.write("Sample Data contains ", len(flow_stats['sample']), " events")
99 outf.write("MIF_POP ", flow_stats['mfi_pop'])
100 sys.exit(0)