def __init__(self, fig, traj, **kw):
self.__dict__.update(kw)
if not fig.axes:
ax_map = fig.add_subplot(1, 2, 1)
ax_ts = fig.add_subplot(2, 2, 2)
ax_ts2 = fig.add_subplot(2, 2, 4)
else:
# assume that ax_map, ax_ts, and/or ax_ts2 were passed in
ax_map = self.ax_map
ax_ts = self.ax_ts
ax_ts2 = self.ax_ts2
if ax_map:
pos = ax_map.get_position()
plot_wkb.plot_polygon(grid_poly,
ax=ax_map,
fc='0.8',
ec='0.6',
lw=0.5,
zorder=-2)
ax_map.axis('equal')
ax_map.axis((606812, 633363, 4222818, 4256651))
ax_map.xaxis.set_visible(0)
ax_map.yaxis.set_visible(0)
ax_map.plot(traj['traj']['x'], traj['traj']['y'], 'k-', lw=0.5)
sel = np.zeros(len(traj['Tfill']), np.bool8)
sel[:] = True # thinned out
obs = traj['fill_dist'] == 0
sel[obs] = True
sizes = 5 * np.ones_like(sel)
sizes[obs] = 60
scat = ax_map.scatter(traj['traj']['x'][sel],
traj['traj']['y'][sel],
sizes[sel],
traj['Tfill'][sel],
cmap=self.cmap)
scat.set_clim(self.clim)
if ax_ts:
ax_ts.plot(traj['traj']['t'], traj['Tfill'], label='Tfill')
ax_ts.set_ylabel('Lagrangian temp $^{\circ}$C')
if ax_ts2:
ax_ts2.plot(traj['traj']['t'],
np.abs(traj['fill_dist']) / 3600.,
label='fill_dist')
ax_ts2.set_ylabel('Hours from observation')
if ax_ts:
ax_ts2.set_xlim(ax_ts.get_xlim())
fig.autofmt_xdate()
if ax_map:
cax = fig.add_axes([pos.xmin, pos.ymin - 0.08, pos.width, 0.03])
plt.colorbar(scat,
cax=cax,
orientation='horizontal',
label='$^{\circ}$C')
def __init__(self, fig, t, **kw):
self.__dict__.update(kw)
snap_data = extract_particle_snapshot(t)
if self.ax is None:
fig.clf()
ax = fig.add_subplot(1, 1, 1)
ax.set_position([0, 0, 1, 1])
else:
ax = self.ax
plot_wkb.plot_polygon(grid_poly,
ax=ax,
fc='0.8',
ec='none',
lw=0.5,
zorder=-2)
plot_wkb.plot_polygon(grid_poly,
ax=ax,
fc='none',
ec='k',
lw=0.5,
zorder=2)
station_xys = np.array([station.xy.values for station in stations])
ax.plot(station_xys[:, 0], station_xys[:, 1], 'ko', ms=5)
values = self.snap_to_value(snap_data)
sel = np.isfinite(values)
stale_s = np.abs(snap_data['fill_dist'])
sel = sel & (stale_s < self.stale_thresh_s)
scat = ax.scatter(snap_data['x'][sel], snap_data['y'][sel],
40 * (1 / (1 + stale_s[sel] / 1800.)), values[sel])
scat.set_cmap(self.cmap)
scat.set_clim(self.clim)
pos = ax.get_position()
cax = fig.add_axes([
pos.xmin + 0.08, pos.ymin + 0.93 * pos.height, pos.width * 0.25,
0.02
])
ax.text(0.08,
0.96,
utils.to_datetime(t).strftime("%Y-%m-%d %H:%M PST"),
transform=ax.transAxes)
plt.colorbar(scat,
cax=cax,
orientation='horizontal',
label=self.units_label)
ax.xaxis.set_visible(0)
ax.yaxis.set_visible(0)
ax.axis('equal')
ax.axis(self.zoom)
valid1=np.isfinite(per_cell_K) & (per_cell_K>=0)
coll1=g.plot_cells(values=per_cell_K.clip(1,np.inf),
norm=colors.LogNorm(),
mask=valid1,ax=ax1)
valid2=np.isfinite(smooth_K)&(smooth_K>=0)
coll2=g.plot_cells(values=smooth_K.clip(1,np.inf),
norm=colors.LogNorm(),
mask=valid2,ax=ax2)
for coll in [coll1,coll2]:
coll.set_clim([3,300])
coll.set_cmap('inferno_r')
for coll,ax in zip([coll1,coll2],[ax1,ax2]):
plot_wkb.plot_polygon(grid_poly,ax=ax,fc='none',ec='k',lw=0.5)
plt.colorbar(coll, label="log10 K",ax=ax)
ax.axis('equal')
ax.axis(zoom)
ax.xaxis.set_visible(0)
ax.yaxis.set_visible(0)
ax1.set_title('Output')
ax2.set_title('Smoothed')
fig.tight_layout()
fig.savefig('third-cutb-dispersion.png',dpi=200)
##
ax.plot(particles[0,:,0],
xyz_aug = field.XYZField(X=cdt.nodes['x'], F=cdt.nodes['value'])
aug_tri = delaunay.Triangulation(xyz_aug.X[:, 0], xyz_aug.X[:, 1],
cdt.cells['nodes'][~cdt.cells['deleted']])
xyz_aug._tri = aug_tri
dem2 = xyz_aug.to_grid(dx=5, dy=10, interp='linear')
##
plt.figure(20).clf()
#fig,ax=plt.subplots(1,1,num=20,sharex=True,sharey=True)
fig, (ax, ax2) = plt.subplots(1, 2, num=20, sharex=True, sharey=True)
plot_wkb.plot_polygon(poly, ax=ax, fc='none')
ax.scatter(xyz_sub.X[:, 0],
xyz_sub.X[:, 1],
30,
xyz_sub.F,
lw=1,
edgecolor='m')
dem1.plot(ax=ax, interpolation='none', zorder=-2)
# cdt.plot_edges(ax=ax,edgecolor='k')
# Worse:
dem2.plot(ax=ax2, interpolation='none', zorder=-2)
plot_wkb.plot_polygon(poly, ax=ax2, fc='none')
g_sfb = dfm_grid.DFMGrid('../../sfb_dfm_v2/sfei_v20_net.nc')
##
g_roms_poly = g_roms.boundary_polygon()
g_sfb_poly = g_sfb.boundary_polygon()
##
plt.figure(1).clf()
fig, ax = plt.subplots(num=1)
g_roms.plot_edges(ax=ax, color='b', lw=0.8)
g_sfb.plot_edges(ax=ax, color='g', lw=0.8)
plot_wkb.plot_polygon(g_roms_poly, facecolor='b', alpha=0.3)
plot_wkb.plot_polygon(g_sfb_poly, facecolor='g', alpha=0.3)
##
# Clear out a buffer region
sfb_dx_min = 200
roms_dx_typ = 3500
# cheating a bit - ought to be more like 10xn
buff_size = (roms_dx_typ - sfb_dx_min) * 6
sfb_buff = g_sfb_poly.buffer(buff_size)
##
overlap_cells = g_roms.select_cells_intersecting(sfb_buff)
poly = g.boundary_polygon()
##
# zoom=(605889.6569457075, 638002.2586920519, 4217801.158715993, 4241730.226468915)
zoom = (597913.7274775933, 648118.8262812896, 4217179.54644355,
4301202.344200377)
# zoom=(611280.377359663, 632614.9072567355, 4222938.787804629, 4248182.140275016)
plt.figure(1).clf()
fig, ax = plt.subplots(num=1)
init.plot(ntimes - 1, ax=ax, zoom=zoom, update=False, ms=1)
sac.plot(ntimes - 1, ax=ax, zoom=zoom, update=False, color='cyan', ms=1)
srv.plot(ntimes - 1, ax=ax, zoom=zoom, update=False, color='g', ms=1)
# g.plot_edges(color='k',lw=0.4,ax=ax,clip=zoom)
plot_wkb.plot_polygon(poly, ax=ax, fc='0.8', ec='k', lw=0.5)
ax.axis(zoom)
##
for ti in range(0, ntimes, 2):
init.plot(ti, ax=ax, zoom=zoom)
sac.plot(ti, ax=ax, zoom=zoom)
srv.plot(ti, ax=ax, zoom=zoom)
plt.draw()
plt.pause(0.001)
##
ax2.yaxis.set_visible(0)
ax1.text(0.05, 0.95, 'IM1', transform=ax1.transAxes)
ax2.text(0.05, 0.95, 'IM2', transform=ax2.transAxes)
ccolls = []
plot_vars = ['IM1', 'IM2']
for v, ax, cax in zip(plot_vars, [ax1, ax2], [cax1, cax2]):
ssc = map_ds[v].isel(time=-1, layer=0).values
ssc = np.ma.array(
ssc,
mask=(ssc == -999)) # map_ds[v].isel(time=-1,layer=0).values.copy()
ax.set_facecolor('0.6')
plot_wkb.plot_polygon(boundary,
facecolor='0.8',
edgecolor='none',
ax=ax,
lw=0.25,
zorder=-1)
ccoll = g.plot_cells(lw=0.5, values=ssc, ax=ax, cmap='CMRmap_r')
ccoll.set_clim([0, 50])
ccoll.set_edgecolor('face')
ccolls.append(ccoll)
plt.colorbar(ccoll, cax=cax)
ax.axis('equal')
##
for frame, ti in enumerate(range(0, 800, 2)):
print "[%04d] %d/%d" % (frame, ti, len(map_ds.time))
for v, ccoll in zip(plot_vars, ccolls):
ssc = map_ds[v].isel(time=ti, layer=0).values