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 | class DatasetBuilder:
"""Manage data structure, slicing, and mesh creation for a target N-D dataset."""
def __init__(
self,
dataset: str = None,
server: Any = None,
viewer: bool = False,
catalogs: List[str] = [],
) -> None:
"""Create an instance of the DatasetBuilder class.
Parameters:
dataset: A path or URL referencing a dataset readable by xarray.open_dataset()
server: Trame server name or instance.
catalogs: A list of strings referencing available catalog modules (options include 'pangeo', 'esgf'). Each included catalog will be available to search in the Viewer UI.
"""
self._algorithm = PyVistaXarraySource()
self._viewer = None
self._dataset = None
self._dataset_info = None
self._da_name = None
self._server = server
self._catalogs = catalogs
if viewer:
# Access to instantiate
self.viewer
if dataset:
self.dataset_info = {
"source": "default",
"id": dataset,
}
# -----------------------------------------------------
# Properties
# -----------------------------------------------------
@property
def viewer(self):
"""Return the Pan3D DatasetViewer instance for this DatasetBuilder.
If none exists, create a new one and synchronize state.
"""
from pan3d.dataset_viewer import DatasetViewer
if self._viewer is None:
self._viewer = DatasetViewer(
builder=self,
server=self._server,
catalogs=self._catalogs,
state=dict(
dataset_info=self.dataset_info,
da_active=self.data_array_name,
da_x=self.x,
da_y=self.y,
da_z=self.z,
da_t=self.t,
da_t_index=self.t_index,
),
)
return self._viewer
@property
def dataset_info(self) -> Optional[Dict]:
"""A dictionary referencing the current dataset.
This dictionary should adhere to the following schema:
| Key | Required? | Default | Type | Value Description |
|-----|-----------|---------|------|-------------------|
| `id` | Yes | | string | A unique identifier that will be used to load the dataset
|`source`| No | "default" | string | Name of a module to load the dataset (options: "default", "xarray", "pangeo", "esgf")
With the default source, the id value must be readable with xarray.open_dataset().
"""
return self._dataset_info
@dataset_info.setter
def dataset_info(self, dataset_info: Optional[Dict]) -> None:
if dataset_info is not None:
if not isinstance(dataset_info, dict):
raise TypeError("Type of dataset_info must be Dict or None.")
source = dataset_info.get("source")
id = dataset_info.get("id")
if not isinstance(id, str):
raise ValueError(
'Dataset info must contain key "id" with string value.'
)
if source is None:
dataset_info["source"] = "default"
elif source not in ["default", "xarray", "pangeo", "esgf"]:
raise ValueError(
"Invalid source value. Must be one of [default, xarray, pangeo, esgf]."
)
if dataset_info != self._dataset_info:
self._dataset_info = dataset_info
self._set_state_values(dataset_info=dataset_info)
self._load_dataset(dataset_info)
@property
def dataset(self) -> Optional[xarray.Dataset]:
"""Xarray.Dataset object read from the current dataset_info."""
return self._dataset
@dataset.setter
def dataset(self, dataset: Optional[xarray.Dataset]) -> None:
if dataset is not None and not isinstance(dataset, xarray.Dataset):
raise TypeError("Type of dataset must be xarray.Dataset or None.")
self._dataset = dataset
if dataset is not None:
vars = list(
k
for k in dataset.data_vars.keys()
if not k.endswith("_bnds") and not k.endswith("_bounds")
)
if len(vars) > 0:
self.data_array_name = vars[0]
else:
self.data_array_name = None
if self._viewer:
self._viewer._dataset_changed()
self._viewer._mesh_changed()
@property
def data_array_name(self) -> Optional[str]:
"""String name of an array that exists on the current dataset."""
return self._da_name
@data_array_name.setter
def data_array_name(self, data_array_name: Optional[str]) -> None:
if data_array_name is not None:
if not isinstance(data_array_name, str):
raise TypeError("Type of data_array_name must be str or None.")
if self.dataset is None:
raise ValueError(
"Cannot set data array name without setting dataset info first."
)
if data_array_name not in self.dataset.data_vars:
acceptable_values = list(self.dataset.data_vars.keys())
raise ValueError(
f"{data_array_name} does not exist on dataset. Must be one of {acceptable_values}."
)
if data_array_name != self._da_name:
self._da_name = data_array_name
self._set_state_values(da_active=data_array_name)
da = None
self.x = None
self.y = None
self.z = None
self.t = None
self.t_index = 0
if data_array_name is not None and self.dataset is not None:
da = self.dataset[data_array_name]
if len(da.indexes.variables.mapping) == 0:
da = da.assign_coords({d: range(s) for d, s in da.sizes.items()})
self._algorithm.data_array = da
if self._viewer:
self._viewer._data_array_changed()
self._viewer._mesh_changed()
self._auto_select_coordinates()
@property
def data_array(self) -> Optional[xarray.DataArray]:
"""Return the current Xarray data array with current slicing applied."""
return self._algorithm.sliced_data_array
@property
def data_range(self) -> Tuple[Any]:
"""Return the minimum and maximum of the current Xarray data array with current slicing applied."""
if self.dataset is None:
return None
return self._algorithm.data_range
@property
def x(self) -> Optional[str]:
"""String name of a coordinate that should be rendered on the X axis.
Value must exist in coordinates of current data array."""
return self._algorithm.x
@x.setter
def x(self, x: Optional[str]) -> None:
if x is not None:
if not isinstance(x, str):
raise TypeError("Type of x must be str or None.")
if self.data_array_name is None:
raise ValueError("Cannot set x without setting data array name first.")
acceptable_values = self.dataset[self.data_array_name].dims
if x not in acceptable_values:
raise ValueError(
f"{x} does not exist on data array. Must be one of {acceptable_values}."
)
if self._algorithm.x != x:
self._algorithm.x = x
self._set_state_values(da_x=x)
if self._viewer:
self._viewer._mesh_changed()
@property
def y(self) -> Optional[str]:
"""String name of a coordinate that should be rendered on the Y axis.
Value must exist in coordinates of current data array."""
return self._algorithm.y
@y.setter
def y(self, y: Optional[str]) -> None:
if y is not None:
if not isinstance(y, str):
raise TypeError("Type of y must be str or None.")
if self.data_array_name is None:
raise ValueError("Cannot set y without setting data array name first.")
acceptable_values = self.dataset[self.data_array_name].dims
if y not in acceptable_values:
raise ValueError(
f"{y} does not exist on data array. Must be one of {acceptable_values}."
)
if self._algorithm.y != y:
self._algorithm.y = y
self._set_state_values(da_y=y)
if self._viewer:
self._viewer._mesh_changed()
@property
def z(self) -> Optional[str]:
"""String name of a coordinate that should be rendered on the Z axis.
Value must exist in coordinates of current data array."""
return self._algorithm.z
@z.setter
def z(self, z: Optional[str]) -> None:
if z is not None:
if not isinstance(z, str):
raise TypeError("Type of z must be str or None.")
if self.data_array_name is None:
raise ValueError("Cannot set z without setting data array name first.")
acceptable_values = self.dataset[self.data_array_name].dims
if z not in acceptable_values:
raise ValueError(
f"{z} does not exist on data array. Must be one of {acceptable_values}."
)
if self._algorithm.z != z:
self._algorithm.z = z
self._set_state_values(da_z=z)
if self._viewer:
self._viewer._mesh_changed()
@property
def t(self) -> Optional[str]:
"""String name of a coordinate that represents time or some other fourth dimension.
Only one slice may be viewed at once.
Value must exist in coordinates of current data array."""
return self._algorithm.time
@t.setter
def t(self, t: Optional[str]) -> None:
if t is not None:
if not isinstance(t, str):
raise TypeError("Type of t must be str or None.")
if self.data_array_name is None:
raise ValueError("Cannot set t without setting data array name first.")
acceptable_values = self.dataset[self.data_array_name].dims
if t not in acceptable_values:
raise ValueError(
f"{t} does not exist on data array. Must be one of {acceptable_values}."
)
if self._algorithm.time != t:
self._algorithm.time = t
self._set_state_values(da_t=t)
if self._viewer:
self._viewer._time_index_changed()
self._viewer._mesh_changed()
@property
def t_index(self) -> int:
"""Integer representing the index of the current time slice."""
return self._algorithm.time_index
@t_index.setter
def t_index(self, t_index: int) -> None:
if not isinstance(t_index, int):
raise TypeError("Type of t_index must be int.")
if t_index < 0:
raise ValueError("Time index must be a positive integer.")
if t_index > 0:
if not self.t:
raise ValueError(
"Cannot set time index > 0 without setting t array first."
)
max_value = self.dataset[self.data_array_name].coords[self.t].size
if t_index >= max_value:
raise ValueError(
f"Time index must be less than size of t coordinate ({max_value})."
)
if self._algorithm.time_index != t_index:
self._algorithm.time_index = int(t_index)
self._set_state_values(da_t_index=t_index)
if self._viewer:
self._viewer._time_index_changed()
self._viewer._mesh_changed()
@property
def slicing(self) -> Dict[str, List]:
"""Dictionary mapping of coordinate names to slice arrays.
Each key should exist in the coordinates of the current data array.
Each value should be an array consisting of three
integers or floats representing start value, stop value, and step.
"""
return self._algorithm.slicing
@slicing.setter
def slicing(self, slicing: Dict[str, List]) -> None:
if slicing is not None:
if not isinstance(slicing, Dict):
raise TypeError("Type of slicing must be Dict or None.")
if self.data_array_name is None:
raise ValueError(
"Cannot set slicing without setting data array name first."
)
for key, value in slicing.items():
if not isinstance(key, str):
raise ValueError("Keys in slicing must be strings.")
if not isinstance(value, list) or len(value) != 3:
raise ValueError(
"Values in slicing must be lists of length 3 ([start, stop, step])."
)
acceptable_coords = self.dataset[self.data_array_name].coords
if key not in acceptable_coords:
raise ValueError(
f"Key {key} not found in data array. Must be one of {list(acceptable_coords.keys())}."
)
key_coord = acceptable_coords[key]
if value[2] > key_coord.size:
raise ValueError(
f"Value {value} not applicable for Key {key}. Step value must be <= {key_coord.size}."
)
self._algorithm.slicing = slicing
if self._viewer:
self._viewer._data_slicing_changed()
self._viewer._mesh_changed()
@property
def mesh(
self,
) -> Union[pyvista.core.grid.RectilinearGrid, pyvista.StructuredGrid]:
"""Returns the PyVista Mesh derived from the current data array."""
if self.data_array is None:
return None
return self._algorithm.mesh
# -----------------------------------------------------
# Internal methods
# -----------------------------------------------------
def _load_dataset(self, dataset_info):
ds = None
if dataset_info is not None:
source = dataset_info.get("source")
if source in ["pangeo", "esgf"]:
ds = pan3d_catalogs.load_dataset(source, id=dataset_info["id"])
elif source == "xarray":
ds = xarray.tutorial.load_dataset(dataset_info["id"])
else:
ds = self._load_dataset_default(dataset_info)
if ds is not None:
self.dataset = ds
def _load_dataset_default(self, dataset_info):
# Assume 'id' in dataset_info is a path or url
if "https://" in dataset_info["id"] or os.path.exists(dataset_info["id"]):
engine = None
if ".zarr" in dataset_info["id"]:
engine = "zarr"
if ".nc" in dataset_info["id"]:
engine = "netcdf4"
ds = xarray.open_dataset(dataset_info["id"], engine=engine, chunks={})
return ds
else:
raise ValueError(f'Could not find dataset at {dataset_info["id"]}')
def _set_state_values(self, **kwargs):
if self._viewer is not None:
for k, v in kwargs.items():
if self._viewer.state[k] != v:
self._viewer.state[k] = v
def _auto_select_coordinates(self) -> None:
"""Automatically assign available coordinates to available axes.
Automatic assignment is done according to the following expected coordinate names:\n
X: "x" | "i" | "lon" | "len"\n
Y: "y" | "j" | "lat" | "width"\n
Z: "z" | "k" | "depth" | "height"\n
T: "t" | "time"
"""
if self.x or self.y or self.z or self.t:
# Some coordinates already assigned, don't auto-assign
return
if self.dataset is not None and self.data_array_name is not None:
da = self.dataset[self.data_array_name]
assigned_coords = []
# Prioritize assignment by known names
for coord_name in da.dims:
name = coord_name.lower()
for axis, accepted_names in coordinate_auto_selection.items():
# If accepted name is longer than one letter, look for contains match
name_match = [
accepted
for accepted in accepted_names
if (len(accepted) == 1 and accepted == name)
or (len(accepted) > 1 and accepted in name)
]
if len(name_match) > 0:
setattr(self, axis, coord_name)
assigned_coords.append(coord_name)
# Then assign any remaining by index
unassigned_axes = [
a for a in ["x", "y", "z", "t"] if getattr(self, a) is None
]
unassigned_coords = [d for d in da.dims if d not in assigned_coords]
for i, d in enumerate(unassigned_coords):
if i < len(unassigned_axes):
setattr(self, unassigned_axes[i], d)
# -----------------------------------------------------
# Config logic
# -----------------------------------------------------
def import_config(self, config_file: Union[str, Path, None]) -> None:
"""Import state from a JSON configuration file.
Parameters:
config_file: Can be a dictionary containing state information,
or a string or Path referring to a JSON file which contains state information.
For details, see Configuration Files documentation.
"""
if isinstance(config_file, dict):
config = config_file
elif isinstance(config_file, str):
path = Path(config_file)
if path.exists():
config = json.loads(path.read_text())
else:
config = json.loads(config_file)
origin_config = config.get("data_origin")
array_config = config.get("data_array")
if not origin_config or not array_config:
raise ValueError("Invalid format of import file.")
if isinstance(origin_config, str):
origin_config = {
"source": "default",
"id": origin_config,
}
self.dataset_info = origin_config
self.data_array_name = array_config.pop("name")
for key, value in array_config.items():
setattr(self, key, value)
self.slicing = config.get("data_slices")
if self._viewer:
ui_config = {f"ui_{k}": v for k, v in config.get("ui", {}).items()}
render_config = {
f"render_{k}": v for k, v in config.get("render", {}).items()
}
self._set_state_values(
**ui_config,
**render_config,
ui_action_name=None,
)
def export_config(self, config_file: Union[str, Path, None] = None) -> None:
"""Export the current state to a JSON configuration file.
Parameters:
config_file: Can be a string or Path representing the destination of the JSON configuration file.
If None, a dictionary containing the current configuration will be returned.
For details, see Configuration Files documentation.
"""
data_origin = self.dataset_info
if data_origin.get("source") == "default":
data_origin = data_origin.get("id")
config = {
"data_origin": data_origin,
"data_array": {
"name": self.data_array_name,
**{
key: getattr(self, key)
for key in ["x", "y", "z", "t", "t_index"]
if getattr(self, key) is not None
},
},
"data_slices": self.slicing,
}
if self._viewer:
state_items = list(self._viewer.state.to_dict().items())
config["ui"] = {
k.replace("ui_", ""): v
for k, v in state_items
if k.startswith("ui_")
and "action" not in k
and "loading" not in k
and "catalog" not in k
}
config["render"] = {
k.replace("render_", ""): v
for k, v in state_items
if k.startswith("render_") and "_options" not in k
}
if config_file:
Path(config_file).write_text(json.dumps(config))
return config
|