/
classify_all.py
140 lines (106 loc) · 3.34 KB
/
classify_all.py
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import sys
import json
import os
import h5py
import numpy as np
from bubbly.model import ModelGroup
from bubbly.field import get_field
from bubbly.util import chunk, cloud_map
job_file = 'classify_jobs.json'
result_dir = os.path.join('..', 'data', 'full_search')
def field_stamps(lon):
"""
Return the stamp parameters to classify for each longitude
Returns
-------
A list of lists
"""
f = get_field(lon)
stamps = list(f.all_stamps())
stamps = [s for s in stamps if np.abs(s[1] - lon) <= 0.5]
return sorted(stamps)
def submit_job(lon):
"""
Submit a new batch classification job to the cloud
This also creates or overwrides the appropraite entry
in classify_jobs.json
Parameters
----------
lon : longitude to run
"""
if already_submitted(lon):
print ("Job already submitted. To force a re-run, "
"first run\n\t python %s delete %i" % (__file__, lon))
return
workers = 100
stamps = field_stamps(lon)
model = ModelGroup.load('../models/full_classifier.dat')
chunks = chunk(stamps, workers)
jobs = cloud_map(model.decision_function,
chunks,
return_jobs=True,
_label='classify_%3.3i' % lon)
save_job_ids(lon, jobs)
def delete(lon):
data = json.load(open(job_file))
data.pop(str(lon), None)
with open(job_file, 'w') as outfile:
json.dump(data, outfile, indent=2)
def already_submitted(lon):
data = json.load(open(job_file))
return str(lon) in data
def retrieve_job(lon):
"""
Retrieve the results of a previous job submission,
and save to an hdf5 file
This creates/overwrites a file at ../data/full_search/<lon>.h5
Parameters
----------
lon : int. Longitude to retrieve
"""
import cloud
jobs = fetch_job_ids(lon)
stamps = np.array(field_stamps(lon), dtype=np.float32)
scores = np.hstack(cloud.result(jobs)).astype(np.float32)
#write to file
result_file = os.path.join(result_dir, "%3.3i.h5" % lon)
with h5py.File(result_file, 'w') as f:
f.create_dataset('stamps', data=stamps, compression=9)
f.create_dataset('scores', data=scores, compression=9)
def save_job_ids(lon, jobs):
data = {}
if os.path.exists(job_file):
data = json.load(open(job_file))
data[lon] = [min(jobs), max(jobs)]
with open(job_file, 'w') as outfile:
json.dump(data, outfile, indent=2)
def fetch_job_ids(lon):
err_msg = ("No submitted jobs. "
"Run python %s submit %i first" % (__file__, lon))
lon = str(lon)
if not os.path.exists(job_file):
raise RuntimeError(err_msg)
data = json.load(open(job_file))
if lon not in data:
raise RuntimeError(err_msg)
lo, hi = data[lon]
return range(lo, hi + 1)
def main(argv):
if len(argv) != 3:
raise RuntimeError("Usage: \n"
"python %s [submit fetch delete] longitude" %
__file__)
lon = int(argv[2])
if argv[1] == 'submit':
submit_job(lon)
sys.exit(0)
elif argv[1] == 'fetch':
retrieve_job(lon)
sys.exit(0)
elif argv[1] == 'delete':
delete(lon)
sys.exit(0)
else:
raise RuntimeError("Invalid option: %s" % argv[1])
if __name__ == "__main__":
main(sys.argv)