def nosql_draw2(check_func, match):
from matplotlib.backends.backend_agg import FigureCanvas
try:
from matplotlib.backends.backend_agg import Figure
except ImportError:
from matplotlib.figure import Figure
was_interactive = mpl.is_interactive()
if was_interactive:
mpl.interactive(False)
# fnum = 32
fig = Figure()
canvas = FigureCanvas(fig) # NOQA
# fig.clf()
ax = fig.add_subplot(1, 1, 1)
if check_func is not None and check_func():
return
ax, xywh1, xywh2 = match.show(ax=ax)
if check_func is not None and check_func():
return
savekw = {
# 'dpi' : 60,
'dpi': 80,
}
axes_extents = pt.extract_axes_extents(fig)
# assert len(axes_extents) == 1, 'more than one axes'
extent = axes_extents[0]
with io.BytesIO() as stream:
# This call takes 23% - 15% of the time depending on settings
fig.savefig(stream, bbox_inches=extent, **savekw)
stream.seek(0)
data = np.fromstring(stream.getvalue(), dtype=np.uint8)
if check_func is not None and check_func():
return
pt.plt.close(fig)
image = cv2.imdecode(data, 1)
thumbsize = 221
max_dsize = (thumbsize, thumbsize)
dsize, sx, sy = vt.resized_clamped_thumb_dims(
vt.get_size(image), max_dsize)
if check_func is not None and check_func():
return
image = vt.resize(image, dsize)
vt.imwrite(fpath, image)
if check_func is not None and check_func():
return
def make_plot(ts, dat, ylabel='Data', ylog=False, enums=None,
ts2=None, dat2=None, y2label=None,
y2log=False, enums2=None,
tmin=None, tmax=None, fname=None,
ymin=None, ymax=None, y2min=None, y2max=None):
fig = Figure(figsize=(8., 5.0), dpi=300)
gspec = GridSpec(1, 1)
canvas = FigureCanvas(fig)
axes = fig.add_subplot(gspec[0], facecolor='#FFFFFF')
if ylog: # and False:
axes.set_yscale('log', basey=10)
pos = np.where(dat>0)
ts = ts[pos]
dat = dat[pos]
tvals = [ts2date(t) for t in ts]
if enums is not None:
pad = min(0.8, 0.1*len(enums))
axes.set_ylim(-pad, len(enums)-1+pad)
axes.set_yticks(range(len(enums)))
axes.set_yticklabels(enums)
try:
axes.get_yaxis().get_major_formatter().set_useOffset(False)
except:
pass
if tmin is not None and tmax is not None:
axes.set_xlim((ts2date(tmin), ts2date(tmax)))
if ymin is not None or ymax is not None:
if ymin is not None:
ymin = float(ymin)
else:
ymin = min(dat)
if ymax is not None:
ymax = float(ymax)
else:
ymax = max(dat)
axes.set_ylim((ymin, ymax))
axes.set_xlabel('Date', fontproperties=mplfont)
axes.set_ylabel(ylabel, color='b', fontproperties=mplfont)
axes.xaxis.set_major_formatter(DateFormatter("%H:%M\n%b-%d"))
axes.plot(tvals, dat, color='b', **plotopts)
for x in axes.get_xticklabels():
x.set_rotation(0)
x.set_ha('center')
axes.grid(True, zorder=-5)
if ts2 is not None:
if len(fig.get_axes()) < 2:
ax = axes.twinx()
axes = fig.get_axes()[1]
axes0 = fig.get_axes()[0]
axes0.set_zorder(axes.get_zorder()+10)
axes0.patch.set_visible(False)
axes0.grid(axes.get_zorder()-5)
axes.grid(False)
try:
axes.get_yaxis().get_major_formatter().set_useOffset(False)
except:
pass
if y2log:
axes.set_yscale('log', basey=10)
pos = np.where(dat2>0)
ts2 = ts2[pos]
dat2 = dat2[pos]
t2vals = [ts2date(t) for t in ts2]
if enums2 is not None:
pad = min(0.8, 0.1*len(enums2))
axes.set_ylim(-pad, len(enums2)-1+pad)
axes.set_yticks(range(len(enums2)))
axes.set_yticklabels(enums2)
plotopts['zorder'] = 20
axes.plot(t2vals, dat2, color='r', **plotopts)
axes.set_ylabel(y2label, color='r', fontproperties=mplfont)
if tmin is not None and tmax is not None:
axes.set_xlim((ts2date(tmin), ts2date(tmax)))
if y2min is not None or y2max is not None:
if y2min is not None:
y2min = float(y2min)
else:
y2min = min(dat2)
if y2max is not None:
y2max = float(y2max)
else:
y2max = max(dat2)
axes.set_ylim((y2min, y2max))
auto_margins(fig, canvas, axes, gspec)
if fname is None:
figdata = io.BytesIO()
fig.savefig(figdata, format='png', facecolor='#FDFDFA')
figdata.seek(0)
return base64.b64encode(figdata.getvalue())
else:
fig.savefig(fname)
return fname
def nosql_draw(check_func, rchip1_fpath, rchip2_fpath, kpts1, kpts2):
# This gets executed in the child thread and does drawing async style
#from matplotlib.backends.backend_pdf import FigureCanvasPdf as FigureCanvas
#from matplotlib.backends.backend_pdf import Figure
#from matplotlib.backends.backend_svg import FigureCanvas
#from matplotlib.backends.backend_svg import Figure
from matplotlib.backends.backend_agg import FigureCanvas
try:
from matplotlib.backends.backend_agg import Figure
except ImportError:
from matplotlib.figure import Figure
kpts1_ = vt.offset_kpts(kpts1, (0, 0), (resize_factor, resize_factor))
kpts2_ = vt.offset_kpts(kpts2, (0, 0), (resize_factor, resize_factor))
#from matplotlib.figure import Figure
if check_func is not None and check_func():
return
rchip1 = vt.imread(rchip1_fpath)
rchip1 = vt.resize_image_by_scale(rchip1, resize_factor)
if check_func is not None and check_func():
return
rchip2 = vt.imread(rchip2_fpath)
rchip2 = vt.resize_image_by_scale(rchip2, resize_factor)
if check_func is not None and check_func():
return
try:
idx = cm.daid2_idx[daid]
fm = cm.fm_list[idx]
fsv = None if cm.fsv_list is None else cm.fsv_list[idx]
fs = None if fsv is None else fsv.prod(axis=1)
except KeyError:
fm = []
fs = None
fsv = None
maxnum = 200
if fs is not None and len(fs) > maxnum:
# HACK TO ONLY SHOW TOP MATCHES
sortx = fs.argsort()[::-1]
fm = fm.take(sortx[:maxnum], axis=0)
fs = fs.take(sortx[:maxnum], axis=0)
was_interactive = mpl.is_interactive()
if was_interactive:
mpl.interactive(False)
#fnum = 32
fig = Figure()
canvas = FigureCanvas(fig) # NOQA
#fig.clf()
ax = fig.add_subplot(1, 1, 1)
if check_func is not None and check_func():
return
#fig = pt.plt.figure(fnum)
#H1 = np.eye(3)
#H2 = np.eye(3)
#H1[0, 0] = .5
#H1[1, 1] = .5
#H2[0, 0] = .5
#H2[1, 1] = .5
ax, xywh1, xywh2 = pt.show_chipmatch2(rchip1, rchip2, kpts1_, kpts2_, fm,
fs=fs, colorbar_=False, ax=ax)
if check_func is not None and check_func():
return
savekw = {
# 'dpi' : 60,
'dpi' : 80,
}
axes_extents = pt.extract_axes_extents(fig)
#assert len(axes_extents) == 1, 'more than one axes'
extent = axes_extents[0]
with io.BytesIO() as stream:
# This call takes 23% - 15% of the time depending on settings
fig.savefig(stream, bbox_inches=extent, **savekw)
stream.seek(0)
data = np.fromstring(stream.getvalue(), dtype=np.uint8)
if check_func is not None and check_func():
return
pt.plt.close(fig)
image = cv2.imdecode(data, 1)
thumbsize = 221
max_dsize = (thumbsize, thumbsize)
dsize, sx, sy = vt.resized_clamped_thumb_dims(vt.get_size(image), max_dsize)
if check_func is not None and check_func():
return
image = vt.resize(image, dsize)
vt.imwrite(fpath, image)
if check_func is not None and check_func():
return