/
views.py
312 lines (260 loc) · 13.7 KB
/
views.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
# Create your views here.
from ga_ows.rendering.palettes import _Palette, LinearGradient, ColorBin, CatchAll, rgba
from ga_ows.views import wms
from osr import SpatialReference, CoordinateTransformation
import numpy as np
import cairo as cr
from datetime import datetime, timedelta
from logging import getLogger
import numexpr
from cera import query, models
log = getLogger(__name__)
def jet(mn, mx):
"""MATLAB jet colormap gradient spread from a min value to a max value"""
delta = (mx-mn) / 32.0
return _Palette(
ColorBin(rgba(1,1,1,0), mn-10, mn, include_right=True),
LinearGradient(rgba( 0, 0,143), rgba( 0, 0,175), mn + 0*delta, mn + 1*delta, include_left=False, include_right=False),
LinearGradient(rgba( 0, 0,175), rgba( 0, 0,207), mn + 1*delta, mn + 2*delta, include_right=False),
LinearGradient(rgba( 0, 0,207), rgba( 0, 0,239), mn + 2*delta, mn + 3*delta, include_right=False),
LinearGradient(rgba( 0, 0,239), rgba( 0, 16,255), mn + 3*delta, mn + 4*delta, include_right=False),
LinearGradient(rgba( 0, 16,255), rgba( 0, 48,255), mn + 4*delta, mn + 5*delta, include_right=False),
LinearGradient(rgba( 0, 48,255), rgba( 0, 80,255), mn + 5*delta, mn + 6*delta, include_right=False),
LinearGradient(rgba( 0, 80,255), rgba( 0,112,255), mn + 6*delta, mn + 7*delta, include_right=False),
LinearGradient(rgba( 0,112,255), rgba( 0,143,255), mn + 7*delta, mn + 8*delta, include_right=False),
LinearGradient(rgba( 0,143,255), rgba( 0,175,255), mn + 8*delta, mn + 9*delta, include_right=False),
LinearGradient(rgba( 0,175,255), rgba( 0,207,255), mn + 9*delta, mn + 10*delta, include_right=False),
LinearGradient(rgba( 0,207,255), rgba( 0,239,255), mn + 10*delta, mn + 11*delta, include_right=False),
LinearGradient(rgba( 0,239,255), rgba( 16,255,239), mn + 11*delta, mn + 12*delta, include_right=False),
LinearGradient(rgba( 16,255,239), rgba( 48,255,207), mn + 12*delta, mn + 13*delta, include_right=False),
LinearGradient(rgba( 48,255,207), rgba( 80,255,175), mn + 13*delta, mn + 14*delta, include_right=False),
LinearGradient(rgba( 80,255,175), rgba(112,255,143), mn + 14*delta, mn + 15*delta, include_right=False),
LinearGradient(rgba(112,255,143), rgba(143,255,112), mn + 15*delta, mn + 16*delta, include_right=False),
LinearGradient(rgba(143,255,112), rgba(175,255, 80), mn + 16*delta, mn + 17*delta, include_right=False),
LinearGradient(rgba(175,255, 80), rgba(207,255, 48), mn + 17*delta, mn + 18*delta, include_right=False),
LinearGradient(rgba(207,255, 48), rgba(239,255, 16), mn + 18*delta, mn + 19*delta, include_right=False),
LinearGradient(rgba(239,255, 16), rgba(255,239, 0), mn + 19*delta, mn + 20*delta, include_right=False),
LinearGradient(rgba(255,239, 0), rgba(255,207, 0), mn + 20*delta, mn + 21*delta, include_right=False),
LinearGradient(rgba(255,207, 0), rgba(255,175, 0), mn + 21*delta, mn + 22*delta, include_right=False),
LinearGradient(rgba(255,175, 0), rgba(255,143, 0), mn + 22*delta, mn + 23*delta, include_right=False),
LinearGradient(rgba(255,143, 0), rgba(255,112, 0), mn + 23*delta, mn + 24*delta, include_right=False),
LinearGradient(rgba(255,112, 0), rgba(255, 80, 0), mn + 24*delta, mn + 25*delta, include_right=False),
LinearGradient(rgba(255, 80, 0), rgba(255, 48, 0), mn + 25*delta, mn + 26*delta, include_right=False),
LinearGradient(rgba(255, 48, 0), rgba(255, 16, 0), mn + 26*delta, mn + 27*delta, include_right=False),
LinearGradient(rgba(255, 16, 0), rgba(239, 0, 0), mn + 27*delta, mn + 28*delta, include_right=False),
LinearGradient(rgba(239, 0, 0), rgba(207, 0, 0), mn + 28*delta, mn + 29*delta, include_right=False),
LinearGradient(rgba(207, 0, 0), rgba(175, 0, 0), mn + 29*delta, mn + 30*delta, include_right=False),
LinearGradient(rgba(175, 0, 0), rgba(143, 0, 0), mn + 30*delta, mn + 31*delta, include_right=False),
ColorBin (rgba(143, 0, 0), mn+31*delta, mx),
CatchAll (rgba( 1, 1, 1, 0))
)
# color palettes for the views based on CERA NetCDFs
imperial = dict(
water_height = jet(0, 10),
inundation_depth = jet(0, 6),
wave_height = jet(0, 26),
rel_peak = jet(0, 16),
wind_speed = jet(0, 60),
)
default = jet(0.0, 256)
metric = dict(
water_height = (default, 0, 3),
inundation_depth = (default, 0, 2),
wave_height = (default, 0, 8),
rel_peak = (default, 0, 16),
wind_speed = (default, 0, 100),
)
imperial_units = ('ft','ft','ft','s','mph')
metric_units = ('m','m','m','s','km/h')
palettes = {
'default' : jet(0.0, 256.0),
'adcirc' : jet(0.0, 256.0)
}
class RenderingContext(object):
"""Renders a triangular irregular grid to a Cairo surface"""
def __init__(self, palette, minx, miny, maxx, maxy, minv, maxv, width, height, surfdata=None):
"""
:param palette: the palette to use to color the geometry
:param minx: the minx to render in the geometry's coordinate system
:param miny: the miny to render
:param maxx: the maxx to render
:param maxy: the maxy to render
:param width: the width of the image in pixels
:param height: the height of the image in pixels
:param surfdata: if we have pre-rendered surface data (like another layer), pass it in so a new surface isn't created.
:return:
"""
self.palette = palette
self.minx=minx
self.miny=miny
self.maxx=maxx
self.maxy=maxy
self.minv=minv
self.maxv=maxv
if surfdata:
self.surface = cr.ImageSurface.create_for_data(surfdata, cr.FORMAT_ARGB32, width, height)
else:
self.surface = cr.ImageSurface(cr.FORMAT_ARGB32, width, height)
self.ctx = cr.Context(self.surface)
self.height = height
self.pixel_w = (maxx-minx) / width
self.pixel_h = (maxy-miny) / height
def cleanslate(self):
"""Clear the slate for new rendering.
"""
self.ctx.set_source_rgba(1,1,1,0)
self.ctx.set_operator(cr.OPERATOR_SOURCE)
self.ctx.paint()
def render(self, geometry, data):
"""
:param data: The data to use. This will be passed to the styler wholesale.
:return: None
"""
c = 0
binsize=(self.maxv-self.minv)/256.0
bins = np.arange(self.minv, self.maxv, binsize)
data = np.digitize(np.clip(data, self.minv, self.maxv,data), bins)
geometry[...,...,0] -= self.minx
geometry[...,...,0] /= self.pixel_w
geometry[...,...,1] -= self.maxy
geometry[...,...,1] /= -self.pixel_h
then = datetime.now()
last_bin = None
for i in np.argsort(data):
c+=1
if last_bin is None:
color = np.array([self.palette(data[i])], dtype=np.uint32).view(dtype=np.uint8) / 255.0
self.ctx.set_source_rgba(*color)
last_bin = data[i]
elif last_bin != data[i]:
self.ctx.fill()
color = np.array([self.palette(data[i])], dtype=np.uint32).view(dtype=np.uint8) / 255.0
self.ctx.set_source_rgba(*color)
last_bin = data[i]
self._sketch_triangle(geometry[i])
self.ctx.fill()
delta = datetime.now() - then # timing
log.debug("Rendered {ln} elements in {secs}.{usecs}".format(ln=c, secs=delta.seconds, usecs=delta.microseconds)) # timing
def _sketch_triangle(self, g):
self.ctx.move_to(*g[0])
self.ctx.line_to(*g[1])
self.ctx.line_to(*g[2])
self.ctx.close_path()
# TODO create a WCS view for the local pyramid - could use OpenDAP subsetting for this.
# TODO create a WMS view for the local pyramid.
class WMSAdapter(wms.WMSAdapterBase):
def __init__(self, styles):
super(WMSAdapter, self).__init__({}, requires_time=True)
self.cache = wms.WMSCache('cera')
self.styles = styles
def get_valid_elevations(self, **kwargs):
return [0] # TODO get the elevations from the bathymetry and allow a person to filter based on that.
def get_2d_dataset(
self, layers, srs, bbox, width, height, styles, bgcolor, transparent, time, elevation, v, filter, **kwargs
):
time = time if time else datetime.now() # if we don't have time, we should use whatever the latest is.
srs = int(srs[5:] if srs.upper().startswith('EPSG:') else int(srs))
t_srs = SpatialReference()
s_srs = SpatialReference()
s_srs.ImportFromEPSG(4326)
t_srs.ImportFromEPSG(srs)
crx = CoordinateTransformation(t_srs, s_srs) # transform to lon-lat for getting into the bathymetry index
x1, y1, _ = crx.TransformPoint(bbox[0], bbox[1], 0)
x2, y2, _ = crx.TransformPoint(bbox[2], bbox[3], 0)
t_srs = SpatialReference()
s_srs = SpatialReference()
s_srs.ImportFromEPSG(4326)
t_srs.ImportFromEPSG(srs)
xrc = CoordinateTransformation(s_srs, t_srs)
then = datetime.now() # timing
if isinstance(styles, list):
styles = styles[0]
palette, minv, maxv = self.styles[styles]
ctx = RenderingContext(palette, bbox[0], bbox[1], bbox[2], bbox[3], minv, maxv, width, height)
delta = datetime.now() - then # timing
log.debug("Created rendering context in {secs}.{usecs}".format(secs=delta.seconds, usecs=delta.microseconds)) # timing
for layer in layers:
basename, varname = layer.split('.')
then = datetime.now()
geometry, values = query.bbox_mean_values_for_triangles(basename, varname, time, (x1,y1,x2,y2))
delta = datetime.now() - then # timing
log.debug("query completed in {secs}.{usecs}".format(secs=delta.seconds, usecs=delta.microseconds)) # timing
if geometry.shape[0] == 0:
continue
then = datetime.now()
if srs != 4326:
log.debug('transforming geometry from 4326 to {srs}'.format(srs=srs))
geometry = geometry.reshape(geometry.shape[0]*3, 2)
for i in range(geometry.shape[0]):
x, y, _ = xrc.TransformPoint(geometry[i,0], geometry[i,1])
geometry[i,0] = x
geometry[i,1] = y
geometry = geometry.reshape(geometry.shape[0]/3, 3, 2)
delta = datetime.now() - then # timing
log.debug("transformation completed in {secs}.{usecs}".format(secs=delta.seconds, usecs=delta.microseconds)) # timing
ctx.render(geometry, values)
return ctx.surface
def get_layer_descriptions(self):
query.ensure_bathymetry_index()
minx, miny, maxx, maxy = query._local.index.bounds
return [{
'name' : var.basename + '.' + var.name,
'srs' : 4326,
'queryable' : True,
'minx' : minx,
'miny' : miny,
'maxx' : maxx,
'maxy' : maxy,
'll_minx' : minx,
'll_miny' : miny,
'll_maxx' : maxx,
'll_maxy' : maxy,
'styles' : self.styles.keys()
} for var in models.Variable.objects.all()]
def cache_result(self, item, **kwargs):
locator = kwargs
locator['layers'] = ','.join(locator['layers'])
locator['time'] = locator['time'].strftime("%Y%m%d%H") if 'time' in locator and locator['time'] else query.today() + timedelta(hours=datetime.now().hour)
if 'fresh' in locator:
del locator['fresh']
self.cache.save(item, **locator)
def get_cache_record(self, **kwargs):
locator = kwargs
locator['layers'] = ','.join(locator['layers'])
locator['time'] = locator['time'].strftime("%Y%m%d%H") if 'time' in locator and locator['time'] else query.today() + timedelta(hours=datetime.now().hour)
if 'fresh' in locator:
del locator['fresh']
return self.cache.locate(**locator)
def get_valid_times(self, **kwargs):
return [run.when for run in models.ModelRun.objects.all()] # TODO this should contain all valid times for each layer, not just the model run times.
def nativesrs(self, layer):
return 4326
def get_valid_versions(self, group_by=None, **kwargs):
return [run.when.strftime('%Y%m%d%H') for run in models.ModelRun.objects.all()]
def get_feature_info(self, wherex, wherey, layers, callback, format, feature_count, srs, filter):
srs = int(srs[5:] if srs.upper().startswith('EPSG:') else srs)
t_srs = SpatialReference()
s_srs = SpatialReference()
s_srs.ImportFromEPSG(4326)
t_srs.ImportFromEPSG(srs)
crx = CoordinateTransformation(t_srs, s_srs) # transform to lon-lat for getting into the bathymetry index
x, y, _ = crx.TransformPoint(wherex, wherey, 0)
result = {}
for layer in layers:
basename, varname = layer.split('.')
triangle, value = query.value_nearest(basename, varname, filter['time'], x, y, version=filter['version'] if 'version' in filter else None)
result[layer] = value
if callback:
return callback(result)
else:
return result
def nativebbox(self):
query.ensure_bathymetry_index()
return query._local.index.bounds
def get_service_boundaries(self):
return self.nativebbox()
def layerlist(self):
return [(var.basename + '.' + var.name) for var in models.Variable.objects.all()]
class WMS(wms.WMS):
adapter = WMSAdapter(metric)
title = "NCFS ADCIRC storm surge model output"