-
-
Notifications
You must be signed in to change notification settings - Fork 307
/
MapAlignerPoseClustering.py
255 lines (207 loc) · 8.75 KB
/
MapAlignerPoseClustering.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
import argparse
import pyopenms as pms
from common import addDataProcessing, writeParamsIfRequested, updateDefaults
def align(in_files, out_files, out_trafos, reference_index,
reference_file, params):
in_types = set(pms.FileHandler.getType(in_) for in_ in in_files)
if in_types <= set((pms.Type.MZML, pms.Type.MZXML, pms.Type.MZDATA)):
align_features = False
elif in_types == set((pms.Type.FEATUREXML,)):
align_features = True
else:
raise Exception("different kinds of input files")
algorithm = pms.MapAlignmentAlgorithmPoseClustering()
alignment_params = params.copy("algorithm:", True)
algorithm.setParameters(alignment_params)
algorithm.setLogType(pms.LogType.CMD)
plog = pms.ProgressLogger()
plog.setLogType(pms.LogType.CMD)
if reference_file:
file_ = reference_file
elif reference_index > 0:
file_ = in_files[reference_index-1]
else:
sizes = []
if align_features:
fh = pms.FeatureXMLFile()
plog.startProgress(0, len(in_files), "Determine Reference map")
for i, in_f in enumerate(in_files):
sizes.append((fh.loadSize(in_f), in_f))
plog.setProgress(i)
else:
fh = pms.MzMLFile()
mse = pms.MSExperiment()
plog.startProgress(0, len(in_files), "Determine Reference map")
for i, in_f in enumerate(in_files):
fh.load(in_f, mse)
mse.updateRanges()
sizes.append((mse.getSize(), in_f))
plog.setProgress(i)
plog.endProgress()
__, file_ = max(sizes)
f_fmxl = pms.FeatureXMLFile()
if not out_files:
options = f_fmxl.getOptions()
options.setLoadConvexHull(False)
options.setLoadSubordinates(False)
f_fmxl.setOptions(options)
if align_features:
map_ref = pms.FeatureMap()
f_fxml_tmp = pms.FeatureXMLFile()
options = f_fmxl.getOptions()
options.setLoadConvexHull(False)
options.setLoadSubordinates(False)
f_fxml_tmp.setOptions(options)
f_fxml_tmp.load(file_, map_ref)
algorithm.setReference(map_ref)
else:
map_ref = pms.MSExperiment()
pms.MzMLFile().load(file_, map_ref)
algorithm.setReference(map_ref)
plog.startProgress(0, len(in_files), "Align input maps")
for i, in_file in enumerate(in_files):
trafo = pms.TransformationDescription()
if align_features:
map_ = pms.FeatureMap()
f_fxml_tmp = pms.FeatureXMLFile()
f_fxml_tmp.setOptions(f_fmxl.getOptions())
f_fxml_tmp.load(in_file, map_)
if in_file == file_:
trafo.fitModel("identity")
else:
algorithm.align(map_, trafo)
if out_files:
pms.MapAlignmentTransformer.transformRetentionTimes(map_, trafo)
addDataProcessing(map_, params, pms.ProcessingAction.ALIGNMENT)
f_fxml_tmp.store(out_files[i], map_)
else:
map_ = pms.MSExperiment()
pms.MzMLFile().load(in_file, map_)
if in_file == file_:
trafo.fitModel("identity")
else:
algorithm.align(map_, trafo)
if out_files:
pms.MapAlignmentTransformer.transformRetentionTimes(map_, trafo)
addDataProcessing(map_, params, pms.ProcessingAction.ALIGNMENT)
pms.MzMLFile().store(out_files[i], map_)
if out_trafos:
pms.TransformationXMLFile().store(out_trafos[i], trafo)
plog.setProgress(i+1)
plog.endProgress()
def getModelDefaults(default_model):
params = pms.Param()
params.setValue("type", default_model, "Type of model")
model_types = [ "linear", "interpolated"]
if default_model not in model_types:
model_types.insert(0, default_model)
params.setValidStrings("type", model_types)
model_params = pms.Param()
pms.TransformationModelLinear.getDefaultParameters(model_params)
params.insert("linear:", model_params)
params.setSectionDescription("linear", "Parameters for 'linear' model")
pms.TransformationModelInterpolated.getDefaultParameters(model_params)
entry = model_params.getEntry("interpolation_type")
interpolation_types = entry.valid_strings
model_params.setValidStrings("interpolation_type", interpolation_types)
params.insert("interpolated:", model_params)
params.setSectionDescription("interpolated", "Parameters for 'interpolated' model")
return params
def getDefaultParameters():
model_param = getModelDefaults("linear")
algo_param = pms.MapAlignmentAlgorithmPoseClustering().getParameters()
default = pms.Param()
default.insert("model:", model_param)
default.insert("algorithm:", algo_param)
return default
def main():
parser = argparse.ArgumentParser(description="PeakPickerHiRes")
parser.add_argument("-in",
action="append",
type=str,
dest="in_",
metavar="input_file",
)
parser.add_argument("-seeds",
action="store",
type=str,
metavar="seeds_file",
)
parser.add_argument("-out",
action="append",
type=str,
metavar="output_file",
)
parser.add_argument("-trafo_out",
action="append",
type=str,
metavar="output_file",
)
parser.add_argument("-ini",
action="store",
type=str,
metavar="ini_file",
)
parser.add_argument("-dict_ini",
action="store",
type=str,
metavar="python_dict_ini_file",
)
parser.add_argument("-write_ini",
action="store",
type=str,
metavar="ini_file",
)
parser.add_argument("-write_dict_ini",
action="store",
type=str,
metavar="python_dict_ini_file",
)
parser.add_argument("-reference:file",
action="store",
type=str,
metavar="reference_file",
dest="reference_file",
)
parser.add_argument("-reference:index",
action="store",
type=int,
metavar="reference_index",
dest="reference_index",
)
args = parser.parse_args()
def collect(args):
return [f.strip() for arg in args or [] for f in arg.split(",")]
in_files = collect(args.in_)
out_files = collect(args.out)
trafo_out_files = collect(args.trafo_out)
run_mode = (in_files and (out_files or trafo_out_files))\
and (args.ini is not None or args.dict_ini is not None)
write_mode = args.write_ini is not None or args.write_dict_ini is not None
ok = run_mode or write_mode
if not ok:
parser.error("either specify -in, -(trafo_)out and -(dict)ini for running "
"the map aligner\nor -write(dict)ini for creating std "
"ini file")
defaults = getDefaultParameters()
write_requested = writeParamsIfRequested(args, defaults)
if not write_requested:
updateDefaults(args, defaults)
if not out_files and not trafo_out_files:
parser.error("need -out or -trafo_out files")
if out_files and len(out_files) != len(in_files):
parser.error("need as many -out files as -in files")
if trafo_out_files and len(trafo_out_files) != len(in_files):
parser.error("need as many -trafo_out files as -in files")
if args.reference_index is not None and args.reference_file is not None:
parser.error("can only handle either reference:index or reference:file")
if args.reference_index is not None:
if args.reference_index <0 or args.reference_index >= len(in_files):
parser.error("reference:index invalid")
if args.reference_file is not None:
if args.reference_file not in in_files:
parser.error("reference_file not in input files")
align(in_files, out_files, trafo_out_files, args.reference_index or 0,
args.reference_file or "", defaults)
if __name__ == "__main__":
main()