def jobs_report_summary_servo_xy(context, combinations, explogs_test):
parts = StoreResults()
for id_robot, id_agent in combinations:
for e in explogs_test:
key = dict(id_robot=id_robot, id_agent=id_agent, id_episode=e.id_episode)
job_id = 'part-' + basename_from_key(key)
arrows = context.comp(get_node, 'xy_arrows_colors',
context.get_report('servo1', **key),
job_id=job_id)
parts[key] = arrows
r = context.comp(report_servo1_global, combinations,
map(str, explogs_test), parts)
context.add_report(r, 'servo1_global')
interps = StoreResults()
for id_robot, id_agent in combinations:
for e in explogs_test:
key = dict(id_robot=id_robot, id_agent=id_agent, id_episode=e.id_episode)
job_id = 'interpolation-' + basename_from_key(key)
field = context.comp(get_node, 'interpolation',
context.get_report('distances2', **key),
job_id=job_id)
interps[key] = field
r = context.comp(report_distances2_global, combinations,
map(str, explogs_test), parts, interps)
context.add_report(r, 'distances2_global')
def report_distances2_global(combs, explogs_test, arrows, interps):
r = Report()
figs = {}
def get_fig(id_robot):
if not id_robot in figs:
figs[id_robot] = r.figure(cols=len(explogs_test), caption=id_robot)
return figs[id_robot]
for id_robot, id_agent in combs:
for id_episode in map(str, explogs_test):
key = dict(id_robot=id_robot, id_agent=id_agent, id_episode=id_episode)
interp = interps[key]
interp.nid = basename_from_key(key) + '-interp'
interp.caption = '%s, %s' % (id_robot, id_agent)
r.add_child(interp)
get_fig(id_robot).sub(interp)
for id_episode in map(str, explogs_test):
key = dict(id_robot=id_robot, id_agent=id_agent, id_episode=id_episode)
arrow = arrows[key]
arrow.nid = basename_from_key(key) + '-vf'
arrow.caption = '%s, %s' % (id_robot, id_agent)
r.add_child(arrow)
get_fig(id_robot).sub(arrow)
return r
def report_summary_servo_theta(context, combinations, explogs_test):
context = context.child('servo_theta')
rp = ReportProxy(context)
for id_robot, id_agent in combinations:
context.needs(RM_AGENT_LEARN, id_robot=id_robot, id_agent=id_agent)
f = rp.figure('%s-%s-servo_theta' % (id_robot, id_agent), cols=8,
caption='%s, %s' % (id_robot, id_agent))
for e in explogs_test:
key = dict(report_type='servo1', id_robot=id_robot,
id_agent=id_agent,
id_episode=e.id_episode)
s = 'servo-%s-' % basename_from_key(dict(id_agent=id_agent,
id_robot=id_robot,
id_episode=e.id_episode))
def add(url, nid, strict):
r = rp.add_child_from_other(url, s + nid, strict=strict, ** key)
f.sub(r, caption=nid)
add('u/figure2/tw', 'u-tw', True)
add('descent/figure2/tw', 'descent-tw', False)
return rp.get_job()
def job_report_learn(context, combs):
context = context.child('report_learn')
rp = ReportProxy(context)
for id_robot, id_agent in combs:
context.needs(RM_AGENT_LEARN, id_robot=id_robot, id_agent=id_agent)
f = rp.figure('%s-%s-model' % (id_robot, id_agent), cols=8,
caption='%s, %s' % (id_robot, id_agent))
key = dict(report_type='agent_report', id_robot=id_robot, id_agent=id_agent)
s = 'bds-%s-' % basename_from_key(dict(id_agent=id_agent, id_robot=id_robot))
add = lambda n, nid: f.sub(rp.add_child_from_other(n, s + nid, **key), caption=nid)
addif = lambda n, nid: f.sub(rp.add_child_from_other(n, s + nid, strict=False, **key), caption=nid)
add('estimator/model/M/slices/0/normalized/png', 'M0')
add('estimator/model/M/slices/1/normalized/png', 'M1')
addif('estimator/model/M/slices/2/normalized/png', 'M2')
add('estimator/model/N/slices/0/figure1/plot_scaled', 'N0')
add('estimator/model/N/slices/1/figure1/plot_scaled', 'N1')
addif('estimator/model/N/slices/2/figure1/plot_scaled', 'N2')
f = rp.figure('%s-%s-learn' % (id_robot, id_agent), cols=8,
caption='%s, %s' % (id_robot, id_agent))
add('estimator/tensors/T/slices/0/normalized/png', 'T0')
add('estimator/tensors/T/slices/1/normalized/png', 'T1')
addif('estimator/tensors/T/slices/2/normalized/png', 'T2')
add('estimator/tensors/U/slices/0/figure1/plot_scaled', 'U0')
add('estimator/tensors/U/slices/1/figure1/plot_scaled', 'U1')
addif('estimator/tensors/U/slices/2/figure1/plot_scaled', 'U2')
add('estimator/tensors/P/posneg', 'P')
return rp.get_job()
def add_child_from_other(self, url, nid, report_type, strict=True, **report_args):
part = self.get_part_of(url, report_type, strict=strict, **report_args)
if nid is None:
nid = basename_from_key(report_args) + "-" + url.replace("/", "-") # XXX url chars
self.add_child_with_id(part, nid)
return nid
def add_child_from_other(self, url, nid, report_type, strict=True, **report_args):
part = self.get_part_of(url, report_type, strict=strict, ** report_args)
if nid is None:
nid = basename_from_key(report_args) + '-' + url.replace('/', '-') # XXX url chars
self.add_child_with_id(part, nid)
return nid
def rp_simulation_tranche(c, id_robot, tranche):
tranche_episodes = tranches[tranche]
job_id = basename_from_key(dict(id_robot=id_robot, explorer=explorer, tranche=tranche))
return c.comp_config(simulate_agent_robot,
data_central=data_central,
id_agent=explorer,
id_robot=id_robot,
max_episode_len=max_episode_len,
stateful=False,
interval_print=5,
num_episodes=len(tranche_episodes),
id_episodes=tranche_episodes,
cumulative=False,
write_extra=False,
job_id=job_id)
def report_servo1_global(combs, explogs_test, parts):
r = Report()
figs = {}
def get_fig(id_robot):
if not id_robot in figs:
figs[id_robot] = r.figure(cols=len(explogs_test), caption=id_robot)
return figs[id_robot]
for id_robot, id_agent in combs:
for id_episode in map(str, explogs_test):
key = dict(id_robot=id_robot, id_agent=id_agent, id_episode=id_episode)
part = parts[key]
part.nid = basename_from_key(key)
part.caption = '%s, %s' % (id_robot, id_agent)
r.add_child(part)
get_fig(id_robot).sub(part)
return r
def bds_report(output_dir, report, agent, robot):
prefix = basename_from_key(dict(id_agent=agent, id_robot=robot))
# prefix = '%s-%s' % (agent, robot)
filename = os.path.join(output_dir, prefix + '.tex')
filename_doc = os.path.join(output_dir, prefix + '-single.tex')
preamble = """
\usepackage{graphicx}
\usepackage{fullpage}
\usepackage{nopageno}
\usepackage{subfig}
\usepackage{etoolbox}
\input{tex/config-draft.tex}
% \input{tex/preamble_figures.tex}
\input{tex/preamble_label_trick.tex}
% \input{tex/preamble_fancy_formatting.tex}
\input{tex/preamble_symbols.tex}
% \input{tex/preamble_symbols_nuisances.tex}
\input{tex/preamble_symbols_calib.tex}
\input{tex/preamble_symbols_bds.tex}
% \input{tex/preamble_thesis_layout.tex}
\input{tex/preamble_biblio.tex}
\input{tex/preamble_nomenclature.tex}
% \input{tex/preamble_prettyref.tex}
\input{tex/preamble_algo.tex}
% \input{tex/preamble_firstmention.tex}
\input{tex/preamble_hyperref.tex}
\input{tex/preamble_drafttools.tex}
\input{tex/preamble_info.tex}
\input{tex/preamble_python.tex}
"""
print('Writing to %s' % friendly_path(filename))
prefix_paths = 'jbds-tables/'
label_prefix = 'fig:%s-jlearn' % prefix
with latex_fragment(filename, graphics_path=output_dir) as frag:
jbds_bds_report(frag, report, prefix, label_prefix, agent, robot, prefix_paths=prefix_paths)
with latex_document(filename_doc, graphics_path=output_dir, document_class='IEEEtran') as doc:
doc.context.preamble.write(preamble)
with doc.figure(label=label_prefix, placement="p", double=True) as fig:
fig.input(os.path.basename(filename))
def get_part_of(self, url, report_type, strict=True, **report_args):
job_id = "get_part-" + report_type + "-" + basename_from_key(report_args)
r = self.context.get_report(report_type, **report_args)
job_id += "-" + url.replace("/", "_") # XXX
part = self.context.comp(get_node, url=url, r=r, strict=strict, job_id=job_id)
return part
def get_part_of(self, url, report_type, strict=True, **report_args):
job_id = 'get_part-' + report_type + '-' + basename_from_key(report_args)
r = self.context.get_report(report_type, **report_args)
job_id += '-' + url.replace('/', '_') # XXX
part = self.context.comp(get_node, url=url, r=r, strict=strict, job_id=job_id)
return part
def get_part_of(self, url, report_type, strict=True, **report_args):
job_id = 'get_part-' + report_type + '-' + basename_from_key(report_args)
r = self.context.get_report(report_type, **report_args)
job_id += '-' + url.replace('/', '_') # XXX
part = self.context.comp(get_node, url=url, r=r, strict=strict, job_id=job_id)
return part
