def plotLabelledSet():
# Creating a web report
report = otter.Otter("otterHtmls/training_set_noDS.html",
author="Gonghan Xu",
title="Training Set")
dat = np.load("heavyTrainSet_noDS.npy")
dat = sorted(dat)
# dat = dat[: 10]
startLoadTime = time.time()
numIns = len(dat)
with report:
# Putting the plots onto the web page.
for idx, ins in enumerate(dat, start=1):
if idx % 20 == 0:
print "Generating {}st/{} image".format(idx, numIns)
fig, ax = ins.getPlot()
# Writing the downsampled time_freq image
# Creating a row with three columns.
row = bt.Row(3)
row[0] + idx
# Putting the figure to the middle cell.
row[1].width = 6
row[1] + fig
report + row
if ins.hasDoubleChirp:
row[2] + "Double Chirp"
else:
row[2] + "Not Double Chirp"
plt.close(fig)
endLoadTime = time.time()
loadTime = endLoadTime - startLoadTime
print "Web page generation time:", loadTime, "sec"
def plotArbiAngles():
# Creating a web report
report = otter.Otter("otterHtmls/GT0448_100SampleTfMaps.html",
author="Gonghan Xu",
title="100 Time-frequency maps without labels")
with report:
# Putting the plots onto the web page.
for waveName in waveList:
plotNum = 0
wavePath = PATH.join(WAVEFORM_DIR, waveName + ".h5")
for iota in np.linspace(0, pi, 10, endpoint=True):
for phi in np.linspace(0, 2 * pi, 10, endpoint=True):
iotaStr = utils.ang_to_str(iota)
phiStr = utils.ang_to_str(phi)
# Constructing a data row
# Writing the data parameters
plotNum += 1
# Generate the downsampled time-freq map
# used for training
wf_data = gen_waveform(wavePath, iota, phi)
tf_data = tf_decompose(wf_data['hp'],
wf_data["sample_times"], motherFreq,
maxScale)
wplane = tf_data["wplane"]
wfreqs = tf_data["wfreqs"]
sample_times = wf_data["sample_times"]
# Get the selected region.
wplane_sel, freqs_sel, times_sel = \
utils.select_wplane(wplane, wfreqs,
sample_times,
mid_t=0, xnum=500,
ynum=350,
left_t_window=-0.05,
right_t_window=0.03,
freq_window=500)
print "{}. {}, iota: {}, phi: {}".\
format(plotNum, waveName, iotaStr, phiStr)
fig, ax = plt.subplots(figsize=fig_size)
ax.pcolormesh(times_sel,
freqs_sel,
wplane_sel,
cmap="gray")
ax.set_xlabel("time (s)")
ax.set_ylabel("frequency (Hz)")
ax.set_title("{}. {}, iota: {}, phi: {}, "
"mother freq: {:.2f}".format(
plotNum, waveName, iotaStr, phiStr,
motherFreq))
# plt.show()
# Writing the downsampled time_freq image
# Creating a row with three columns.
row = bt.Row(3)
# Putting the figure to the middle cell.
row[1].width = 6
row[1] + fig
report + row
def plotInstances(dataSetName):
instances = np.load(dataSetName)
instances.sort()
report = otter.Otter("otterHtmls/GT0453_100SampleInstances.html",
author="Gonghan Xu",
title="100 time-frequency maps for "
"{} with manual label".format(
instances[0].waveformName))
# i = 0
with report:
plotNum = 0
for instance in instances:
# i += 1
# if i == 5:
# break
# Loading parameters.
plotNum += 1
waveName = instance.waveformName
wavePath = PATH.join(WAVEFORM_DIR, waveName + ".h5")
iota = instance.iota
phi = instance.phi
hasDoubleChirp = instance.hasDoubleChirp
motherFreq = instance.motherFreq
iotaStr = utils.ang_to_str(iota)
phiStr = utils.ang_to_str(phi)
# Generate the down-sampled time-freq map
# used for training with embedded data parameters.
wf_data = gen_waveform(wavePath, iota, phi)
tf_data = tf_decompose(wf_data['hp'], wf_data["sample_times"],
motherFreq, maxScale)
wplane = tf_data["wplane"]
wfreqs = tf_data["wfreqs"]
sample_times = wf_data["sample_times"]
# Get the selected region.
wplane_sel, freqs_sel, times_sel = \
utils.select_wplane(wplane, wfreqs,
sample_times,
mid_t=0, xnum=500,
ynum=350,
left_t_window=-0.05,
right_t_window=0.03,
freq_window=500)
print "{}. {}, iota: {}, phi: {}, motherFreq: {:.2f}".\
format(plotNum, waveName, iotaStr, phiStr, motherFreq)
fig, ax = plt.subplots(figsize=fig_size)
ax.pcolormesh(times_sel, freqs_sel, wplane_sel, cmap="gray")
ax.set_xlabel("time (s)")
ax.set_ylabel("frequency (Hz)")
ax.set_title("{}. {}, iota: {}, phi: {}, "
"mother freq: {:.2f}".format(plotNum, waveName,
iotaStr, phiStr,
motherFreq))
# plt.show()
# Writing the down-sampled time_freq image.
# Creating a row with three columns.
row = bt.Row(3)
# Putting the figure to the middle cell.
row[1].width = 6
row[1] + fig
report + row
row = bt.Row(3)
row[1] + "({}) Double Chirp: {}".format(plotNum, hasDoubleChirp)
report + row
def plotProbs():
# Creating a web report
report = otter.Otter("otterHtmls/probs.html",
author="Gonghan Xu",
title="All Cases (Linear Kernel; "
"Using Original Image Size: 508 * 328)")
dat = np.load("heavyTrainSet_noDS.npy")
# dat = sorted(dat)
# dat = dat[: 248]
startLoadTime = time.time()
numIns = len(dat)
shuffIndices, probs, accus, fails, confMat \
= getCrossValProbs(dat, nfolds=5)
# sys.exit()
print "Start generating plots.."
numAccurates = 0
counter = 0
with report:
# Putting the plots onto the web page.
for c, i in enumerate(range(numIns), start=1):
if c % 50 == 0:
print "At {}st/{} image".format(c, numIns)
# if not fails[i]:
# continue
counter += 1
ins = dat[shuffIndices[i]]
fig, ax = ins.getPlot()
# Writing the downsampled time_freq image
# Creating a row with three columns.
row = bt.Row(4)
row[0] + counter
# Putting the figure to the middle cell.
row[1].width = 6
row[1] + fig
if ins.hasDoubleChirp:
row[2] + "Hand Label: Double Chirp"
else:
row[2] + "Hand Label: Not Double Chirp"
row[3] + "Predicted Prob (Double Chirp): {:.3f}"\
.format(probs[i])
report + row
plt.close(fig)
# if ins.hasDoubleChirp:
# numAccurates += 1 if probs[i] > 0.5 else 0
# else:
# numAccurates += 1 if probs[i] <= 0.5 else 0
# if dat[shuffIndices[i]].hasDoubleChirp:
# numAccurates += 1 if probs[shuffIndices[i]] > 0.5 else 0
# else:
# numAccurates += 1 if probs[shuffIndices[i]] <= 0.5 else 0
endLoadTime = time.time()
loadTime = endLoadTime - startLoadTime
print "Web page generation time:", loadTime, "sec"
print "Verifying classification accuracy: {:.5f}"\
.format(1 - 1.0 * sum(fails) / numIns)
return cluster, status, job
uber_repository = git.MetaRepository(
"/home/daniel.williams/events/O3/o3a_catalog_events")
events = gitlab.find_events(repository, milestone="PE: C01 Reruns")
mattermost = mattermost.Mattermost()
mattermost.send_message(":mega: The run supervising robot is running. :robot:",
"@daniel-williams")
report = otter.Otter(
filename=
"/home/daniel.williams/public_html/LVC/projects/O3/C01/summary.html",
author="R. Daniel Williams",
title="Asimov/Olivaw : Event supervision report")
with report:
report + "This report contains the latest updates on the run status of the various PE runs ongoing at CIT."
report + "Supervisor last checked these events at " + str(
datetime.datetime.now())
message = """# Run updates\n"""
message += """| Event | Gitlab State | Run state | Production | Approx | Sampler | Status |\n"""
message += """|---|---|---|---|---|---|\n"""
for event in events:
print(event.title)
status = None
def main(eventflag):
report = otter.Otter(
filename=
"/home/daniel.williams/public_html/LVC/projects/O3/C01/audit_current.html",
author="R. Daniel Williams",
title="Asimov/Olivaw : Preferred run audit report")
with report:
report + "This report contains the latest updates on the run status of the various PE runs ongoing at CIT."
report + "Supervisor last checked these events at " + str(
datetime.datetime.now())
global events
if eventflag:
events = [event for event in events if event.title == eventflag]
for event in events:
print(event.title)
# if event.state == None:
# continue
# if "Special" in event.labels:
# continue
# if "Preferred cleaned" in event.labels:
# continue
try:
repo = uber_repository.get_repo(event.title)
except:
print(f"{event.title} missing from the uberrepo")
continue
repo.update(stash=True)
with report:
report + f"#{event.title}"
preferred_summary = os.path.join(repo.directory, "Preferred",
"PESummary_metafile",
"posterior_samples.h5")
try:
print(preferred_summary)
data = read(preferred_summary)
print(data.labels)
with report:
report + f"{data.labels}"
except OSError:
with report:
report + f"There is no preferred file in this repository."
try:
event_prods = repo.find_prods(config.get("olivaw", "run_category"))
except:
print(f"No runs in this repository")
continue
if event.state in ["Generating PSDs", "Productions running", "Stuck"]:
psds_dict = {}
prod_keys = [
key for key in event.data.keys() if "Prod" in key[0:5]
]
n_productions = len(event_prods)
event_psds_l = []
pref_prod = []
for prod in event_prods:
prod = prod.split("_")[0]
if prod in event.data:
cluster = event.data[prod]
run_ini = os.path.join(event.data[f"{prod}_rundir"],
"config.ini")
actual_config = RunConfiguration(run_ini)
engine_data = actual_config.get_engine()
if "finalised" in cluster.lower():
print(f"{prod} is the preferred production")
pref_prod.append(prod)
try:
if len(pref_prod) == 0: continue
upload_results(repo, event, pref_prod, report=report)
except FileNotFoundError as e:
print(e)
def main():
report = otter.Otter(
filename=
"/home/daniel.williams/public_html/LVC/projects/O3/C01/audit_mcmc.html",
author="R. Daniel Williams",
title="Asimov/Olivaw : Preferred run audit report")
with report:
report + "This report contains the latest updates on the run status of the various PE runs ongoing at CIT."
report + "Supervisor last checked these events at " + str(
datetime.datetime.now())
all_ids, all_wds = get_all_jobs()
for event in events:
print(event.title)
if event.state == None:
continue
if "Special" in event.labels:
continue
try:
repo = uber_repository.get_repo(event.title)
except:
print(f"{event.title} missing from the uberrepo")
continue
repo.update(stash=True)
with report:
report + f"#{event.title}"
try:
event_prods = repo.find_prods(config.get("olivaw", "run_category"))
except:
print(f"No runs in this repository")
continue
if event.state in ["Generating PSDs", "Productions running", "Stuck"]:
psds_dict = {}
prod_keys = [
key for key in event.data.keys() if "Prod" in key[0:5]
]
n_productions = len(event_prods)
event_psds_l = []
pref_prod = []
for prod in event_prods:
prod = prod.split("_")[0]
if prod in event.data:
if "blocked" in event.data[prod].lower(): continue
cluster = event.data[prod]
prod_rundir = event.data[f"{prod}_rundir"]
run_ini = os.path.join(prod_rundir, "config.ini")
actual_config = RunConfiguration(run_ini)
try:
engine_data = actual_config.get_engine()
except:
continue
if not "daniel.williams" in prod_rundir:
continue
if actual_config.ini.get("analysis",
"engine") == "lalinferencemcmc":
# Keep only lists that correspond to the working directory
job_ids = [
number
for number, directory in zip(all_ids, all_wds)
if (prod in directory) and (
event.title in directory)
]
print(job_ids)
if len(job_ids) > 0:
report += job_ids
tmp = "tmp"
try:
os.makedirs(tmp)
except:
pass
try:
os.makedirs(f"{prod_rundir}/{tmp}/html")
#os.popen(f"rm -r /home/john.veitch/projects/O3/SEOBNRv4P_rota_runs/{event.title}/{prod}")
os.makedirs(
f"/home/john.veitch/projects/O3/SEOBNRv4P_rota_runs/{event.title}/{prod}-robot"
)
except:
pass
raw_pp_str = os.popen(
f'grep cbcBayesPostProc {prod_rundir}/lalinference*.sh'
).read()
pspath0 = raw_pp_str.split('hdf5_snr.txt ')[-1].split(
' ')[0]
for job in job_ids:
os.system(
f'condor_ssh_to_job -ssh scp {job} remote:./*.hdf* {prod_rundir}/{tmp}'
)
for h5file in glob.glob(f"{prod_rundir}/{tmp}/*.hdf5"):
pspath1 = h5file # os.path.join(prod_rundir, tmp,'*.hdf5')
# print(pspath1)
file = h5file.split("/")[-1]
copy(
h5file,
f"/home/john.veitch/projects/O3/SEOBNRv4P_rota_runs/{event.title}/{prod}-robot/{file}"
)
pspath = raw_pp_str.replace(pspath0, pspath1)
webpath = pspath.split("--outpath")[1].split()[0]
new_webpath = f"{prod_rundir}/{tmp}/html"
print(pspath.replace(webpath, new_webpath))
def html(event, webdir):
"""
Return the ledger for a given event.
If no event is specified then the entire production ledger is returned.
"""
server, repository = connect_gitlab()
if not webdir:
webdir = config.get("report", "report_root")
click.echo("Getting events...")
events = gitlab.find_events(repository,
milestone=config.get("olivaw", "milestone"),
subset=[event],
repo=False,
update=False)
click.echo("Got events")
if len(glob.glob("asimov.conf")) > 0:
config_file = "asimov.conf"
else:
config_file = None
report = otter.Otter(f"{webdir}/index.html",
author="Olivaw",
title="Olivaw PE Report",
author_email=config.get("report", "report_email"),
config_file=config_file)
with report:
navbar = bt.Navbar("Asimov", background="navbar-dark bg-primary")
report + navbar
with report:
time = bt.Container()
time + f"Report generated at {str(datetime.now(tz))}"
report + time
cards = []
container = bt.Container()
container + "# All PE Productions"
for event in events:
click.secho(event.title, bold=True)
event_report = otter.Otter(f"{webdir}/{event.title}.html",
author="Olivaw",
title=f"Olivaw PE Report | {event.title}",
author_email="*****@*****.**",
config_file=config_file)
with event_report:
navbar = bt.Navbar("Asimov", background="navbar-dark bg-primary")
event_report + navbar
card = bt.Card(title=f"<a href='{event.title}.html'>{event.title}</a>")
toc = bt.Container()
for production in event.productions:
toc + f"* [{production.name}](#{production.name}) | {production.pipeline} |" # + bt.Badge({production.pipeline}, "info")
with event_report:
title_c = bt.Container()
title_c + f"#{event.title}"
event_report + title_c
event_report + toc
production_list = bt.ListGroup()
for production in event.productions:
click.echo(f"{event.title}\t{production.name}")
if production.pipeline.lower() in known_pipelines:
pipe = known_pipelines[production.pipeline.lower()](
production, "C01_offline")
event_log = otter.Otter(
f"{webdir}/{event.title}-{production.name}.html",
author="Olivaw",
title=f"Olivaw PE Report | {event.title} | {production.name}",
author_email="*****@*****.**",
config_file=config_file)
status_map = {
"cancelled": "light",
"finished": "success",
"uploaded": "success",
"processing": "primary",
"running": "primary",
"stuck": "warning",
"restart": "secondary",
"ready": "secondary",
"wait": "light",
"stop": "danger",
"manual": "light",
"stopped": "light"
}
with event_report:
container = bt.Container()
container + f"## {production.name}"
container + f"<a id='{production.name}'/>"
container + "### Ledger"
container + production.meta
if production.pipeline.lower() == "bilby":
container + f"### Progress"
progress_line = []
procs = pipe.check_progress()
for proc, val in procs.items():
container + f"- {proc.split('_')[-1]}\t{val[0]}\t{val[1]}"
progress_line.append(f"{val[1]}")
else:
progress_line = []
if production.status.lower() == "running":
progress = str(bt.Badge("|".join(progress_line)))
else:
progress = ""
if production.status.lower() == "uploaded":
link = os.path.join(
"https://ldas-jobs.ligo.caltech.edu",
config.get('general',
'webroot').replace("/home/", "~").replace(
"public_html/", ""), production.event.name,
production.name, "results", "home.html")
item_text = f"<a href='{link}'>{production.name}</a>"
else:
item_text = f"<a href='{event.title}.html#{production.name}'>{production.name}</a>"
production_list.add_item(
item_text + str(bt.Badge(f"{production.pipeline}", "info")) +
progress + str(bt.Badge(f"{production.status}")),
context=status_map[production.status])
# logs = pipe.collect_logs()
# container + f"### Log files"
# container + f"<a href='{event.title}-{production.name}.html'>Log file page</a>"
# with event_log:
# for log, message in logs.items():
# log_card = bt.Card(title=f"{log}")
# log_card.add_content("<div class='card-body'><pre>"+message+"</pre></div>")
# event_log + log_card
with event_report:
event_report + container
card.add_content(production_list)
cards.append(card)
with report:
if len(cards) == 1:
report + card
else:
for i, card in enumerate(cards):
if i % 2 == 0:
deck = bt.CardDeck()
deck + card
if i % 2 == 1:
report + deck