/
raster.py
412 lines (335 loc) · 15.5 KB
/
raster.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
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
import copy
from itertools import product
import numpy as np
from matplotlib import pyplot as plt
import param
from ...core import CompositeOverlay, Element
from ...core import traversal
from ...core.util import match_spec, max_range, unique_iterator
from ...element.raster import Image, Raster, RGB
from .element import ColorbarPlot, OverlayPlot
from .plot import MPLPlot, GridPlot
class RasterPlot(ColorbarPlot):
aspect = param.Parameter(default='equal', doc="""
Raster elements respect the aspect ratio of the
Images by default but may be set to an explicit
aspect ratio or to 'square'.""")
colorbar = param.Boolean(default=False, doc="""
Whether to add a colorbar to the plot.""")
situate_axes = param.Boolean(default=False, doc="""
Whether to situate the image relative to other plots. """)
style_opts = ['alpha', 'cmap', 'interpolation', 'visible',
'filterrad', 'clims', 'norm']
_plot_methods = dict(single='imshow')
def __init__(self, *args, **kwargs):
super(RasterPlot, self).__init__(*args, **kwargs)
if self.hmap.type == Raster:
self.invert_yaxis = not self.invert_yaxis
def get_extents(self, element, ranges):
extents = super(RasterPlot, self).get_extents(element, ranges)
if self.situate_axes:
return extents
else:
if isinstance(element, Image):
return element.bounds.lbrt()
else:
return element.extents
def _compute_ticks(self, element, ranges):
return None, None
def get_data(self, element, ranges, style):
xticks, yticks = self._compute_ticks(element, ranges)
if element.depth != 1:
style.pop('cmap', None)
data = element.data
if isinstance(element, Image):
l, b, r, t = element.bounds.lbrt()
else:
l, b, r, t = element.extents
if self.invert_yaxis and type(element) is Raster:
b, t = t, b
if isinstance(element, RGB):
data = element.rgb.data
vdim = element.vdims[0]
self._norm_kwargs(element, ranges, style, vdim)
style['extent'] = [l, r, b, t]
return [data], style, {'xticks': xticks, 'yticks': yticks}
def update_handles(self, key, axis, element, ranges, style):
im = self.handles['artist']
data, style, axis_kwargs = self.get_data(element, ranges, style)
l, r, b, t = style['extent']
im.set_data(data[0])
im.set_extent((l, r, b, t))
im.set_clim((style['vmin'], style['vmax']))
if 'norm' in style:
im.norm = style['norm']
return axis_kwargs
class HeatMapPlot(RasterPlot):
show_values = param.Boolean(default=False, doc="""
Whether to annotate each pixel with its value.""")
def _annotate_plot(self, ax, annotations):
handles = {}
for plot_coord, text in annotations.items():
handles[plot_coord] = ax.annotate(text, xy=plot_coord,
xycoords='axes fraction',
horizontalalignment='center',
verticalalignment='center')
return handles
def _annotate_values(self, element):
val_dim = element.vdims[0]
vals = np.rot90(element.raster, 3).flatten()
d1uniq, d2uniq = [element.dimension_values(i, False) for i in range(2)]
num_x, num_y = len(d1uniq), len(d2uniq)
xstep, ystep = 1.0/num_x, 1.0/num_y
xpos = np.linspace(xstep/2., 1.0-xstep/2., num_x)
ypos = np.linspace(ystep/2., 1.0-ystep/2., num_y)
plot_coords = product(xpos, ypos)
annotations = {}
for plot_coord, v in zip(plot_coords, vals):
text = val_dim.pprint_value(v)
text = '' if v is np.nan else text
annotations[plot_coord] = text
return annotations
def _compute_ticks(self, element, ranges):
xdim, ydim = element.kdims
dim1_keys, dim2_keys = [element.dimension_values(i, False)
for i in range(2)]
num_x, num_y = len(dim1_keys), len(dim2_keys)
x0, y0, x1, y1 = element.extents
xstep, ystep = ((x1-x0)/num_x, (y1-y0)/num_y)
xpos = np.linspace(x0+xstep/2., x1-xstep/2., num_x)
ypos = np.linspace(y0+ystep/2., y1-ystep/2., num_y)
xlabels = [xdim.pprint_value(k) for k in dim1_keys]
ylabels = [ydim.pprint_value(k) for k in dim2_keys]
return list(zip(xpos, xlabels)), list(zip(ypos, ylabels))
def init_artists(self, ax, plot_args, plot_kwargs):
l, r, b, t = plot_kwargs['extent']
ax.set_aspect(float(r - l)/(t-b))
handles = {}
annotations = plot_kwargs.pop('annotations', None)
handles['artist'] = ax.imshow(*plot_args, **plot_kwargs)
if self.show_values and annotations:
handles['annotations'] = self._annotate_plot(ax, annotations)
return handles
def get_data(self, element, ranges, style):
_, style, axis_kwargs = super(HeatMapPlot, self).get_data(element, ranges, style)
data = element.raster
data = np.ma.array(data, mask=np.logical_not(np.isfinite(data)))
cmap_name = style.pop('cmap', None)
cmap = copy.copy(plt.cm.get_cmap('gray' if cmap_name is None else cmap_name))
cmap.set_bad('w', 1.)
style['cmap'] = cmap
style['annotations'] = self._annotate_values(element)
return [data], style, axis_kwargs
def update_handles(self, key, axis, element, ranges, style):
im = self.handles['artist']
data, style, axis_kwargs = self.get_data(element, ranges, style)
l, r, b, t = style['extent']
im.set_data(data[0])
im.set_extent((l, r, b, t))
im.set_clim((style['vmin'], style['vmax']))
if 'norm' in style:
im.norm = style['norm']
if self.show_values:
annotations = self.handles['annotations']
for annotation in annotations.values():
try:
annotation.remove()
except:
pass
annotations = self._annotate_plot(axis, style['annotations'])
self.handles['annotations'] = annotations
return axis_kwargs
class ImagePlot(RasterPlot):
def get_data(self, element, ranges, style):
data = np.flipud(element.dimension_values(2, flat=False))
data = np.ma.array(data, mask=np.logical_not(np.isfinite(data)))
vdim = element.vdims[0]
self._norm_kwargs(element, ranges, style, vdim)
l, b, r, t = element.bounds.lbrt()
style['extent'] = [l, r, b, t]
return (data,), style, {}
def get_extents(self, element, ranges):
extents = super(ImagePlot, self).get_extents(element, ranges)
if self.situate_axes:
return extents
else:
return element.bounds.lbrt()
class QuadMeshPlot(ColorbarPlot):
style_opts = ['alpha', 'cmap', 'clim', 'edgecolors', 'norm', 'shading',
'linestyles', 'linewidths', 'hatch', 'visible']
_plot_methods = dict(single='pcolormesh')
def get_data(self, element, ranges, style):
data = np.ma.array(element.data[2],
mask=np.logical_not(np.isfinite(element.data[2])))
cmesh_data = list(element.data[:2]) + [data]
style['locs'] = np.concatenate(element.data[:2])
vdim = element.vdims[0]
self._norm_kwargs(element, ranges, style, vdim)
return tuple(cmesh_data), style, {}
def init_artists(self, ax, plot_args, plot_kwargs):
locs = plot_kwargs.pop('locs')
artist = ax.pcolormesh(*plot_args, **plot_kwargs)
return {'artist': artist, 'locs': locs}
def update_handles(self, key, axis, element, ranges, style):
cmesh = self.handles['artist']
locs = np.concatenate(element.data[:2])
if (locs != self.handles['locs']).any():
return super(QuadMeshPlot, self).update_handles(key, axis, element,
ranges, style)
else:
data, style, axis_kwargs = self.get_data(element, ranges, style)
cmesh.set_array(data[-1])
cmesh.set_clim((style['vmin'], style['vmax']))
if 'norm' in style:
cmesh.norm = style['norm']
return axis_kwargs
class RasterGridPlot(GridPlot, OverlayPlot):
"""
RasterGridPlot evenly spaces out plots of individual projections on
a grid, even when they differ in size. Since this class uses a single
axis to generate all the individual plots it is much faster than the
equivalent using subplots.
"""
# Parameters inherited from OverlayPlot that are not part of the
# GridPlot interface. Some of these may be enabled in future in
# conjunction with GridPlot.
apply_extents = param.Parameter(precedence=-1)
apply_ranges = param.Parameter(precedence=-1)
apply_ticks = param.Parameter(precedence=-1)
batched = param.Parameter(precedence=-1)
bgcolor = param.Parameter(precedence=-1)
invert_axes = param.Parameter(precedence=-1)
invert_xaxis = param.Parameter(precedence=-1)
invert_yaxis = param.Parameter(precedence=-1)
invert_zaxis = param.Parameter(precedence=-1)
labelled = param.Parameter(precedence=-1)
legend_cols = param.Parameter(precedence=-1)
legend_position = param.Parameter(precedence=-1)
legend_limit = param.Parameter(precedence=-1)
logx = param.Parameter(precedence=-1)
logy = param.Parameter(precedence=-1)
logz = param.Parameter(precedence=-1)
show_grid = param.Parameter(precedence=-1)
style_grouping = param.Parameter(precedence=-1)
xticks = param.Parameter(precedence=-1)
yticks = param.Parameter(precedence=-1)
zticks = param.Parameter(precedence=-1)
zaxis = param.Parameter(precedence=-1)
zrotation = param.Parameter(precedence=-1)
def __init__(self, layout, keys=None, dimensions=None, create_axes=False, ranges=None,
layout_num=1, **params):
if not keys or not dimensions:
dimensions, keys = traversal.unique_dimkeys(layout)
MPLPlot.__init__(self, dimensions=dimensions, keys=keys, **params)
self.layout = layout
self.cyclic_index = 0
self.zorder = 0
self.layout_num = layout_num
self.overlaid = False
self.hmap = {}
if layout.ndims > 1:
xkeys, ykeys = zip(*layout.data.keys())
else:
xkeys = layout.keys()
ykeys = [None]
self._xkeys = sorted(set(xkeys))
self._ykeys = sorted(set(ykeys))
self._xticks, self._yticks = [], []
self.rows, self.cols = layout.shape
self.fig_inches = self._get_size()
_, _, self.layout = self._create_subplots(layout, None, ranges, create_axes=False)
self.border_extents = self._compute_borders()
width, height, _, _, _, _ = self.border_extents
if self.aspect == 'equal':
self.aspect = float(width/height)
def _finalize_artist(self, key):
pass
def get_extents(self, view, ranges):
width, height, _, _, _, _ = self.border_extents
return (0, 0, width, height)
def _get_frame(self, key):
return GridPlot._get_frame(self, key)
def initialize_plot(self, ranges=None):
_, _, b_w, b_h, widths, heights = self.border_extents
key = self.keys[-1]
ranges = self.compute_ranges(self.layout, key, ranges)
self.handles['projs'] = {}
x, y = b_w, b_h
for xidx, xkey in enumerate(self._xkeys):
w = widths[xidx]
for yidx, ykey in enumerate(self._ykeys):
h = heights[yidx]
if self.layout.ndims > 1:
vmap = self.layout.get((xkey, ykey), None)
else:
vmap = self.layout.get(xkey, None)
pane = vmap.select(**{d.name: val for d, val in zip(self.dimensions, key)
if d in vmap.kdims})
if pane:
if issubclass(vmap.type, CompositeOverlay): pane = pane.values()[-1]
data = pane.data if pane else None
else:
pane = vmap.last.values()[-1] if issubclass(vmap.type, CompositeOverlay) else vmap.last
data = pane.data
ranges = self.compute_ranges(vmap, key, ranges)
opts = self.lookup_options(pane, 'style')[self.cyclic_index]
plot = self.handles['axis'].imshow(data, extent=(x,x+w, y, y+h), **opts)
cdim = pane.vdims[0].name
valrange = match_spec(pane, ranges).get(cdim, pane.range(cdim))
plot.set_clim(valrange)
if data is None:
plot.set_visible(False)
self.handles['projs'][(xkey, ykey)] = plot
y += h + b_h
if xidx == 0:
self._yticks.append(y-b_h-h/2.)
y = b_h
x += w + b_w
self._xticks.append(x-b_w-w/2.)
kwargs = self._get_axis_kwargs()
return self._finalize_axis(key, ranges=ranges, **kwargs)
def update_frame(self, key, ranges=None):
grid = self._get_frame(key)
ranges = self.compute_ranges(self.layout, key, ranges)
for xkey in self._xkeys:
for ykey in self._ykeys:
plot = self.handles['projs'][(xkey, ykey)]
grid_key = (xkey, ykey) if self.layout.ndims > 1 else (xkey,)
element = grid.data.get(grid_key, None)
if element:
plot.set_visible(True)
data = element.values()[0].data if isinstance(element, CompositeOverlay) else element.data
plot.set_data(data)
else:
plot.set_visible(False)
kwargs = self._get_axis_kwargs()
return self._finalize_axis(key, ranges=ranges, **kwargs)
def _get_axis_kwargs(self):
xdim = self.layout.kdims[0]
ydim = self.layout.kdims[1] if self.layout.ndims > 1 else None
xticks = (self._xticks, [xdim.pprint_value(l) for l in self._xkeys])
yticks = (self._yticks, [ydim.pprint_value(l) if ydim else ''
for l in self._ykeys])
return dict(xlabel=xdim.pprint_label, ylabel=ydim.pprint_label if ydim else '',
xticks=xticks, yticks=yticks)
def _compute_borders(self):
ndims = self.layout.ndims
width_fn = lambda x: x.range(0)
height_fn = lambda x: x.range(1)
width_extents = [max_range(self.layout[x, :].traverse(width_fn, [Element]))
for x in unique_iterator(self.layout.dimension_values(0))]
if ndims > 1:
height_extents = [max_range(self.layout[:, y].traverse(height_fn, [Element]))
for y in unique_iterator(self.layout.dimension_values(1))]
else:
height_extents = [max_range(self.layout.traverse(height_fn, [Element]))]
widths = [extent[0]-extent[1] for extent in width_extents]
heights = [extent[0]-extent[1] for extent in height_extents]
width, height = np.sum(widths), np.sum(heights)
border_width = (width*self.padding)/(len(widths)+1)
border_height = (height*self.padding)/(len(heights)+1)
width += width*self.padding
height += height*self.padding
return width, height, border_width, border_height, widths, heights
def __len__(self):
return max([len(self.keys), 1])