{{ message }}
-
Notifications
You must be signed in to change notification settings - Fork 5
Expand file tree
/
Copy pathconvert.py
More file actions
564 lines (500 loc) · 21.3 KB
/
Copy pathconvert.py
File metadata and controls
564 lines (500 loc) · 21.3 KB
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
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
"""Utilities for converting input files to Python `Project`s."""
import warnings
from collections.abc import Iterable
from os import PathLike
from pathlib import Path
from numpy import array, empty
from scipy.io.matlab import MatlabOpaque, loadmat
from ratapi import Project, wrappers
from ratapi.classlist import ClassList
from ratapi.models import Background, Contrast, CustomFile, Data, Layer, Parameter, Resolution
from ratapi.utils.enums import Geometries, Languages, LayerModels
def r1_to_project(filename: str | PathLike) -> Project:
"""Read a RasCAL1 project struct as a Python `Project`.
Parameters
----------
filename : str, PathLike
The path to a .mat file containing project data.
Returns
-------
Project
A RAT `Project` equivalent to the RasCAL1 project struct.
"""
mat_project = loadmat(str(filename), simplify_cells=True)["problem"]
mat_module = mat_project["module"]
if mat_module["experiment_type"] == "Air / Liquid (or solid)":
geom = Geometries.AirSubstrate
else:
geom = Geometries.SubstrateLiquid
# R1 uses a different name for custom xy layer model
layer_model = mat_module["type"]
if layer_model.lower() == "custom xy profile":
layer_model = LayerModels.CustomXY
layer_model = LayerModels(layer_model)
def zip_if_several(*params) -> tuple | list[tuple]:
"""Zips parameters if necessary, but can handle single-item parameters.
Examples
--------
zip_if_several([1, 2], [3, 4]) = [(1, 3), (2, 4)]
zip_if_several(1, 2, 3) = [(1, 2, 3)]
Parameters
----------
*params
Any number of parameters.
Returns
-------
tuple or list of tuple
If any parameter is a single item, returns a list just containing the tuple of parameters.
Otherwise, returns the same as zip(*params).
"""
if all(isinstance(param, Iterable) and not isinstance(param, str) for param in params):
return zip(*params, strict=False)
return [params]
def read_param(names, constrs, values, fits):
"""Read in a parameter list from the relevant keys, and fix constraints for non-fit parameters.
Parameters
----------
names, constrs, values, fits : str
The keys for names, constraints, values
and whether to fit for a type of parameter.
Returns
-------
ClassList
A list of all relevant parameters.
"""
def fix_invalid_constraints(name: str, constrs: tuple[float, float], value: float) -> tuple[float, float]:
"""Check that constraints are valid and fix them if they aren't.
RasCAL-1 allowed the constraints of non-fit parameters to be invalid, which means
we need to fix them here so that the project is valid.
Parameters
----------
name: str
The name of the parameter.
constrs : tuple[float, float]
The constraints of the parameter (min and max, respectively)
value : float
The value of the parameter.
Returns
-------
tuple[float, float]
The adjusted constraints (identical to constrs if constraints were valid)
"""
new_constrs = (min(constrs[0], value), max(constrs[1], value))
if new_constrs[0] != constrs[0] or new_constrs[1] != constrs[1]:
warnings.warn(
f"The parameter {name} has invalid constraints,"
" these have been adjusted to satisfy the current value of the parameter.",
stacklevel=2,
)
return new_constrs
# adjust invalid constraints
# if just one item in the classlist, these objects won't be in lists
if not isinstance(fit := mat_project[fits], Iterable):
if not fit:
mat_project[constrs] = fix_invalid_constraints(
mat_project[names], mat_project[constrs], mat_project[values]
)
# else they will be iterable
else:
for i, fit in enumerate(mat_project[fits]):
if not fit:
mat_project[constrs][i] = fix_invalid_constraints(
mat_project[names][i], mat_project[constrs][i], mat_project[values][i]
)
return ClassList(
[
Parameter(
name=name,
min=constr[0],
value=val,
max=constr[1],
fit=fitbool,
)
for name, constr, val, fitbool in zip_if_several(
mat_project[names],
mat_project[constrs],
mat_project[values],
mat_project[fits],
)
]
)
# we add these as new attributes of the mat project dict so we can feed them into read_param better
if mat_project["numberOfBacks"] == 1:
mat_project["back_param_names"] = "Background parameter 1"
else:
mat_project["back_param_names"] = [
f"Background parameter {i}" for i in range(1, mat_project["numberOfBacks"] + 1)
]
# sometimes numberOfResolutions isn't defined: in all these cases there's only one resolution
# maybe from before multiple resolutions were possible?
if getattr(mat_project, "numberOfResolutions", 1) == 1:
mat_project["res_param_names"] = "Resolution parameter 1"
else:
mat_project["res_param_names"] = [
f"Resolution parameter {i}" for i in range(1, mat_project["numberOfBacks"] + 1)
]
params = read_param("paramnames", "constr", "params", "fityesno")
back_params = read_param("back_param_names", "backs_constr", "backs", "backgrounds_fityesno")
res_params = read_param("res_param_names", "resolution_constr", "resolution", "resolution_fityesno")
bulk_ins = read_param("nbaNames", "nbairs_constr", "nba", "nbairs_fityesno")
bulk_outs = read_param("nbsNames", "nbsubs_constr", "nbs", "nbsubs_fityesno")
scale_facs = read_param("scalesNames", "scale_constr", "scalefac", "scalefac_fityesno")
# if just one background, backsNames and back_param_names are strings; fix that here
# and mutatis mutandis for resolution
if isinstance(mat_project["back_param_names"], str):
mat_project["back_param_names"] = [mat_project["back_param_names"]]
if isinstance(mat_project["backsNames"], str):
mat_project["backsNames"] = [mat_project["backsNames"]]
if isinstance(mat_project["res_param_names"], str):
mat_project["res_param_names"] = [mat_project["res_param_names"]]
if isinstance(mat_project["resolNames"], str):
mat_project["resolNames"] = [mat_project["resolNames"]]
# create backgrounds and resolutions from parameters
backs = ClassList(
[
Background(name=back_name, type="constant", source=mat_project["back_param_names"][i])
for i, back_name in enumerate(mat_project["backsNames"])
]
)
res = ClassList(
[
Resolution(name=res_name, type="constant", source=mat_project["res_param_names"][i])
for i, res_name in enumerate(mat_project["resolNames"])
]
)
data = ClassList(
[
Data(
name=Path(name).stem,
data=data,
data_range=data_range,
simulation_range=sim_range,
)
for name, data, data_range, sim_range in zip_if_several(
mat_project["contrastFiles"],
mat_project["data"],
mat_project["dataLimits"],
mat_project["simLimits"],
)
]
)
# contrast names may be java strings (unsure why, maybe GUI input?): convert to Python str
# the java string is presented in Python as a MatlabOpaque object in a 1-item array (hence index [0])
# which are given as a 1-item array with 4 entries. the fourth is the actual data (index [3]),
# which is given as the byte data of a Java string; this consists of 7 metadata bytes (ignored)
# and then the actual string characters (index [7:]) in ascii format (.decode("ascii"))
if len(mat_project["contrastNames"]) == 1 and isinstance(mat_project["contrastNames"], MatlabOpaque):
mat_project["contrastNames"] = bytes(mat_project["contrastNames"][0][3][7:]).decode("ascii")
else:
for i, contrast_name in enumerate(mat_project["contrastNames"]):
if isinstance(contrast_name, MatlabOpaque):
mat_project["contrastNames"][i] = bytes(contrast_name[0][3][7:]).decode("ascii")
# if just one contrast, resolNames is a string; fix that here
if isinstance(mat_project["resolNames"], str):
mat_project["resolNames"] = [mat_project["resolNames"]]
contrasts = ClassList(
[
Contrast(
name=name,
background=backs[int(back) - 1].name,
resolution=mat_project["resolNames"][int(res) - 1],
scalefactor=scale_facs[int(scale) - 1].name,
bulk_in=bulk_ins[int(bulk_in) - 1].name,
bulk_out=bulk_outs[int(bulk_out) - 1].name,
data=data[i].name,
)
for i, (name, back, res, scale, bulk_in, bulk_out) in enumerate(
zip_if_several(
mat_project["contrastNames"],
mat_project["contrastBacks"],
mat_project["contrastResolutions"],
mat_project["contrastScales"],
mat_project["contrastNbas"],
mat_project["contrastNbss"],
)
)
]
)
# set model for each contrast and add custom files
if layer_model == LayerModels.StandardLayers:
custom_file = ClassList()
layers = ClassList(
[
Layer(
name=name,
thickness=params[int(thickness) - 1].name,
SLD=params[int(sld) - 1].name,
roughness=params[int(roughness) - 1].name,
# if hydration is not set, it is an empty numpy array, else it is a string representing a number
hydration=params[int(hydration) - 1].name if getattr(hydration, "size", 1) > 0 else "",
hydrate_with=hydrate_with,
)
# R1 layers are 6-item arrays, unpack into a Layer object
for thickness, sld, roughness, hydration, name, hydrate_with in mat_project["layersDetails"]
]
)
for i, contrast in enumerate(contrasts):
# if there is only one layer, contrastsNumberOfLayers is an int; otherwise it is a list
if (
isinstance(mat_project["contrastsNumberOfLayers"], int)
and mat_project["contrastsNumberOfLayers"] == 0
or isinstance(mat_project["contrastsNumberOfLayers"], list)
and mat_project["contrastsNumberOfLayers"][i] == 0
):
continue
# contrastLayers is not an array, but rather a string with commas between entries
contrast_layers = mat_project["contrastLayers"][i].split(",")
contrast_layers = [
int(x) - 1 for x in contrast_layers if x != ""
] # remove empty string from hanging commas
contrast.model = [layers[i].name for i in contrast_layers]
else:
custom_filepath = mat_module["name"]
if Path(custom_filepath).suffix != ".m":
custom_filepath += ".m"
model_name = Path(custom_filepath).stem
# Assume the custom file is in the same directory as the mat file
custom_file = ClassList(
[
CustomFile(
name=model_name, filename=custom_filepath, language=Languages.Matlab, path=Path(filename).parent
)
]
)
layers = ClassList()
for contrast in contrasts:
contrast.model = [model_name]
project = Project(
name=mat_project.get("name", ""),
model=layer_model,
geometry=geom,
parameters=params,
backgrounds=backs,
background_parameters=back_params,
resolutions=res,
resolution_parameters=res_params,
bulk_in=bulk_ins,
bulk_out=bulk_outs,
scalefactors=scale_facs,
data=data,
layers=layers,
contrasts=contrasts,
custom_files=custom_file,
)
return project
def project_to_r1(
project: Project, filename: str | PathLike = "RAT_project", return_struct: bool = False
) -> dict | None:
"""Convert a RAT Project to a RasCAL1 project struct.
Parameters
----------
project : Project
The RAT Project to convert.
filename : str or PathLike, default "RAT_project"
If given, saves as a .mat file with the given filename.
return_struct : bool, default False
If True, do not save and instead return the R1 struct.
Returns
-------
dict or None
If `return_struct` is True, return the r1 struct. Else, return nothing.
"""
def convert_parameters(
params: ClassList[Parameter], name: str, value: str, constr: str, fit: str, number: str = ""
):
"""Convert a list of parameters to r1 data fields.
Parameters
----------
params: ClassList
A list of parameter type from the Project.
name, constr, value, fit : str
The keys for names, constraints, values
and whether to fit for a type of parameter.
number : str, optional, default ""
Key for the length of the parameter list if not blank.
Returns
-------
dict
A dict of the relevant struct fields.
"""
output = {
name: [p.name for p in params],
value: [p.value for p in params],
constr: [[p.min, p.max] for p in params],
fit: [int(p.fit) for p in params],
}
if number:
output[number] = len(params)
return output
# translate RAT geometries into R1 experiment types
r1_geoms_dict = {Geometries.AirSubstrate: "Air / Liquid (or solid)", Geometries.SubstrateLiquid: "Solid / Liquid"}
r1 = {
# set name, type, experiment type
"name": project.name,
"module": {
"type": str(project.model),
"experiment_type": r1_geoms_dict[project.geometry],
},
}
# parameter names, values, constraints, fits
r1.update(
convert_parameters(
project.parameters,
"paramnames",
"params",
"constr",
"fityesno",
)
)
# scalefactors names, values, constraints, fit, and number
r1.update(
convert_parameters(
project.scalefactors,
"scalesNames",
"scalefac",
"scale_constr",
"scalefac_fityesno",
"numberOfScales",
)
)
# bulk in names, values, constraints, fit, and number
r1.update(
convert_parameters(
project.bulk_in,
"nbaNames",
"nba",
"nbairs_constr",
"nbairs_fityesno",
"numberOfNbas",
)
)
# bulk out names, values, constraints, fit, and number
r1.update(
convert_parameters(
project.bulk_out,
"nbsNames",
"nbs",
"nbsubs_constr",
"nbsubs_fityesno",
"numberOfNbss",
)
)
shifts = {
"numberOfShifts": 1,
"shiftsNames": "Shift 1",
"shifts_horisontal": 0,
"shifts_fityesno": 0,
"shifts_constr": [-1e-4, 1e-4],
}
r1.update(shifts)
resolutions = {
"resolNames": [r.name for r in project.resolutions],
"resolution": [project.resolution_parameters[r.source].value for r in project.resolutions],
"resolution_constr": [
[project.resolution_parameters[r.source].min, project.resolution_parameters[r.source].max]
for r in project.resolutions
],
"resolution_fityesno": [int(project.resolution_parameters[r.source].fit) for r in project.resolutions],
"numberOfResolutions": len(project.resolutions),
}
r1.update(resolutions)
backgrounds = {
"backsNames": [b.name for b in project.backgrounds],
"backs": [project.background_parameters[b.source].value for b in project.backgrounds],
"backs_constr": [
[project.background_parameters[b.source].min, project.background_parameters[b.source].max]
for b in project.backgrounds
],
"backgrounds_fityesno": [int(project.background_parameters[b.source].fit) for b in project.backgrounds],
"numberOfBacks": len(project.backgrounds),
}
r1.update(backgrounds)
if project.model == LayerModels.StandardLayers:
layer_info = {
"numberOfLayers": len(project.layers),
"layersDetails": [
[
project.parameters.index(layer.thickness, True),
project.parameters.index(layer.SLD, True),
project.parameters.index(layer.roughness, True),
project.parameters.index(layer.hydration, True) if layer.hydration else empty(shape=(0, 0)),
layer.name,
str(layer.hydrate_with),
]
for layer in project.layers
],
}
r1["module"]["name"] = ""
else:
layer_info = {"numberOfLayers": 0, "layersDetails": []}
# note R1 only supports one custom file!
r1["module"]["name"] = project.custom_files[0].name
r1.update(layer_info)
contrasts = {
"contrastNames": [c.name for c in project.contrasts],
"contrastNbas": [project.bulk_in.index(c.bulk_in, True) for c in project.contrasts],
"contrastNbss": [project.bulk_out.index(c.bulk_out, True) for c in project.contrasts],
"contrastScales": [project.scalefactors.index(c.scalefactor, True) for c in project.contrasts],
"data": [project.data[c.data].data for c in project.contrasts],
"simLimits": [project.data[c.data].simulation_range for c in project.contrasts],
"dataLimits": [project.data[c.data].data_range for c in project.contrasts],
"fitlowrange": [project.data[c.data].data_range[0] for c in project.contrasts],
"fithirange": [project.data[c.data].data_range[1] for c in project.contrasts],
"contrastRepeatSLDs": [[0, 1] for _ in project.contrasts],
"contrastFiles": [project.data[c.data].name for c in project.contrasts],
# some of the data is a bit complex for a (readable) list comp; create empty lists and append below
"contrastResolutions": [],
"contrastBacks": [],
"dataPresent": [],
"include_data": [],
"dataTypes": [],
"contrastLayers": [],
"contrastsNumberOfLayers": [],
}
for contrast in project.contrasts:
# R1 stores contrast resolutions and background by the index of the relevant parameter
resolution = project.resolutions[contrast.resolution]
contrasts["contrastResolutions"].append(project.resolution_parameters.index(resolution.source, True))
background = project.backgrounds[contrast.background]
contrasts["contrastBacks"].append(project.background_parameters.index(background.source, True))
data = project.data[contrast.data]
if "simulation" in data.name:
contrasts["dataPresent"].append(0)
contrasts["include_data"].append(0)
contrasts["dataTypes"].append("Simulation")
else:
contrasts["dataPresent"].append(1)
contrasts["include_data"].append(1)
contrasts["dataTypes"].append("Ascii File")
if project.model == LayerModels.StandardLayers:
model = contrast.model
contrasts["contrastsNumberOfLayers"].append(len(model))
contrasts["contrastLayers"].append(",".join(str(project.layers.index(layer) + 1) for layer in model))
else:
contrasts["contrastsNumberOfLayers"].append(0)
contrasts["contrastLayers"].append("")
r1.update(contrasts)
# some final processing:
# .mat files just contain the item for any single-item list, so process and fix that
# also, `savemat` will only write cells instead of matrices for object-type ndarrays. convert lists to those
for key, value in r1.items():
if isinstance(value, list):
if len(value) == 1:
r1[key] = value[0]
else:
if not all(isinstance(x, type(r1[key][0])) for x in r1[key]):
r1[key] = array(value, dtype="object")
if return_struct:
return r1
if Path(filename).suffix != ".mat":
filename += ".mat"
# scipy.io.savemat doesn't do cells properly:
# https://github.com/scipy/scipy/issues/3756
# rather than fiddling we just use matlab
loader = wrappers.MatlabWrapper.loader
if loader is None:
raise ImportError("matlabengine is not installed.")
eng = loader.result()
eng.workspace["problem"] = r1
eng.save(str(filename), "problem", nargout=0)
return None
You can’t perform that action at this time.