def color_by_nids(graph, unique_nids=None, ibs=None, nid2_color_=None):
""" Colors edges and nodes by nid """
# TODO use ut.color_nodes
import plottool as pt
ensure_graph_nid_labels(graph, unique_nids, ibs=ibs)
node_to_nid = nx.get_node_attributes(graph, 'nid')
unique_nids = ut.unique(node_to_nid.values())
ncolors = len(unique_nids)
if (ncolors) == 1:
unique_colors = [pt.UNKNOWN_PURP]
else:
if nid2_color_ is not None:
unique_colors = pt.distinct_colors(ncolors + len(nid2_color_) * 2)
else:
unique_colors = pt.distinct_colors(ncolors)
# Find edges and aids strictly between two nids
nid_to_color = dict(zip(unique_nids, unique_colors))
if nid2_color_ is not None:
# HACK NEED TO ENSURE COLORS ARE NOT REUSED
nid_to_color.update(nid2_color_)
edge_aids = list(graph.edges())
edge_nids = ut.unflat_take(node_to_nid, edge_aids)
flags = [nids[0] == nids[1] for nids in edge_nids]
flagged_edge_aids = ut.compress(edge_aids, flags)
flagged_edge_nids = ut.compress(edge_nids, flags)
flagged_edge_colors = [nid_to_color[nids[0]] for nids in flagged_edge_nids]
edge_to_color = dict(zip(flagged_edge_aids, flagged_edge_colors))
node_to_color = ut.map_dict_vals(ut.partial(ut.take, nid_to_color),
node_to_nid)
nx.set_edge_attributes(graph, 'color', edge_to_color)
nx.set_node_attributes(graph, 'color', node_to_color)
def color_by_nids(graph, unique_nids=None, ibs=None, nid2_color_=None):
""" Colors edges and nodes by nid """
# TODO use ut.color_nodes
import plottool as pt
ensure_graph_nid_labels(graph, unique_nids, ibs=ibs)
node_to_nid = nx.get_node_attributes(graph, 'nid')
unique_nids = ut.unique(node_to_nid.values())
ncolors = len(unique_nids)
if (ncolors) == 1:
unique_colors = [pt.UNKNOWN_PURP]
else:
if nid2_color_ is not None:
unique_colors = pt.distinct_colors(ncolors + len(nid2_color_) * 2)
else:
unique_colors = pt.distinct_colors(ncolors)
# Find edges and aids strictly between two nids
nid_to_color = dict(zip(unique_nids, unique_colors))
if nid2_color_ is not None:
# HACK NEED TO ENSURE COLORS ARE NOT REUSED
nid_to_color.update(nid2_color_)
edge_aids = list(graph.edges())
edge_nids = ut.unflat_take(node_to_nid, edge_aids)
flags = [nids[0] == nids[1] for nids in edge_nids]
flagged_edge_aids = ut.compress(edge_aids, flags)
flagged_edge_nids = ut.compress(edge_nids, flags)
flagged_edge_colors = [nid_to_color[nids[0]] for nids in flagged_edge_nids]
edge_to_color = dict(zip(flagged_edge_aids, flagged_edge_colors))
node_to_color = ut.map_dict_vals(ut.partial(ut.take, nid_to_color), node_to_nid)
nx.set_edge_attributes(graph, 'color', edge_to_color)
nx.set_node_attributes(graph, 'color', node_to_color)
def make_colorcodes(model):
"""
python -m ibeis.algo.hots.bayes --exec-make_name_model --show
python -m ibeis.algo.hots.bayes --exec-cluster_query --show
python -m ibeis --tf demo_bayesnet --ev :nA=4,nS=2,Na=n0,rand_scores=True --show --verbose
python -m ibeis --tf demo_bayesnet --ev :nA=4,nS=3,Na=n0,rand_scores=True --show --verbose
"""
import plottool as pt
ttype_colors = {}
ttype_scalars = {}
# Hacked in custom colors
if 'name' in model.ttype2_template:
basis = model.ttype2_template['name'].basis
card = len(basis)
colors = pt.distinct_colors(max(card, 10))[:card]
ttype_colors['name'] = colors
ttype_scalars['name'] = np.linspace(0, 1, len(basis))
if 'score' in model.ttype2_template:
cmap_, mn, mx = 'plasma', 0.15, 1.0
_cmap = pt.plt.get_cmap(cmap_)
def cmap(x):
return _cmap((x * mx) + mn)
basis = model.ttype2_template['score'].basis
scalars = np.linspace(0, 1, len(basis))
# scalars = np.linspace(0, 1, 100)
colors = pt.scores_to_color(scalars, cmap_=cmap_, reverse_cmap=False,
cmap_range=(mn, mx))
colors = [pt.lighten_rgb(c, .4) for c in colors]
ttype_scalars['score'] = scalars
ttype_colors['score'] = colors
return ttype_colors, ttype_scalars
def color_nodes(graph, labelattr='label'):
""" Colors edges and nodes by nid """
import plottool as pt
import utool as ut
import networkx as nx
node_to_lbl = nx.get_node_attributes(graph, labelattr)
unique_lbls = ut.unique(node_to_lbl.values())
ncolors = len(unique_lbls)
if (ncolors) == 1:
unique_colors = [pt.NEUTRAL_BLUE]
else:
unique_colors = pt.distinct_colors(ncolors)
# Find edges and aids strictly between two nids
lbl_to_color = dict(zip(unique_lbls, unique_colors))
node_to_color = {node: lbl_to_color[lbl] for node, lbl in node_to_lbl.items()}
nx.set_node_attributes(graph, 'color', node_to_color)
ut.nx_ensure_agraph_color(graph)
def make_colorcodes(model):
"""
python -m ibeis.algo.hots.bayes --exec-make_name_model --show
python -m ibeis.algo.hots.bayes --exec-cluster_query --show
python -m ibeis --tf demo_bayesnet --ev :nA=4,nS=2,Na=n0,rand_scores=True --show --verbose
python -m ibeis --tf demo_bayesnet --ev :nA=4,nS=3,Na=n0,rand_scores=True --show --verbose
"""
import plottool as pt
ttype_colors = {}
ttype_scalars = {}
# Hacked in custom colors
if 'name' in model.ttype2_template:
basis = model.ttype2_template['name'].basis
card = len(basis)
colors = pt.distinct_colors(max(card, 10))[:card]
ttype_colors['name'] = colors
ttype_scalars['name'] = np.linspace(0, 1, len(basis))
if 'score' in model.ttype2_template:
cmap_, mn, mx = 'plasma', 0.15, 1.0
_cmap = pt.plt.get_cmap(cmap_)
def cmap(x):
return _cmap((x * mx) + mn)
basis = model.ttype2_template['score'].basis
scalars = np.linspace(0, 1, len(basis))
# scalars = np.linspace(0, 1, 100)
colors = pt.scores_to_color(scalars,
cmap_=cmap_,
reverse_cmap=False,
cmap_range=(mn, mx))
colors = [pt.lighten_rgb(c, .4) for c in colors]
ttype_scalars['score'] = scalars
ttype_colors['score'] = colors
return ttype_colors, ttype_scalars
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:
print('[matchver] show_page(fulldraw=%r, onlyrows=%r)' % (fulldraw, onlyrows))
else:
print('[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=.7, hue_range=(.05, .95))
self.nid2_color = dict(zip(unique_nids, unique_colors))
row_aids_list = self.get_row_aids_list()
if self.cm is not None:
print("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)
print('nid = %r' % (nid,))
print('self.nid2_color = %s' % (ut.dict_str(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()
#pt.adjust_subplots_safe(top=0.85, hspace=0.03)
hspace = .05 if (self.nCols) > 1 else .1
pt.adjust_subplots_safe(top=0.85, hspace=hspace)
self.draw()
self.show()
if bring_to_front:
self.bring_to_front()
def show_model(model, evidence={}, soft_evidence={}, **kwargs):
"""
References:
http://stackoverflow.com/questions/22207802/pygraphviz-networkx-set-node-level-or-layer
Ignore:
pkg-config --libs-only-L libcgraph
sudo apt-get install libgraphviz-dev -y
sudo apt-get install libgraphviz4 -y
# sudo apt-get install pkg-config
sudo apt-get install libgraphviz-dev
# pip install git+git://github.com/pygraphviz/pygraphviz.git
pip install pygraphviz
python -c "import pygraphviz; print(pygraphviz.__file__)"
sudo pip3 install pygraphviz --install-option="--include-path=/usr/include/graphviz" --install-option="--library-path=/usr/lib/graphviz/"
python3 -c "import pygraphviz; print(pygraphviz.__file__)"
CommandLine:
python -m ibeis.algo.hots.bayes --exec-show_model --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.hots.bayes import * # NOQA
>>> model = '?'
>>> evidence = {}
>>> soft_evidence = {}
>>> result = show_model(model, evidence, soft_evidence)
>>> print(result)
>>> ut.quit_if_noshow()
>>> import plottool as pt
>>> ut.show_if_requested()
"""
if ut.get_argval('--hackmarkov') or ut.get_argval('--hackjunc'):
draw_tree_model(model, **kwargs)
return
import plottool as pt
import networkx as netx
fnum = pt.ensure_fnum(None)
netx_graph = (model)
#netx_graph.graph.setdefault('graph', {})['size'] = '"10,5"'
#netx_graph.graph.setdefault('graph', {})['rankdir'] = 'LR'
pos_dict = get_hacked_pos(netx_graph)
#pos_dict = netx.pygraphviz_layout(netx_graph)
#pos = netx.pydot_layout(netx_graph, prog='dot')
#pos_dict = netx.graphviz_layout(netx_graph)
textprops = {
'family': 'monospace',
'horizontalalignment': 'left',
#'horizontalalignment': 'center',
#'size': 12,
'size': 8,
}
netx_nodes = model.nodes(data=True)
node_key_list = ut.get_list_column(netx_nodes, 0)
pos_list = ut.dict_take(pos_dict, node_key_list)
var2_post = {f.variables[0]: f for f in kwargs.get('factor_list', [])}
prior_text = None
post_text = None
evidence_tas = []
post_tas = []
prior_tas = []
node_color = []
has_infered = evidence or var2_post
if has_infered:
ignore_prior_with_ttype = ['score', 'match']
show_prior = False
else:
ignore_prior_with_ttype = []
#show_prior = True
show_prior = False
dpy = 5
dbx, dby = (20, 20)
takw1 = {'bbox_align': (.5, 0), 'pos_offset': [0, dpy], 'bbox_offset': [dbx, dby]}
takw2 = {'bbox_align': (.5, 1), 'pos_offset': [0, -dpy], 'bbox_offset': [-dbx, -dby]}
name_colors = pt.distinct_colors(max(model.num_names, 10))
name_colors = name_colors[:model.num_names]
#cmap_ = 'hot' #mx = 0.65 #mn = 0.15
cmap_, mn, mx = 'plasma', 0.15, 1.0
_cmap = pt.plt.get_cmap(cmap_)
def cmap(x):
return _cmap((x * mx) + mn)
for node, pos in zip(netx_nodes, pos_list):
variable = node[0]
cpd = model.var2_cpd[variable]
prior_marg = (cpd if cpd.evidence is None else
cpd.marginalize(cpd.evidence, inplace=False))
show_evidence = variable in evidence
show_prior = cpd.ttype not in ignore_prior_with_ttype
show_post = variable in var2_post
show_prior |= cpd.ttype not in ignore_prior_with_ttype
post_marg = None
if show_post:
post_marg = var2_post[variable]
def get_name_color(phi):
order = phi.values.argsort()[::-1]
if len(order) < 2:
dist_next = phi.values[order[0]]
else:
dist_next = phi.values[order[0]] - phi.values[order[1]]
dist_total = (phi.values[order[0]])
confidence = (dist_total * dist_next) ** (2.5 / 4)
#print('confidence = %r' % (confidence,))
color = name_colors[order[0]]
color = pt.color_funcs.desaturate_rgb(color, 1 - confidence)
color = np.array(color)
return color
if variable in evidence:
if cpd.ttype == 'score':
cmap_index = evidence[variable] / (cpd.variable_card - 1)
color = cmap(cmap_index)
color = pt.lighten_rgb(color, .4)
color = np.array(color)
node_color.append(color)
elif cpd.ttype == 'name':
color = name_colors[evidence[variable]]
color = np.array(color)
node_color.append(color)
else:
color = pt.FALSE_RED
node_color.append(color)
#elif variable in soft_evidence:
# color = pt.LIGHT_PINK
# show_prior = True
# color = get_name_color(prior_marg)
# node_color.append(color)
else:
if cpd.ttype == 'name' and post_marg is not None:
color = get_name_color(post_marg)
node_color.append(color)
elif cpd.ttype == 'match' and post_marg is not None:
color = cmap(post_marg.values[1])
color = pt.lighten_rgb(color, .4)
color = np.array(color)
node_color.append(color)
else:
#color = pt.WHITE
color = pt.NEUTRAL
node_color.append(color)
if show_prior:
if variable in soft_evidence:
prior_color = pt.LIGHT_PINK
else:
prior_color = None
prior_text = pgm_ext.make_factor_text(prior_marg, 'prior')
prior_tas.append(dict(text=prior_text, pos=pos, color=prior_color, **takw2))
if show_evidence:
_takw1 = takw1
if cpd.ttype == 'score':
_takw1 = takw2
evidence_text = cpd.variable_statenames[evidence[variable]]
if isinstance(evidence_text, int):
evidence_text = '%d/%d' % (evidence_text + 1, cpd.variable_card)
evidence_tas.append(dict(text=evidence_text, pos=pos, color=color, **_takw1))
if show_post:
_takw1 = takw1
if cpd.ttype == 'match':
_takw1 = takw2
post_text = pgm_ext.make_factor_text(post_marg, 'post')
post_tas.append(dict(text=post_text, pos=pos, color=None, **_takw1))
def trnps_(dict_list):
""" tranpose dict list """
list_dict = ut.ddict(list)
for dict_ in dict_list:
for key, val in dict_.items():
list_dict[key + '_list'].append(val)
return list_dict
takw1_ = trnps_(post_tas + evidence_tas)
takw2_ = trnps_(prior_tas)
# Draw graph
if has_infered:
pnum1 = (3, 1, (slice(0, 2), 0))
else:
pnum1 = None
fig = pt.figure(fnum=fnum, pnum=pnum1, doclf=True) # NOQA
ax = pt.gca()
#print('node_color = %s' % (ut.repr3(node_color),))
drawkw = dict(pos=pos_dict, ax=ax, with_labels=True, node_size=1500,
node_color=node_color)
netx.draw(netx_graph, **drawkw)
hacks = []
if len(post_tas + evidence_tas):
hacks.append(pt.draw_text_annotations(textprops=textprops, **takw1_))
if prior_tas:
hacks.append(pt.draw_text_annotations(textprops=textprops, **takw2_))
xmin, ymin = np.array(pos_list).min(axis=0)
xmax, ymax = np.array(pos_list).max(axis=0)
num_annots = len(model.ttype2_cpds['name'])
if num_annots > 4:
ax.set_xlim((xmin - 40, xmax + 40))
ax.set_ylim((ymin - 50, ymax + 50))
fig.set_size_inches(30, 7)
else:
ax.set_xlim((xmin - 42, xmax + 42))
ax.set_ylim((ymin - 50, ymax + 50))
fig.set_size_inches(23, 7)
fig = pt.gcf()
title = 'num_names=%r, num_annots=%r' % (model.num_names, num_annots,)
map_assign = kwargs.get('map_assign', None)
top_assignments = kwargs.get('top_assignments', None)
if top_assignments is not None:
map_assign, map_prob = top_assignments[0]
if map_assign is not None:
def word_insert(text):
return '' if len(text) == 0 else text + ' '
title += '\n%sMAP: ' % (word_insert(kwargs.get('method', '')))
title += map_assign + ' @' + '%.2f%%' % (100 * map_prob,)
if kwargs.get('show_title', True):
pt.set_figtitle(title, size=14)
for hack in hacks:
hack()
# Hack in colorbars
if has_infered:
pt.colorbar(np.linspace(0, 1, len(name_colors)), name_colors, lbl='name',
ticklabels=model.ttype2_template['name'].basis, ticklocation='left')
basis = model.ttype2_template['score'].basis
scalars = np.linspace(0, 1, len(basis))
scalars = np.linspace(0, 1, 100)
colors = pt.scores_to_color(scalars, cmap_=cmap_, reverse_cmap=False,
cmap_range=(mn, mx))
colors = [pt.lighten_rgb(c, .4) for c in colors]
if ut.list_type(basis) is int:
pt.colorbar(scalars, colors, lbl='score', ticklabels=np.array(basis) + 1)
else:
pt.colorbar(scalars, colors, lbl='score', ticklabels=basis)
#print('basis = %r' % (basis,))
# Draw probability hist
if has_infered and top_assignments is not None:
bin_labels = ut.get_list_column(top_assignments, 0)
bin_vals = ut.get_list_column(top_assignments, 1)
# bin_labels = ['\n'.join(ut.textwrap.wrap(_lbl, width=30)) for _lbl in bin_labels]
pt.draw_histogram(bin_labels, bin_vals, fnum=fnum, pnum=(3, 8, (2, slice(4, None))),
transpose=True,
use_darkbackground=False,
#xtick_rotation=-10,
ylabel='Prob', xlabel='assignment')
pt.set_title('Assignment probabilities')
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:
print('[matchver] show_page(fulldraw=%r, onlyrows=%r)' %
(fulldraw, onlyrows))
else:
print('[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=.7,
hue_range=(.05, .95))
self.nid2_color = dict(zip(unique_nids, unique_colors))
row_aids_list = self.get_row_aids_list()
if self.cm is not None:
print("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)
print('nid = %r' % (nid, ))
print('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 = .05 if (self.nCols) > 1 else .1
subplotspar = {
'left': .1,
'right': .9,
'top': .85,
'bottom': .1,
'wspace': .3,
'hspace': hspace,
}
pt.adjust_subplots(**subplotspar)
self.draw()
self.show()
if bring_to_front:
self.bring_to_front()
def show_qres(ibs, cm, qreq_=None, **kwargs):
"""
Display Query Result Logic
Defaults to: query chip, groundtruth matches, and top matches
Args:
ibs (ibeis.IBEISController): ibeis controller object
cm (ibeis.ChipMatch): object of feature correspondences and scores
Kwargs:
in_image (bool) show result in image view if True else chip view
annot_mode (int):
if annot_mode == 0, then draw lines and ellipse
elif annot_mode == 1, then dont draw lines or ellipse
elif annot_mode == 2, then draw only lines
See: viz_matches.show_name_matches, viz_helpers.get_query_text
Returns:
mpl.Figure: fig
CommandLine:
./main.py --query 1 -y --db PZ_MTEST --noshow-qtres
python -m ibeis.viz.viz_qres --test-show_qres --show
python -m ibeis.viz.viz_qres --test-show_qres --show --top-aids=10 --db=PZ_MTEST --sidebyside --annot_mode=0 --notitle --no-viz_name_score --qaids=5 --max_nCols=2 --adjust=.01,.01,.01
python -m ibeis.viz.viz_qres --test-show_qres --show --top-aids=10 --db=PZ_MTEST --sidebyside --annot_mode=0 --notitle --no-viz_name_score --qaids=5 --max_nCols=2 --adjust=.01,.01,.01
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.viz.viz_qres import * # NOQA
>>> import plottool as pt
>>> ibs, cm, qreq_, kwargs = testdata_show_qres()
>>> # execute function
>>> fig = show_qres(ibs, cm, show_query=False, qreq_=qreq_, **kwargs)
>>> # verify results
>>> #fig.show()
>>> pt.show_if_requested()
"""
#ut.print_dict(kwargs)
annot_mode = kwargs.get('annot_mode', 1) % 3 # this is toggled
figtitle = kwargs.get('figtitle', '')
make_figtitle = kwargs.get('make_figtitle', False)
aug = kwargs.get('aug', '')
top_aids = kwargs.get('top_aids', DEFAULT_NTOP)
gt_aids = kwargs.get('gt_aids', [])
all_kpts = kwargs.get('all_kpts', False)
show_query = kwargs.get('show_query', False)
in_image = kwargs.get('in_image', False)
sidebyside = kwargs.get('sidebyside', True)
#name_scoring = kwargs.get('name_scoring', False)
viz_name_score = kwargs.get('viz_name_score', qreq_ is not None)
max_nCols = kwargs.get('max_nCols', None)
failed_to_match = kwargs.get('failed_to_match', False)
fnum = pt.ensure_fnum(kwargs.get('fnum', None))
if ut.VERBOSE and ut.NOT_QUIET:
print('query_info = ' + ut.obj_str(ibs.get_annot_info(cm.qaid,
default=True,
gname=False,
name=False,
notes=False,
exemplar=False),
nl=4))
print('top_aids_info = ' +
ut.obj_str(ibs.get_annot_info(top_aids,
default=True,
gname=False,
name=False,
notes=False,
exemplar=False,
reference_aid=cm.qaid),
nl=4))
if make_figtitle is True:
pass
#figtitle = cm.make_title(pack=True)
#figtitle
fig = pt.figure(fnum=fnum, docla=True, doclf=True)
if isinstance(top_aids, int):
#if isinstance(cm, chip_match.ChipMatch):
top_aids = cm.get_top_aids(top_aids)
#else:
# top_aids = cm.get_top_aids(num=top_aids, name_scoring=name_scoring, ibs=ibs)
if failed_to_match:
# HACK to visually indicate failure to match in analysis
top_aids = [None] + top_aids
nTop = len(top_aids)
if max_nCols is None:
max_nCols = 5
if nTop in [6, 7]:
max_nCols = 3
if nTop in [8]:
max_nCols = 4
try:
assert len(list(set(top_aids).intersection(
set(gt_aids)))) == 0, ('gts should be missed. not in top')
except AssertionError as ex:
ut.printex(ex, keys=['top_aids', 'gt_aids'])
raise
if ut.DEBUG2:
print(cm.get_inspect_str())
#--------------------------------------------------
# Get grid / cell information to build subplot grid
#--------------------------------------------------
# Show query or not
nQuerySubplts = 1 if show_query else 0
# The top row is given slots for ground truths and querys
# all aids in gt_aids should not be in top aids
nGtSubplts = nQuerySubplts + (0 if gt_aids is None else len(gt_aids))
# The bottom rows are for the top results
nTopNSubplts = nTop
nTopNCols = min(max_nCols, nTopNSubplts)
nGTCols = min(max_nCols, nGtSubplts)
nGTCols = max(nGTCols, nTopNCols)
nTopNCols = nGTCols
# Get number of rows to show groundtruth
nGtRows = 0 if nGTCols == 0 else int(np.ceil(nGtSubplts / nGTCols))
# Get number of rows to show results
nTopNRows = 0 if nTopNCols == 0 else int(np.ceil(nTopNSubplts / nTopNCols))
nGtCells = nGtRows * nGTCols
# Total number of rows
nRows = nTopNRows + nGtRows
DEBUG_SHOW_QRES = 0
if DEBUG_SHOW_QRES:
allgt_aids = ibs.get_annot_groundtruth(cm.qaid)
nSelGt = len(gt_aids)
nAllGt = len(allgt_aids)
print('[show_qres]========================')
print('[show_qres]----------------')
print('[show_qres] * annot_mode=%r' % (annot_mode, ))
print('[show_qres] #nTop=%r #missed_gts=%r/%r' %
(nTop, nSelGt, nAllGt))
print('[show_qres] * -----')
print('[show_qres] * nRows=%r' % (nRows, ))
print('[show_qres] * nGtSubplts=%r' % (nGtSubplts, ))
print('[show_qres] * nTopNSubplts=%r' % (nTopNSubplts, ))
print('[show_qres] * nQuerySubplts=%r' % (nQuerySubplts, ))
print('[show_qres] * -----')
print('[show_qres] * nGTCols=%r' % (nGTCols, ))
print('[show_qres] * -----')
print('[show_qres] * fnum=%r' % (fnum, ))
print('[show_qres] * figtitle=%r' % (figtitle, ))
print('[show_qres] * max_nCols=%r' % (max_nCols, ))
print('[show_qres] * show_query=%r' % (show_query, ))
print('[show_qres] * kwargs=%s' % (ut.dict_str(kwargs), ))
# HACK:
_color_list = pt.distinct_colors(nTop)
aid2_color = {aid: _color_list[ox] for ox, aid in enumerate(top_aids)}
ranked_aids = cm.get_top_aids()
# Helpers
def _show_query_fn(plotx_shift, rowcols):
""" helper for show_qres """
plotx = plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
#print('[viz] Plotting Query: pnum=%r' % (pnum,))
_kwshow = dict(draw_kpts=annot_mode)
_kwshow.update(kwargs)
_kwshow['prefix'] = 'q'
_kwshow['pnum'] = pnum
_kwshow['aid2_color'] = aid2_color
_kwshow['draw_ell'] = annot_mode >= 1
viz_chip.show_chip(ibs, cm.qaid, annote=False, qreq_=qreq_, **_kwshow)
def _plot_matches_aids(aid_list, plotx_shift, rowcols):
""" helper for show_qres to draw many aids """
_kwshow = dict(draw_ell=annot_mode,
draw_pts=False,
draw_lines=annot_mode,
ell_alpha=.5,
all_kpts=all_kpts)
_kwshow.update(kwargs)
_kwshow['fnum'] = fnum
_kwshow['in_image'] = in_image
if sidebyside:
# Draw each match side by side the query
_kwshow['draw_ell'] = annot_mode == 1
_kwshow['draw_lines'] = annot_mode >= 1
else:
#print('annot_mode = %r' % (annot_mode,))
_kwshow['draw_ell'] = annot_mode == 1
#_kwshow['draw_pts'] = annot_mode >= 1
#_kwshow['draw_lines'] = False
_kwshow['show_query'] = False
def _show_matches_fn(aid, orank, pnum):
""" Helper function for drawing matches to one aid """
aug = 'rank=%r\n' % orank
_kwshow['pnum'] = pnum
_kwshow['title_aug'] = aug
#draw_ell = annot_mode == 1
#draw_lines = annot_mode >= 1
# If we already are showing the query dont show it here
if sidebyside:
# Draw each match side by side the query
if viz_name_score:
cm.show_single_namematch(qreq_, ibs.get_annot_nids(aid),
**_kwshow)
else:
_kwshow['draw_border'] = False
_kwshow['draw_lbl'] = False
_kwshow['notitle'] = True
_kwshow['vert'] = False
cm.show_single_annotmatch(qreq_, aid, **_kwshow)
#viz_matches.show_matches(ibs, cm, aid, qreq_=qreq_, **_kwshow)
else:
# Draw each match by themselves
data_config2_ = None if qreq_ is None else qreq_.get_external_data_config2(
)
#_kwshow['draw_border'] = kwargs.get('draw_border', True)
#_kwshow['notitle'] = ut.get_argflag(('--no-title', '--notitle'))
viz_chip.show_chip(ibs,
aid,
annote=False,
notitle=True,
data_config2_=data_config2_,
**_kwshow)
if DEBUG_SHOW_QRES:
print('[show_qres()] Plotting Chips %s:' %
vh.get_aidstrs(aid_list))
if aid_list is None:
return
# Do lazy load before show
#data_config2_ = None if qreq_ is None else qreq_.get_external_data_config2()
tblhack = getattr(qreq_, 'tablename', None)
# HACK FOR HUMPBACKS
# (Also in viz_matches)
if tblhack == 'vsone' or (qreq_ is not None and not qreq_._isnewreq):
# precompute
pass
#ibs.get_annot_chips(aid_list, config2_=data_config2_, ensure=True)
#ibs.get_annot_kpts(aid_list, config2_=data_config2_, ensure=True)
for ox, aid in enumerate(aid_list):
plotx = ox + plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
oranks = np.where(ranked_aids == aid)[0]
# This pair has no matches between them.
if len(oranks) == 0:
orank = -1
if aid is None:
pt.imshow_null('Failed to find matches\nfor qaid=%r' %
(cm.qaid),
fnum=fnum,
pnum=pnum,
fontsize=18)
else:
_show_matches_fn(aid, orank, pnum)
#if DEBUG_SHOW_QRES:
# print('skipping pnum=%r' % (pnum,))
continue
if DEBUG_SHOW_QRES:
print('pnum=%r' % (pnum, ))
orank = oranks[0] + 1
_show_matches_fn(aid, orank, pnum)
shift_topN = nGtCells
if nGtSubplts == 1:
nGTCols = 1
if nRows == 0:
pt.imshow_null('[viz_qres] No matches. nRows=0', fnum=fnum)
else:
fig = pt.figure(fnum=fnum,
pnum=(nRows, nGTCols, 1),
docla=True,
doclf=True)
pt.plt.subplot(nRows, nGTCols, 1)
# Plot Query
if show_query:
_show_query_fn(0, (nRows, nGTCols))
# Plot Ground Truth (if given)
_plot_matches_aids(gt_aids, nQuerySubplts, (nRows, nGTCols))
# Plot Results
_plot_matches_aids(top_aids, shift_topN, (nRows, nTopNCols))
figtitle += aug
if failed_to_match:
figtitle += '\n No matches found'
incanvas = kwargs.get('with_figtitle', not vh.NO_LBL_OVERRIDE)
pt.set_figtitle(figtitle, incanvas=incanvas)
# Result Interaction
return fig
def show_qres(ibs, cm, qreq_=None, **kwargs):
"""
Display Query Result Logic
Defaults to: query chip, groundtruth matches, and top matches
Args:
ibs (ibeis.IBEISController): ibeis controller object
cm (ibeis.ChipMatch): object of feature correspondences and scores
Kwargs:
in_image (bool) show result in image view if True else chip view
annot_mode (int):
if annot_mode == 0, then draw lines and ellipse
elif annot_mode == 1, then dont draw lines or ellipse
elif annot_mode == 2, then draw only lines
See: viz_matches.show_name_matches, viz_helpers.get_query_text
Returns:
mpl.Figure: fig
CommandLine:
./main.py --query 1 -y --db PZ_MTEST --noshow-qtres
python -m ibeis.viz.viz_qres --test-show_qres --show
python -m ibeis.viz.viz_qres --test-show_qres --show --top-aids=10 --db=PZ_MTEST --sidebyside --annot_mode=0 --notitle --no-viz_name_score --qaids=5 --max_nCols=2 --adjust=.01,.01,.01
python -m ibeis.viz.viz_qres --test-show_qres --show --top-aids=10 --db=PZ_MTEST --sidebyside --annot_mode=0 --notitle --no-viz_name_score --qaids=5 --max_nCols=2 --adjust=.01,.01,.01
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.viz.viz_qres import * # NOQA
>>> import plottool as pt
>>> ibs, cm, qreq_, kwargs = testdata_show_qres()
>>> # execute function
>>> fig = show_qres(ibs, cm, show_query=False, qreq_=qreq_, **kwargs)
>>> # verify results
>>> #fig.show()
>>> pt.show_if_requested()
"""
#ut.print_dict(kwargs)
annot_mode = kwargs.get('annot_mode', 1) % 3 # this is toggled
figtitle = kwargs.get('figtitle', '')
make_figtitle = kwargs.get('make_figtitle', False)
aug = kwargs.get('aug', '')
top_aids = kwargs.get('top_aids', DEFAULT_NTOP)
gt_aids = kwargs.get('gt_aids', [])
all_kpts = kwargs.get('all_kpts', False)
show_query = kwargs.get('show_query', False)
in_image = kwargs.get('in_image', False)
sidebyside = kwargs.get('sidebyside', True)
#name_scoring = kwargs.get('name_scoring', False)
viz_name_score = kwargs.get('viz_name_score', qreq_ is not None)
max_nCols = kwargs.get('max_nCols', None)
failed_to_match = kwargs.get('failed_to_match', False)
fnum = pt.ensure_fnum(kwargs.get('fnum', None))
if ut.VERBOSE and ut.NOT_QUIET:
print('query_info = ' + ut.obj_str(
ibs.get_annot_info(cm.qaid, default=True, gname=False, name=False, notes=False,
exemplar=False), nl=4))
print('top_aids_info = ' + ut.obj_str(
ibs.get_annot_info(top_aids, default=True, gname=False, name=False, notes=False,
exemplar=False, reference_aid=cm.qaid), nl=4))
if make_figtitle is True:
pass
#figtitle = cm.make_title(pack=True)
#figtitle
fig = pt.figure(fnum=fnum, docla=True, doclf=True)
if isinstance(top_aids, int):
#if isinstance(cm, chip_match.ChipMatch):
top_aids = cm.get_top_aids(top_aids)
#else:
# top_aids = cm.get_top_aids(num=top_aids, name_scoring=name_scoring, ibs=ibs)
if failed_to_match:
# HACK to visually indicate failure to match in analysis
top_aids = [None] + top_aids
nTop = len(top_aids)
if max_nCols is None:
max_nCols = 5
if nTop in [6, 7]:
max_nCols = 3
if nTop in [8]:
max_nCols = 4
try:
assert len(list(set(top_aids).intersection(set(gt_aids)))) == 0, (
'gts should be missed. not in top')
except AssertionError as ex:
ut.printex(ex, keys=['top_aids', 'gt_aids'])
raise
if ut.DEBUG2:
print(cm.get_inspect_str())
#--------------------------------------------------
# Get grid / cell information to build subplot grid
#--------------------------------------------------
# Show query or not
nQuerySubplts = 1 if show_query else 0
# The top row is given slots for ground truths and querys
# all aids in gt_aids should not be in top aids
nGtSubplts = nQuerySubplts + (0 if gt_aids is None else len(gt_aids))
# The bottom rows are for the top results
nTopNSubplts = nTop
nTopNCols = min(max_nCols, nTopNSubplts)
nGTCols = min(max_nCols, nGtSubplts)
nGTCols = max(nGTCols, nTopNCols)
nTopNCols = nGTCols
# Get number of rows to show groundtruth
nGtRows = 0 if nGTCols == 0 else int(np.ceil(nGtSubplts / nGTCols))
# Get number of rows to show results
nTopNRows = 0 if nTopNCols == 0 else int(np.ceil(nTopNSubplts / nTopNCols))
nGtCells = nGtRows * nGTCols
# Total number of rows
nRows = nTopNRows + nGtRows
DEBUG_SHOW_QRES = 0
if DEBUG_SHOW_QRES:
allgt_aids = ibs.get_annot_groundtruth(cm.qaid)
nSelGt = len(gt_aids)
nAllGt = len(allgt_aids)
print('[show_qres]========================')
print('[show_qres]----------------')
print('[show_qres] * annot_mode=%r' % (annot_mode,))
print('[show_qres] #nTop=%r #missed_gts=%r/%r' % (nTop, nSelGt, nAllGt))
print('[show_qres] * -----')
print('[show_qres] * nRows=%r' % (nRows,))
print('[show_qres] * nGtSubplts=%r' % (nGtSubplts,))
print('[show_qres] * nTopNSubplts=%r' % (nTopNSubplts,))
print('[show_qres] * nQuerySubplts=%r' % (nQuerySubplts,))
print('[show_qres] * -----')
print('[show_qres] * nGTCols=%r' % (nGTCols,))
print('[show_qres] * -----')
print('[show_qres] * fnum=%r' % (fnum,))
print('[show_qres] * figtitle=%r' % (figtitle,))
print('[show_qres] * max_nCols=%r' % (max_nCols,))
print('[show_qres] * show_query=%r' % (show_query,))
print('[show_qres] * kwargs=%s' % (ut.dict_str(kwargs),))
# HACK:
_color_list = pt.distinct_colors(nTop)
aid2_color = {aid: _color_list[ox] for ox, aid in enumerate(top_aids)}
ranked_aids = cm.get_top_aids()
# Helpers
def _show_query_fn(plotx_shift, rowcols):
""" helper for show_qres """
plotx = plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
#print('[viz] Plotting Query: pnum=%r' % (pnum,))
_kwshow = dict(draw_kpts=annot_mode)
_kwshow.update(kwargs)
_kwshow['prefix'] = 'q'
_kwshow['pnum'] = pnum
_kwshow['aid2_color'] = aid2_color
_kwshow['draw_ell'] = annot_mode >= 1
viz_chip.show_chip(ibs, cm.qaid, annote=False, qreq_=qreq_, **_kwshow)
def _plot_matches_aids(aid_list, plotx_shift, rowcols):
""" helper for show_qres to draw many aids """
_kwshow = dict(draw_ell=annot_mode, draw_pts=False, draw_lines=annot_mode,
ell_alpha=.5, all_kpts=all_kpts)
_kwshow.update(kwargs)
_kwshow['fnum'] = fnum
_kwshow['in_image'] = in_image
if sidebyside:
# Draw each match side by side the query
_kwshow['draw_ell'] = annot_mode == 1
_kwshow['draw_lines'] = annot_mode >= 1
else:
#print('annot_mode = %r' % (annot_mode,))
_kwshow['draw_ell'] = annot_mode == 1
#_kwshow['draw_pts'] = annot_mode >= 1
#_kwshow['draw_lines'] = False
_kwshow['show_query'] = False
def _show_matches_fn(aid, orank, pnum):
""" Helper function for drawing matches to one aid """
aug = 'rank=%r\n' % orank
_kwshow['pnum'] = pnum
_kwshow['title_aug'] = aug
#draw_ell = annot_mode == 1
#draw_lines = annot_mode >= 1
# If we already are showing the query dont show it here
if sidebyside:
# Draw each match side by side the query
if viz_name_score:
cm.show_single_namematch(qreq_, ibs.get_annot_nids(aid), **_kwshow)
else:
_kwshow['draw_border'] = False
_kwshow['draw_lbl'] = False
_kwshow['notitle'] = True
_kwshow['vert'] = False
cm.show_single_annotmatch(qreq_, aid, **_kwshow)
#viz_matches.show_matches(ibs, cm, aid, qreq_=qreq_, **_kwshow)
else:
# Draw each match by themselves
data_config2_ = None if qreq_ is None else qreq_.get_external_data_config2()
#_kwshow['draw_border'] = kwargs.get('draw_border', True)
#_kwshow['notitle'] = ut.get_argflag(('--no-title', '--notitle'))
viz_chip.show_chip(ibs, aid, annote=False, notitle=True,
data_config2_=data_config2_, **_kwshow)
if DEBUG_SHOW_QRES:
print('[show_qres()] Plotting Chips %s:' % vh.get_aidstrs(aid_list))
if aid_list is None:
return
# Do lazy load before show
#data_config2_ = None if qreq_ is None else qreq_.get_external_data_config2()
tblhack = getattr(qreq_, 'tablename', None)
# HACK FOR HUMPBACKS
# (Also in viz_matches)
if tblhack == 'vsone' or (qreq_ is not None and not qreq_._isnewreq):
# precompute
pass
#ibs.get_annot_chips(aid_list, config2_=data_config2_, ensure=True)
#ibs.get_annot_kpts(aid_list, config2_=data_config2_, ensure=True)
for ox, aid in enumerate(aid_list):
plotx = ox + plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
oranks = np.where(ranked_aids == aid)[0]
# This pair has no matches between them.
if len(oranks) == 0:
orank = -1
if aid is None:
pt.imshow_null('Failed to find matches\nfor qaid=%r' % (cm.qaid), fnum=fnum, pnum=pnum, fontsize=18)
else:
_show_matches_fn(aid, orank, pnum)
#if DEBUG_SHOW_QRES:
# print('skipping pnum=%r' % (pnum,))
continue
if DEBUG_SHOW_QRES:
print('pnum=%r' % (pnum,))
orank = oranks[0] + 1
_show_matches_fn(aid, orank, pnum)
shift_topN = nGtCells
if nGtSubplts == 1:
nGTCols = 1
if nRows == 0:
pt.imshow_null('[viz_qres] No matches. nRows=0', fnum=fnum)
else:
fig = pt.figure(fnum=fnum, pnum=(nRows, nGTCols, 1), docla=True, doclf=True)
pt.plt.subplot(nRows, nGTCols, 1)
# Plot Query
if show_query:
_show_query_fn(0, (nRows, nGTCols))
# Plot Ground Truth (if given)
_plot_matches_aids(gt_aids, nQuerySubplts, (nRows, nGTCols))
# Plot Results
_plot_matches_aids(top_aids, shift_topN, (nRows, nTopNCols))
figtitle += aug
if failed_to_match:
figtitle += '\n No matches found'
incanvas = kwargs.get('with_figtitle', not vh.NO_LBL_OVERRIDE)
pt.set_figtitle(figtitle, incanvas=incanvas)
# Result Interaction
return fig
def show_coverage_grid(num_rows, num_cols, subbin_xy_arr,
neighbor_bin_centers, neighbor_bin_weights,
neighbor_bin_indices, fnum=None, pnum=None):
"""
visualizes the voting scheme on the grid. (not a mask, and no max)
"""
import plottool as pt
import vtool as vt
import matplotlib as mpl
if fnum is None:
fnum = pt.next_fnum()
fig = pt.figure(fnum, pnum=pnum)
ax = fig.gca()
x_edge_indices = np.arange(num_cols)
y_edge_indices = np.arange(num_rows)
x_center_indices = vt.hist_edges_to_centers(x_edge_indices)
y_center_indices = vt.hist_edges_to_centers(y_edge_indices)
x_center_grid, y_center_grid = np.meshgrid(x_center_indices, y_center_indices)
ax.set_xticks(x_edge_indices)
ax.set_yticks(y_edge_indices)
# Plot keypoint loc
ax.scatter(subbin_xy_arr[0], subbin_xy_arr[1], marker='o')
# Plot Weighted Lines to Subbin
pt_colors = pt.distinct_colors(len(subbin_xy_arr.T))
segment_list = []
color_list = []
for subbin_centers, subbin_weights in zip(neighbor_bin_centers,
neighbor_bin_weights):
for pt_xys, center_xys, weight, color in zip(subbin_xy_arr.T, subbin_centers,
subbin_weights, pt_colors):
# Adjsut weight to alpha for easier visualization
alpha = weight
INCRESE_ALPHA_VISIBILITY = True
if INCRESE_ALPHA_VISIBILITY:
min_viz_alpha = .05
alpha = alpha * (1.0 - min_viz_alpha) + min_viz_alpha
alpha **= 1.0
#pt.plots.colorline(
segment = np.vstack((pt_xys, center_xys))
segment_list.append(segment)
# Alpha becomes part of the colors
color_list.append(list(color) + [alpha])
# DO NOT USE PLOT VERY SLOW
#ax.plot(*segment.T, color=color, alpha=alpha, lw=3)
ax = pt.gca()
# Plot all segments in single line collection for speed
# solid | dashed | dashdot | dotted
lc = mpl.collections.LineCollection(segment_list, colors=color_list, linewidth=3, linestyles='solid')
ax.add_collection(lc)
# Plot Grid Center
num_cells = num_cols * num_rows
grid_alpha = min(.4, max(1 - (num_cells / 500), .1))
grid_color = [.6, .6, .6, grid_alpha]
#print(grid_color)
# Plot grid cetner
ax.scatter(x_center_grid, y_center_grid, marker='.', color=grid_color,
s=grid_alpha)
ax.set_xlim(0, num_cols - 1)
ax.set_ylim(0, num_rows - 1)
#-----
pt.dark_background()
ax.grid(True, color=[.3, .3, .3])
ax.set_xticklabels([])
ax.set_yticklabels([])
def show_model(model, evidence={}, soft_evidence={}, **kwargs):
"""
References:
http://stackoverflow.com/questions/22207802/pygraphviz-networkx-set-node-level-or-layer
Ignore:
pkg-config --libs-only-L libcgraph
sudo apt-get install libgraphviz-dev -y
sudo apt-get install libgraphviz4 -y
# sudo apt-get install pkg-config
sudo apt-get install libgraphviz-dev
# pip install git+git://github.com/pygraphviz/pygraphviz.git
pip install pygraphviz
python -c "import pygraphviz; print(pygraphviz.__file__)"
sudo pip3 install pygraphviz --install-option="--include-path=/usr/include/graphviz" --install-option="--library-path=/usr/lib/graphviz/"
python3 -c "import pygraphviz; print(pygraphviz.__file__)"
CommandLine:
python -m ibeis.algo.hots.bayes --exec-show_model --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.hots.bayes import * # NOQA
>>> model = '?'
>>> evidence = {}
>>> soft_evidence = {}
>>> result = show_model(model, evidence, soft_evidence)
>>> print(result)
>>> ut.quit_if_noshow()
>>> import plottool as pt
>>> ut.show_if_requested()
"""
if ut.get_argval('--hackmarkov') or ut.get_argval('--hackjunc'):
draw_tree_model(model, **kwargs)
return
import plottool as pt
import networkx as netx
fnum = pt.ensure_fnum(None)
netx_graph = (model)
#netx_graph.graph.setdefault('graph', {})['size'] = '"10,5"'
#netx_graph.graph.setdefault('graph', {})['rankdir'] = 'LR'
pos_dict = get_hacked_pos(netx_graph)
#pos_dict = netx.nx_agraph.pygraphviz_layout(netx_graph)
#pos = netx.nx_agraph.nx_pydot.pydot_layout(netx_graph, prog='dot')
#pos_dict = netx.nx_agraph.graphviz_layout(netx_graph)
textprops = {
'family': 'monospace',
'horizontalalignment': 'left',
#'horizontalalignment': 'center',
#'size': 12,
'size': 8,
}
netx_nodes = model.nodes(data=True)
node_key_list = ut.get_list_column(netx_nodes, 0)
pos_list = ut.dict_take(pos_dict, node_key_list)
var2_post = {f.variables[0]: f for f in kwargs.get('factor_list', [])}
prior_text = None
post_text = None
evidence_tas = []
post_tas = []
prior_tas = []
node_color = []
has_inferred = evidence or var2_post
if has_inferred:
ignore_prior_with_ttype = [SCORE_TTYPE, MATCH_TTYPE]
show_prior = False
else:
ignore_prior_with_ttype = []
#show_prior = True
show_prior = False
dpy = 5
dbx, dby = (20, 20)
takw1 = {
'bbox_align': (.5, 0),
'pos_offset': [0, dpy],
'bbox_offset': [dbx, dby]
}
takw2 = {
'bbox_align': (.5, 1),
'pos_offset': [0, -dpy],
'bbox_offset': [-dbx, -dby]
}
name_colors = pt.distinct_colors(max(model.num_names, 10))
name_colors = name_colors[:model.num_names]
#cmap_ = 'hot' #mx = 0.65 #mn = 0.15
cmap_, mn, mx = 'plasma', 0.15, 1.0
_cmap = pt.plt.get_cmap(cmap_)
def cmap(x):
return _cmap((x * mx) + mn)
for node, pos in zip(netx_nodes, pos_list):
variable = node[0]
cpd = model.var2_cpd[variable]
prior_marg = (cpd if cpd.evidence is None else cpd.marginalize(
cpd.evidence, inplace=False))
show_evidence = variable in evidence
show_prior = cpd.ttype not in ignore_prior_with_ttype
show_post = variable in var2_post
show_prior |= cpd.ttype not in ignore_prior_with_ttype
post_marg = None
if show_post:
post_marg = var2_post[variable]
def get_name_color(phi):
order = phi.values.argsort()[::-1]
if len(order) < 2:
dist_next = phi.values[order[0]]
else:
dist_next = phi.values[order[0]] - phi.values[order[1]]
dist_total = (phi.values[order[0]])
confidence = (dist_total * dist_next)**(2.5 / 4)
#print('confidence = %r' % (confidence,))
color = name_colors[order[0]]
color = pt.color_funcs.desaturate_rgb(color, 1 - confidence)
color = np.array(color)
return color
if variable in evidence:
if cpd.ttype == SCORE_TTYPE:
cmap_index = evidence[variable] / (cpd.variable_card - 1)
color = cmap(cmap_index)
color = pt.lighten_rgb(color, .4)
color = np.array(color)
node_color.append(color)
elif cpd.ttype == NAME_TTYPE:
color = name_colors[evidence[variable]]
color = np.array(color)
node_color.append(color)
else:
color = pt.FALSE_RED
node_color.append(color)
#elif variable in soft_evidence:
# color = pt.LIGHT_PINK
# show_prior = True
# color = get_name_color(prior_marg)
# node_color.append(color)
else:
if cpd.ttype == NAME_TTYPE and post_marg is not None:
color = get_name_color(post_marg)
node_color.append(color)
elif cpd.ttype == MATCH_TTYPE and post_marg is not None:
color = cmap(post_marg.values[1])
color = pt.lighten_rgb(color, .4)
color = np.array(color)
node_color.append(color)
else:
#color = pt.WHITE
color = pt.NEUTRAL
node_color.append(color)
if show_prior:
if variable in soft_evidence:
prior_color = pt.LIGHT_PINK
else:
prior_color = None
prior_text = pgm_ext.make_factor_text(prior_marg, 'prior')
prior_tas.append(
dict(text=prior_text, pos=pos, color=prior_color, **takw2))
if show_evidence:
_takw1 = takw1
if cpd.ttype == SCORE_TTYPE:
_takw1 = takw2
evidence_text = cpd.variable_statenames[evidence[variable]]
if isinstance(evidence_text, int):
evidence_text = '%d/%d' % (evidence_text + 1,
cpd.variable_card)
evidence_tas.append(
dict(text=evidence_text, pos=pos, color=color, **_takw1))
if show_post:
_takw1 = takw1
if cpd.ttype == MATCH_TTYPE:
_takw1 = takw2
post_text = pgm_ext.make_factor_text(post_marg, 'post')
post_tas.append(dict(text=post_text, pos=pos, color=None,
**_takw1))
def trnps_(dict_list):
""" tranpose dict list """
list_dict = ut.ddict(list)
for dict_ in dict_list:
for key, val in dict_.items():
list_dict[key + '_list'].append(val)
return list_dict
takw1_ = trnps_(post_tas + evidence_tas)
takw2_ = trnps_(prior_tas)
# Draw graph
if has_inferred:
pnum1 = (3, 1, (slice(0, 2), 0))
else:
pnum1 = None
fig = pt.figure(fnum=fnum, pnum=pnum1, doclf=True) # NOQA
ax = pt.gca()
#print('node_color = %s' % (ut.repr3(node_color),))
drawkw = dict(pos=pos_dict,
ax=ax,
with_labels=True,
node_size=1500,
node_color=node_color)
netx.draw(netx_graph, **drawkw)
hacks = []
if len(post_tas + evidence_tas):
hacks.append(pt.draw_text_annotations(textprops=textprops, **takw1_))
if prior_tas:
hacks.append(pt.draw_text_annotations(textprops=textprops, **takw2_))
xmin, ymin = np.array(pos_list).min(axis=0)
xmax, ymax = np.array(pos_list).max(axis=0)
num_annots = len(model.ttype2_cpds[NAME_TTYPE])
if num_annots > 4:
ax.set_xlim((xmin - 40, xmax + 40))
ax.set_ylim((ymin - 50, ymax + 50))
fig.set_size_inches(30, 7)
else:
ax.set_xlim((xmin - 42, xmax + 42))
ax.set_ylim((ymin - 50, ymax + 50))
fig.set_size_inches(23, 7)
fig = pt.gcf()
title = 'num_names=%r, num_annots=%r' % (
model.num_names,
num_annots,
)
map_assign = kwargs.get('map_assign', None)
top_assignments = kwargs.get('top_assignments', None)
if top_assignments is not None:
map_assign, map_prob = top_assignments[0]
if map_assign is not None:
def word_insert(text):
return '' if len(text) == 0 else text + ' '
title += '\n%sMAP: ' % (word_insert(kwargs.get('method', '')))
title += map_assign + ' @' + '%.2f%%' % (100 * map_prob, )
if kwargs.get('show_title', True):
pt.set_figtitle(title, size=14)
for hack in hacks:
hack()
# Hack in colorbars
if has_inferred:
pt.colorbar(np.linspace(0, 1, len(name_colors)),
name_colors,
lbl=NAME_TTYPE,
ticklabels=model.ttype2_template[NAME_TTYPE].basis,
ticklocation='left')
basis = model.ttype2_template[SCORE_TTYPE].basis
scalars = np.linspace(0, 1, len(basis))
scalars = np.linspace(0, 1, 100)
colors = pt.scores_to_color(scalars,
cmap_=cmap_,
reverse_cmap=False,
cmap_range=(mn, mx))
colors = [pt.lighten_rgb(c, .4) for c in colors]
if ut.list_type(basis) is int:
pt.colorbar(scalars,
colors,
lbl=SCORE_TTYPE,
ticklabels=np.array(basis) + 1)
else:
pt.colorbar(scalars, colors, lbl=SCORE_TTYPE, ticklabels=basis)
#print('basis = %r' % (basis,))
# Draw probability hist
if has_inferred and top_assignments is not None:
bin_labels = ut.get_list_column(top_assignments, 0)
bin_vals = ut.get_list_column(top_assignments, 1)
# bin_labels = ['\n'.join(ut.textwrap.wrap(_lbl, width=30)) for _lbl in bin_labels]
pt.draw_histogram(
bin_labels,
bin_vals,
fnum=fnum,
pnum=(3, 8, (2, slice(4, None))),
transpose=True,
use_darkbackground=False,
#xtick_rotation=-10,
ylabel='Prob',
xlabel='assignment')
pt.set_title('Assignment probabilities')
