def update_metadata(self):
mpl4 = self.get_megacube_path('mpl-4/drpall-v1_5_1.fits')
mpl9 = self.get_megacube_path('mpl-9/drpall-v2_7_1.fits')
mpl4_metadata = mclass().get_metadata(mpl4)
self.stdout.write('Fetched MPL4')
mpl9_metadata = mclass().get_metadata(mpl9)
self.stdout.write('Fetched MPL9')
columns = self.get_model_fields(Image)
columns.remove('id')
for column in list(mpl4_metadata):
if column not in columns:
del mpl4_metadata[column]
for column in list(mpl9_metadata):
if column not in columns:
del mpl9_metadata[column]
self.stdout.write('Merged the two MPL file data')
dict_metadata = self.merge_same_keys_dict(mpl4_metadata, mpl9_metadata)
list_metadata = self.dict_list_to_list_dict(dict_metadata)
self.stdout.write(
'Transformed the dictionary of lists to a list of dictionaries')
for row in list_metadata:
filename = 'manga-%s-MEGA.fits.fz' % row['plateifu']
megacube = self.get_megacube_path(filename)
if os.path.isfile(megacube):
try:
self.stdout.write('File {} was found!'.format(filename))
new_image = Image()
for key in row.keys():
setattr(new_image, key, row[key])
# Adding the filename to table
setattr(new_image, 'megacube', filename)
new_image.save()
self.stdout.write('Inserted its metadata into database')
# Verifying that the there's not duplicates
except IntegrityError:
pass
self.stdout.write('Finished the database integration')
def test(self, request, pk=None):
galaxy = self.get_object()
megacube = self.get_megacube_path(galaxy.megacube)
data = mclass().image_by_hud(megacube, 'Adev')
z = mclass().image_data_to_array(data, )
return Response(z)
def exctract_original_image(self):
"""
It extracts the Origimal Image (zero) data from 'FLUX' HUD
for each image and save them in a very small JSON file in the path
/images/megacube_parts/megacube_{JOB_ID}/original_image.json.
"""
self.stdout.write("".ljust(100, '-'))
self.stdout.write('Started Original Image Extraction')
images = Image.objects.all()
for image in images:
self.stdout.write('Extracting Original Image [%s]' % str(image.id))
megacube = self.get_megacube_path(image.megacube)
cube_data = mclass().get_original_cube_data(megacube)
content = dict({
'z': cube_data,
'title': 'FLUX',
})
filename = 'original_image.json'
self.write_in_megacube_path(
image.megacube.split('.fits.fz')[0], filename, content)
self.stdout.write('Finished Original Image Extraction!')
def extract_megacube_header(self):
"""
It extracts the Megacube Header from 'PoPBins' HUD
for each image and save them in a very small JSON file in the path
/images/megacube_parts/megacube_{JOB_ID}/cube_header.json.
"""
self.stdout.write("".ljust(100, '-'))
self.stdout.write('Started Megacube Header Extraction')
images = Image.objects.all()
for image in images:
self.stdout.write('Extracting Megacube Header [%s]' %
str(image.id))
megacube = self.get_megacube_path(image.megacube)
content = repr(mclass().get_headers(megacube,
'PoPBins')).split('\n')
filename = 'cube_header.json'
self.write_in_megacube_path(
image.megacube.split('.fits.fz')[0], filename, content)
self.stdout.write('Finished Megacube Header Extraction!')
def vecs_by_position(self, request, pk=None):
"""
Returns the Vecs by an X, Y position.
Args: <br>
x ([number]): position X on Image. <br>
y ([number]): position Y on Image. <br>
Returns: <br>
[dict]: a dictionary with 'x', 'y', 'm' and 'mlegend'. <br>
- x ([list[number]]) <br>
- y ([list[number]]) <br>
- m ([list[number]]) <br>
- mlegend ([list[string]])
"""
params = request.query_params
if 'x' not in params:
raise Exception("Parameter x is required")
if 'y' not in params:
raise Exception("Parameter y is required")
galaxy = self.get_object()
megacube = self.get_megacube_path(galaxy.megacube)
vecs = mclass().vecs_by_position(megacube, int(params['x']),
int(params['y']))
return Response(vecs)
def extract_list_hud(self):
"""
It extracts the List of HUDs from 'PoPBins' HUD
for each image and save them in a very small JSON file in the path
/images/megacube_parts/megacube_{JOB_ID}/list_hud.json.
"""
self.stdout.write("".ljust(100, '-'))
self.stdout.write('Started List Of HUD Extraction')
images = Image.objects.all()
for image in images:
self.stdout.write('Extracting List Of HUD [%s]' % str(image.id))
megacube = self.get_megacube_path(image.megacube)
cube_header = mclass().get_headers(megacube, 'PoPBins')
cube_data = mclass().get_cube_data(megacube, 'PoPBins')
cube_comments = mclass().get_comments(megacube, 'PoPBins')
lHud = mclass().get_all_hud(cube_header, cube_data)
dHud = list()
for hud in lHud:
# TODO: recuperar o display name para cada HUD
dHud.append({
'name': hud,
'display_name': hud,
'comment': cube_comments[hud]
})
dHud = sorted(dHud, key=lambda i: i['display_name'])
content = ({'hud': dHud})
filename = 'list_hud.json'
self.write_in_megacube_path(
image.megacube.split('.fits.fz')[0], filename, content)
self.stdout.write('Finished List Of HUD Extraction!')
def flux_by_position(self, request, pk=None):
"""
Returns the Flux, Lambda and Synt by an X, Y position.
Args: <br>
x ([number]): position X on Image. <br>
y ([number]): position Y on Image.
Returns: <br>
[dict]: a dictionary with the 'flux', 'lamb' and 'synt'. <br>
- flux ([list[number]]) <br>
- lamb ([list[number]]) <br>
- synt ([list[number]])
"""
params = request.query_params
if 'x' not in params:
raise Exception("Parameter x is required")
if 'y' not in params:
raise Exception("Parameter y is required")
galaxy = self.get_object()
megacube = self.get_megacube_path(galaxy.megacube)
flux, lamb = mclass().flux_by_position(megacube, int(params['x']),
int(params['y']))
synt, lamb2 = mclass().synt_by_position(megacube, int(params['x']),
int(params['y']))
result = dict({
'flux': flux.tolist(),
'lamb': lamb.tolist(),
'synt': synt.tolist(),
})
return Response(result)
def extract_image_heatmap(self):
"""
It extracts all the Image Heatmaps from 'PoPBins' HUD
for each image and for each HUD saved in the file
/images/megacube_parts/megacube_{JOB_ID}/list_hud.json
and save them in very small JSON files in the path
/images/megacube_parts/megacube_{JOB_ID}/image_heatmap_{HUD}.json.json.
"""
self.stdout.write("".ljust(100, '-'))
self.stdout.write('Started Image Heatmap Extraction')
images = Image.objects.all()
for i, image in enumerate(images):
t0 = datetime.now()
self.stdout.write('Started Image Heatmap By ID [%s]: [%s]' %
(image.id, t0.strftime("%Y-%m-%d %H:%M:%S")))
megacube = self.get_megacube_path(image.megacube)
cube_header = mclass().get_headers(megacube, 'PoPBins')
cube_data = mclass().get_cube_data(megacube, 'PoPBins')
lHud = mclass().get_all_hud(cube_header, cube_data)
for hud in lHud:
self.stdout.write('Extracting Image Heatmap [%s] Of HUD [%s]' %
(str(image.id), str(hud)))
megacube = self.get_megacube_path(image.megacube)
image_data = mclass().image_by_hud(megacube, hud)
# z = mclass().image_data_to_array(image_data)
content = dict({
'z': image_data,
'title': hud,
})
filename = 'image_heatmap_%s.json' % hud
self.write_in_megacube_path(
image.megacube.split('.fits.fz')[0], filename, content)
# End time of Image Heatmap
t1 = datetime.now()
self.stdout.write('Finished Image Heatmap By ID [%s]: [%s]' %
(image.id, t0.strftime("%Y-%m-%d %H:%M:%S")))
self.stdout.write('Progress: [%s/%s]' % (i + 1, len(images)))
tdelta = t1 - t0
self.stdout.write(
'Execution Time By ID [%s]: [%s]' %
(image.id, humanize.naturaldelta(tdelta,
minimum_unit="seconds")))
self.stdout.write("".ljust(100, '-'))
self.stdout.write('Finished Image Heatmap Extraction!')