def reset_ax(self):
# from wbia.plottool.interactions import zoom_factory, pan_factory
import wbia.plottool as pt
self.ax = self.fig.add_subplot(1, 1, 1)
pt.adjust_subplots(left=0, right=1, top=1, bottom=0, fig=self.fig)
# self.pan_events = pan_factory(self.ax)
# self.zoon_events = zoom_factory(self.ax)
return self.ax
def show_page(self, bring_to_front=False):
""" Plots all subaxes on a page """
print('[querydec] show_page()')
self.prepare_page()
# Variables we will work with to paint a pretty picture
# ibs = self.ibs
nRows = self.nRows
nCols = self.nCols
# Plot the Comparisions
for count, c_aid in enumerate(self.comp_aids):
if c_aid is not None:
px = nCols + count + 1
title_suffix = ''
if self.suggest_aids is not None and c_aid in self.suggest_aids:
title_suffix = 'SUGGESTED BY IBEIS'
self.plot_chip(c_aid, nRows, nCols, px, title_suffix=title_suffix)
else:
pt.imshow_null(
fnum=self.fnum,
pnum=(nRows, nCols, nCols + count + 1),
title='NO RESULT',
)
# Plot the Query Chip last
with ut.EmbedOnException():
query_title = 'Identify This Animal'
self.plot_chip(self.query_aid, nRows, 1, 1, title_suffix=query_title)
self.show_hud()
pt.adjust_subplots(
top=0.88, hspace=0.12, left=0.1, right=0.9, bottom=0.1, wspace=0.3
)
self.draw()
self.show()
if bring_to_front:
self.bring_to_front()
def show_page(self, bring_to_front=False, onlyrows=None, fulldraw=True):
""" Plots all subaxes on a page
onlyrows is a hack to only draw a subset of the data again
"""
if ut.VERBOSE:
if not fulldraw:
logger.info('[matchver] show_page(fulldraw=%r, onlyrows=%r)' %
(fulldraw, onlyrows))
else:
logger.info('[matchver] show_page(fulldraw=%r)' % (fulldraw))
self.prepare_page(fulldraw=fulldraw)
# Variables we will work with to paint a pretty picture
ibs = self.ibs
nRows = self.nRows
colpad = 1 if self.cm is not None else 0
nCols = self.nCols + colpad
# Distinct color for every unique name
unique_nids = ut.unique_ordered(
ibs.get_annot_name_rowids(self.all_aid_list,
distinguish_unknowns=False))
unique_colors = pt.distinct_colors(len(unique_nids),
brightness=0.7,
hue_range=(0.05, 0.95))
self.nid2_color = dict(zip(unique_nids, unique_colors))
row_aids_list = self.get_row_aids_list()
if self.cm is not None:
logger.info('DRAWING QRES')
pnum = (1, nCols, 1)
if not fulldraw:
# not doing full draw so we have to clear any axes
# that are here already manually
ax = self.fig.add_subplot(*pnum)
self.clear_parent_axes(ax)
self.cm.show_single_annotmatch(
self.qreq_,
self.aid2,
fnum=self.fnum,
pnum=pnum,
draw_fmatch=True,
colorbar_=False,
)
# For each row
for rowx, aid_list in enumerate(row_aids_list):
offset = rowx * nCols + 1
if onlyrows is not None and rowx not in onlyrows:
continue
# ibsfuncs.assert_valid_aids(ibs, groundtruth)
# For each column
for colx, aid in enumerate(aid_list, start=colpad):
if colx >= nCols:
break
try:
nid = ibs.get_annot_name_rowids(aid)
if ibsfuncs.is_nid_unknown(ibs, [nid])[0]:
color = const.UNKNOWN_PURPLE_RGBA01
else:
color = self.nid2_color[nid]
except Exception as ex:
ut.printex(ex)
logger.info('nid = %r' % (nid, ))
logger.info('self.nid2_color = %s' %
(ut.repr2(self.nid2_color), ))
raise
px = colx + offset
ax = self.plot_chip(int(aid),
nRows,
nCols,
px,
color=color,
fulldraw=fulldraw)
# If there are still more in this row to display
if colx + 1 < len(aid_list) and colx + 1 >= nCols:
total_indices = len(aid_list)
current_index = self.col_offset_list[rowx] + 1
next_text = 'next\n%d/%d' % (current_index, total_indices)
next_func = functools.partial(self.rotate_row, rowx=rowx)
self.append_button(
next_text,
callback=next_func,
location='right',
size='33%',
ax=ax,
)
if fulldraw:
self.show_hud()
hspace = 0.05 if (self.nCols) > 1 else 0.1
subplotspar = {
'left': 0.1,
'right': 0.9,
'top': 0.85,
'bottom': 0.1,
'wspace': 0.3,
'hspace': hspace,
}
pt.adjust_subplots(**subplotspar)
self.draw()
self.show()
if bring_to_front:
self.bring_to_front()
def show_time_distributions(ibs, unixtime_list):
r"""
"""
# import vtool as vt
import wbia.plottool as pt
unixtime_list = np.array(unixtime_list)
num_nan = np.isnan(unixtime_list).sum()
num_total = len(unixtime_list)
unixtime_list = unixtime_list[~np.isnan(unixtime_list)]
from wbia.scripts.thesis import TMP_RC
import matplotlib as mpl
mpl.rcParams.update(TMP_RC)
if False:
from matplotlib import dates as mpldates
# data_list = list(map(ut.unixtime_to_datetimeobj, unixtime_list))
n, bins, patches = pt.plt.hist(unixtime_list, 365)
# n_ = list(map(ut.unixtime_to_datetimeobj, n))
# bins_ = list(map(ut.unixtime_to_datetimeobj, bins))
pt.plt.setp(patches, 'facecolor', 'g', 'alpha', 0.75)
ax = pt.gca()
# ax.xaxis.set_major_locator(mpldates.YearLocator())
# hfmt = mpldates.DateFormatter('%y/%m/%d')
# ax.xaxis.set_major_formatter(hfmt)
mpldates.num2date(unixtime_list)
# pt.gcf().autofmt_xdate()
# y = pt.plt.normpdf( bins, unixtime_list.mean(), unixtime_list.std())
# ax.set_xticks(bins_)
# l = pt.plt.plot(bins_, y, 'k--', linewidth=1.5)
else:
pt.draw_time_distribution(unixtime_list)
# pt.draw_histogram()
ax = pt.gca()
ax.set_xlabel('Date')
ax.set_title(
'Timestamp distribution of %s. #nan=%d/%d'
% (ibs.get_dbname_alias(), num_nan, num_total)
)
pt.gcf().autofmt_xdate()
icon = ibs.get_database_icon()
if False and icon is not None:
# import matplotlib as mpl
# import vtool as vt
ax = pt.gca()
# Overlay a species icon
# http://matplotlib.org/examples/pylab_examples/demo_annotation_box.html
# icon = vt.convert_image_list_colorspace([icon], 'RGB', 'BGR')[0]
# pt.overlay_icon(icon, coords=(0, 1), bbox_alignment=(0, 1))
pt.overlay_icon(
icon,
coords=(0, 1),
bbox_alignment=(0, 1),
as_artist=1,
max_asize=(100, 200),
)
# imagebox = mpl.offsetbox.OffsetImage(icon, zoom=1.0)
# # xy = [ax.get_xlim()[0] + 5, ax.get_ylim()[1]]
# # ax.set_xlim(1, 100)
# # ax.set_ylim(0, 100)
# # x = np.array(ax.get_xlim()).sum() / 2
# # y = np.array(ax.get_ylim()).sum() / 2
# # xy = [x, y]
# # logger.info('xy = %r' % (xy,))
# # x = np.nanmin(unixtime_list)
# # xy = [x, y]
# # logger.info('xy = %r' % (xy,))
# # ax.get_ylim()[0]]
# xy = [ax.get_xlim()[0], ax.get_ylim()[1]]
# ab = mpl.offsetbox.AnnotationBbox(
# imagebox, xy, xycoords='data',
# xybox=(-0., 0.),
# boxcoords="offset points",
# box_alignment=(0, 1), pad=0.0)
# ax.add_artist(ab)
if ut.get_argflag('--contextadjust'):
# pt.adjust_subplots(left=.08, bottom=.1, top=.9, wspace=.3, hspace=.1)
pt.adjust_subplots(use_argv=True)
def show_graph(infr, title, final=False, selected_edges=None):
if not VISUALIZE:
return
# TODO: rich colored text?
latest = '\n'.join(infr.latest_logs())
showkw = dict(
# fontsize=infr.graph.graph['fontsize'],
# fontname=infr.graph.graph['fontname'],
show_unreviewed_edges=True,
show_inferred_same=False,
show_inferred_diff=False,
outof=(len(infr.aids)),
# show_inferred_same=True,
# show_inferred_diff=True,
selected_edges=selected_edges,
show_labels=True,
simple_labels=True,
# show_recent_review=not final,
show_recent_review=False,
# splines=infr.graph.graph['splines'],
reposition=False,
# with_colorbar=True
)
verbose = infr.verbose
infr.verbose = 0
infr_ = infr.copy()
infr_ = infr
infr_.verbose = verbose
infr_.show(pickable=True, verbose=0, **showkw)
infr.verbose = verbose
# logger.info('status ' + ut.repr4(infr_.status()))
# infr.show(**showkw)
ax = pt.gca()
pt.set_title(title, fontsize=20)
fig = pt.gcf()
fontsize = 22
if True:
# postprocess xlabel
lines = []
for line in latest.split('\n'):
if False and line.startswith('ORACLE ERROR'):
lines += ['ORACLE ERROR']
else:
lines += [line]
latest = '\n'.join(lines)
if len(lines) > 10:
fontsize = 16
if len(lines) > 12:
fontsize = 14
if len(lines) > 14:
fontsize = 12
if len(lines) > 18:
fontsize = 10
if len(lines) > 23:
fontsize = 8
if True:
pt.adjust_subplots(top=0.95, left=0, right=1, bottom=0.45, fig=fig)
ax.set_xlabel('\n' + latest)
xlabel = ax.get_xaxis().get_label()
xlabel.set_horizontalalignment('left')
# xlabel.set_x(.025)
xlabel.set_x(-0.6)
# xlabel.set_fontname('CMU Typewriter Text')
xlabel.set_fontname('Inconsolata')
xlabel.set_fontsize(fontsize)
ax.set_aspect('equal')
# ax.xaxis.label.set_color('red')
from os.path import join
fpath = join(dpath, 'demo_{:04d}.png'.format(next(fig_counter)))
fig.savefig(
fpath,
dpi=300,
# transparent=True,
edgecolor='none',
)
# pt.save_figure(dpath=dpath, dpi=300)
infr.latest_logs()
def draw_feat_scoresep(testres, f=None, disttype=None):
r"""
SeeAlso:
wbia.unstable.scorenorm.train_featscore_normalizer
CommandLine:
python -m wbia --tf TestResult.draw_feat_scoresep --show
python -m wbia --tf TestResult.draw_feat_scoresep --show -t default:sv_on=[True,False]
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_Master1
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_Master1 --disttype=L2_sift,fg
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_Master1 --disttype=L2_sift
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_MTEST -t best:lnbnn_on=True --namemode=True
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_MTEST -t best:lnbnn_on=True --namemode=False
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_MTEST --disttype=L2_sift
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_MTEST --disttype=L2_sift -t best:SV=False
utprof.py -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_Master1
utprof.py -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_Master1 --fsvx=1:2
utprof.py -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_Master1 --fsvx=0:1
utprof.py -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_Master1 -t best:lnbnn_on=False,bar_l2_on=True --fsvx=0:1
# We want to query the oxford annots taged query
# and we want the database to contain
# K correct images per query, as well as the distractors
python -m wbia --tf TestResult.draw_feat_scoresep --show --db Oxford -a default:qhas_any=\(query,\),dpername=1,exclude_reference=True,minqual=ok
python -m wbia --tf TestResult.draw_feat_scoresep --show --db Oxford -a default:qhas_any=\(query,\),dpername=1,exclude_reference=True,minqual=good
python -m wbia --tf get_annotcfg_list --db PZ_Master1 -a timectrl --acfginfo --verbtd --veryverbtd --nocache-aid
python -m wbia --tf TestResult.draw_feat_scoresep --show --db PZ_MTEST --disttype=ratio
Example:
>>> # SCRIPT
>>> from wbia.expt.test_result import * # NOQA
>>> from wbia.init import main_helpers
>>> disttype = ut.get_argval('--disttype', type_=list, default=None)
>>> ibs, testres = main_helpers.testdata_expts(
>>> defaultdb='PZ_MTEST', a=['timectrl'], t=['best'])
>>> f = ut.get_argval(('--filt', '-f'), type_=list, default=[''])
>>> testres.draw_feat_scoresep(f=f)
>>> ut.show_if_requested()
"""
logger.info('[testres] draw_feat_scoresep')
import wbia.plottool as pt
def load_feat_scores(qreq_, qaids):
import wbia # NOQA
from os.path import dirname, join # NOQA
# HACKY CACHE
cfgstr = qreq_.get_cfgstr(with_input=True)
cache_dir = join(dirname(dirname(wbia.__file__)),
'TMP_FEATSCORE_CACHE')
namemode = ut.get_argval('--namemode', default=True)
fsvx = ut.get_argval('--fsvx',
type_='fuzzy_subset',
default=slice(None, None, None))
threshx = ut.get_argval('--threshx', type_=int, default=None)
thresh = ut.get_argval('--thresh', type_=float, default=0.9)
num = ut.get_argval('--num', type_=int, default=1)
cfg_components = [
cfgstr, disttype, namemode, fsvx, threshx, thresh, f, num
]
cache_cfgstr = ','.join(ut.lmap(six.text_type, cfg_components))
cache_hashid = ut.hashstr27(cache_cfgstr + '_v1')
cache_name = 'get_cfgx_feat_scores_' + cache_hashid
@ut.cached_func(cache_name,
cache_dir=cache_dir,
key_argx=[],
use_cache=True)
def get_cfgx_feat_scores(qreq_, qaids):
from wbia.algo.hots import scorenorm
cm_list = qreq_.execute(qaids)
# logger.info('Done loading cached chipmatches')
tup = scorenorm.get_training_featscores(qreq_,
cm_list,
disttype,
namemode,
fsvx,
threshx,
thresh,
num=num)
# logger.info(ut.depth_profile(tup))
tp_scores, tn_scores, scorecfg = tup
return tp_scores, tn_scores, scorecfg
tp_scores, tn_scores, scorecfg = get_cfgx_feat_scores(qreq_, qaids)
return tp_scores, tn_scores, scorecfg
valid_case_pos = testres.case_sample2(filt_cfg=f, return_mask=False)
cfgx2_valid_qxs = ut.group_items(valid_case_pos.T[0], valid_case_pos.T[1])
test_qaids = testres.get_test_qaids()
cfgx2_valid_qaids = ut.map_dict_vals(ut.partial(ut.take, test_qaids),
cfgx2_valid_qxs)
join_acfgs = True
# TODO: option to average over pipeline configurations
if join_acfgs:
groupxs = testres.get_cfgx_groupxs()
else:
groupxs = list(zip(range(len(testres.cfgx2_qreq_))))
grouped_qreqs = ut.apply_grouping(testres.cfgx2_qreq_, groupxs)
grouped_scores = []
for cfgxs, qreq_group in zip(groupxs, grouped_qreqs):
# testres.print_pcfg_info()
score_group = []
for cfgx, qreq_ in zip(cfgxs, testres.cfgx2_qreq_):
logger.info('Loading cached chipmatches')
qaids = cfgx2_valid_qaids[cfgx]
tp_scores, tn_scores, scorecfg = load_feat_scores(qreq_, qaids)
score_group.append((tp_scores, tn_scores, scorecfg))
grouped_scores.append(score_group)
cfgx2_shortlbl = testres.get_short_cfglbls(join_acfgs=join_acfgs)
for score_group, lbl in zip(grouped_scores, cfgx2_shortlbl):
tp_scores = np.hstack(ut.take_column(score_group, 0))
tn_scores = np.hstack(ut.take_column(score_group, 1))
scorecfg = '+++'.join(ut.unique(ut.take_column(score_group, 2)))
score_group
# TODO: learn this score normalizer as a model
# encoder = vt.ScoreNormalizer(adjust=4, monotonize=False)
encoder = vt.ScoreNormalizer(adjust=2, monotonize=True)
encoder.fit_partitioned(tp_scores, tn_scores, verbose=False)
figtitle = 'Feature Scores: %s, %s' % (scorecfg, lbl)
fnum = None
vizkw = {}
sephack = ut.get_argflag('--sephack')
if not sephack:
vizkw['target_tpr'] = 0.95
vizkw['score_range'] = (0, 1.0)
encoder.visualize(
figtitle=figtitle,
fnum=fnum,
with_scores=False,
# with_prebayes=True,
with_prebayes=False,
with_roc=True,
with_postbayes=False,
# with_postbayes=True,
**vizkw,
)
icon = testres.ibs.get_database_icon()
if icon is not None:
pt.overlay_icon(icon, coords=(1, 0), bbox_alignment=(1, 0))
if ut.get_argflag('--contextadjust'):
pt.adjust_subplots(left=0.1, bottom=0.25, wspace=0.2, hspace=0.2)
pt.adjust_subplots(use_argv=True)
return encoder
def compare_featscores():
r"""
CommandLine:
wbia --tf compare_featscores --db PZ_MTEST \
--nfscfg :disttype=[L2_sift,lnbnn],top_percent=[None,.5,.1] -a timectrl \
-p default:K=[1,2],normalizer_rule=name \
--save featscore{db}.png --figsize=13,20 --diskshow
wbia --tf compare_featscores --db PZ_MTEST \
--nfscfg :disttype=[L2_sift,normdist,lnbnn],top_percent=[None,.5] -a timectrl \
-p default:K=[1],normalizer_rule=name,sv_on=[True,False] \
--save featscore{db}.png --figsize=13,10 --diskshow
wbia --tf compare_featscores --nfscfg :disttype=[L2_sift,normdist,lnbnn] \
-a timectrl -p default:K=1,normalizer_rule=name --db PZ_Master1 \
--save featscore{db}.png --figsize=13,13 --diskshow
wbia --tf compare_featscores --nfscfg :disttype=[L2_sift,normdist,lnbnn] \
-a timectrl -p default:K=1,normalizer_rule=name --db GZ_ALL \
--save featscore{db}.png --figsize=13,13 --diskshow
wbia --tf compare_featscores --db GIRM_Master1 \
--nfscfg ':disttype=fg,L2_sift,normdist,lnbnn' \
-a timectrl -p default:K=1,normalizer_rule=name \
--save featscore{db}.png --figsize=13,13
wbia --tf compare_featscores --nfscfg :disttype=[L2_sift,normdist,lnbnn] \
-a timectrl -p default:K=[1,2,3],normalizer_rule=name,sv_on=False \
--db PZ_Master1 --save featscore{db}.png \
--dpi=128 --figsize=15,20 --diskshow
wbia --tf compare_featscores --show --nfscfg :disttype=[L2_sift,normdist] -a timectrl -p :K=1 --db PZ_MTEST
wbia --tf compare_featscores --show --nfscfg :disttype=[L2_sift,normdist] -a timectrl -p :K=1 --db GZ_ALL
wbia --tf compare_featscores --show --nfscfg :disttype=[L2_sift,normdist] -a timectrl -p :K=1 --db PZ_Master1
wbia --tf compare_featscores --show --nfscfg :disttype=[L2_sift,normdist] -a timectrl -p :K=1 --db GIRM_Master1
wbia --tf compare_featscores --db PZ_MTEST \
--nfscfg :disttype=[L2_sift,normdist,lnbnn],top_percent=[None,.5,.2] -a timectrl \
-p default:K=[1],normalizer_rule=name \
--save featscore{db}.png --figsize=13,20 --diskshow
wbia --tf compare_featscores --db PZ_MTEST \
--nfscfg :disttype=[L2_sift,normdist,lnbnn],top_percent=[None,.5,.2] -a timectrl \
-p default:K=[1],normalizer_rule=name \
--save featscore{db}.png --figsize=13,20 --diskshow
Example:
>>> # DISABLE_DOCTEST
>>> from wbia.unstable.scorenorm import * # NOQA
>>> result = compare_featscores()
>>> print(result)
>>> ut.quit_if_noshow()
>>> import wbia.plottool as pt
>>> ut.show_if_requested()
"""
import wbia.plottool as pt
import wbia
nfs_cfg_list = NormFeatScoreConfig.from_argv_cfgs()
learnkw = {}
ibs, testres = wbia.testdata_expts(defaultdb='PZ_MTEST',
a=['default'],
p=['default:K=1'])
logger.info('nfs_cfg_list = ' + ut.repr3(nfs_cfg_list))
encoder_list = []
lbl_list = []
varied_nfs_lbls = ut.get_varied_cfg_lbls(nfs_cfg_list)
varied_qreq_lbls = ut.get_varied_cfg_lbls(testres.cfgdict_list)
# varies_qreq_lbls
# func = ut.cached_func(cache_dir='.')(learn_featscore_normalizer)
for datakw, nlbl in zip(nfs_cfg_list, varied_nfs_lbls):
for qreq_, qlbl in zip(testres.cfgx2_qreq_, varied_qreq_lbls):
lbl = qlbl + ' ' + nlbl
cfgstr = '_'.join([datakw.get_cfgstr(), qreq_.get_full_cfgstr()])
try:
encoder = vt.ScoreNormalizer()
encoder.load(cfgstr=cfgstr)
except IOError:
logger.info('datakw = %r' % (datakw, ))
encoder = learn_featscore_normalizer(qreq_, datakw, learnkw)
encoder.save(cfgstr=cfgstr)
encoder_list.append(encoder)
lbl_list.append(lbl)
fnum = 1
# next_pnum = pt.make_pnum_nextgen(nRows=len(encoder_list), nCols=3)
next_pnum = pt.make_pnum_nextgen(nRows=len(encoder_list) + 1,
nCols=3,
start=3)
iconsize = 94
if len(encoder_list) > 3:
iconsize = 64
icon = qreq_.ibs.get_database_icon(max_dsize=(None, iconsize),
aid=qreq_.qaids[0])
score_range = (0, 0.6)
for encoder, lbl in zip(encoder_list, lbl_list):
# encoder.visualize(figtitle=encoder.get_cfgstr(), with_prebayes=False, with_postbayes=False)
encoder._plot_score_support_hist(fnum,
pnum=next_pnum(),
titlesuf='\n' + lbl,
score_range=score_range)
encoder._plot_prebayes(fnum, pnum=next_pnum())
encoder._plot_roc(fnum, pnum=next_pnum())
if icon is not None:
pt.overlay_icon(icon, coords=(1, 0), bbox_alignment=(1, 0))
nonvaried_lbl = ut.get_nonvaried_cfg_lbls(nfs_cfg_list)[0]
figtitle = qreq_.__str__() + '\n' + nonvaried_lbl
pt.set_figtitle(figtitle)
pt.adjust_subplots(hspace=0.5, top=0.92, bottom=0.08, left=0.1, right=0.9)
pt.update_figsize()
pt.plt.tight_layout()