def _write_language_file(self, out_file):
coords = Coordinates()
langs = defaultdict(lambda: {'count': 0, 'group': None})
for year, entry_list in self.groups:
if year >= START_YEAR and year <= END_YEAR:
entry_list = list(entry_list)
for entry in entry_list:
langs[entry.language]['count'] += 1
langs[entry.language]['group'] = entry.language_group_initial()
for language in langs.keys():
# Number of possible points (between 3 and 30, depending on
# the frequency of the language)
num_points = int(langs[language]['count'] / 5)
num_points = max(4, min(num_points, 30))
# Select a bunch of random points within the language's geo region
langs[language]['coords'] = [coords.randomize(
language, decimalPlaces=2) for i in range(num_points)]
langs2 = []
for language, vals in langs.items():
langs2.append({'l': language,
'g': vals['group'],
'c': vals['coords']})
with open(out_file, 'w') as filehandle:
json.dump(langs2, filehandle)
language_index = {row['l']: i for i, row in enumerate(langs2)}
return language_index
def get(self, query):
parsed_coordinates = Coordinates.parse(query)
if parsed_coordinates is not None:
target = {
'ra': parsed_coordinates.ra,
'dec': parsed_coordinates.dec
}
get_app_state().target = parsed_coordinates
return jsonify(target)
catalog_result = get_catalog().get_entry(query.upper())
if catalog_result is not None:
parsed_coordinates = Coordinates.parse_csvformat(
catalog_result['RA'], catalog_result['Dec'])
target = {
'name': catalog_result['Name'],
'ra': parsed_coordinates.ra,
'dec': parsed_coordinates.dec,
'type': catalog_result.get('Type'),
'const': catalog_result.get('Const'),
'minAx': catalog_result.get('MinAx'),
'majAx': catalog_result.get('MajAx'),
'posAng': catalog_result.get('PosAng'),
}
get_app_state().target = parsed_coordinates
return jsonify(target)
return '', 404
def store_values(self):
print('Loading coordinates...')
coords = Coordinates()
print('Checking language overrides...')
overrides = LanguageOverrides().list_language_overrides()
print('Loading OED vital statistics...')
vitalstats = VitalStatisticsCache()
entries = []
iterator = FrequencyIterator(message='Listing entries')
for entry in iterator.iterate():
if (entry.has_frequency_table() and
not ' ' in entry.lemma and
not '-' in entry.lemma):
language_breadcrumb = vitalstats.find(entry.id, field='language')
year = vitalstats.find(entry.id, field='first_date') or 0
languages = []
if language_breadcrumb is not None:
languages = [l for l in language_breadcrumb.split('/')
if coords.is_listed(l)
or l == 'English']
else:
languages = ['unspecified', ]
if entry.id in overrides:
languages = [overrides[entry.id], ]
if languages:
# pick the most granular level (e.g. 'Icelandic' in
# preference to 'Germanic')
language = languages[-1]
# Find frequency for this word
freq_table = entry.frequency_table()
frequency = freq_table.frequency(period='modern')
band = freq_table.band(period='modern')
row = (entry.lemma,
entry.label,
entry.id,
year,
frequency,
band,
language)
entries.append(row)
entries = sorted(entries, key=lambda entry: entry[2])
with (open(self.out_file, 'w')) as csvfile:
writer = csv.writer(csvfile)
writer.writerows(entries)
def analyze_fun():
app_state.calibrating = True
calibration_data = Solver().analyze_image(
filepath,
timeout,
run_callback=lambda: app_state.calibrating,
)
app_state.calibrating = False
timestamp = int(datetime.datetime.now().timestamp())
if calibration_data is None:
log_event('Calibration failed')
else:
rotation_angle = calibration_data.rotation_angle
position = calibration_data.center_deg
log_event(
f'Image center: {position} Rotation: {rotation_angle}')
if app_state.target is not None:
target_distance = Coordinates(
app_state.target.ra - position.ra,
app_state.target.dec - position.dec)
log_event(f'Distance to target: {target_distance}')
app_state.last_known_position = {
'timestamp': timestamp,
'position': position,
}
def analyze_image(self,
filepath,
timeout=30,
run_callback=None) -> Union[CalibrationData, None]:
command = self.get_analyze_command([filepath], timeout)
output = run_command_or_die_trying(command, timeout, run_callback)
if output is None:
return None
# Output example:
#
# [...] pixel scale 0.907073 arcsec/pix.
# [...]
# Field: toughstuff/s10212.tif
# Field center: (RA,Dec) = (114.133515, 65.594210) deg.
# Field center: (RA H:M:S, Dec D:M:S) = (07:36:32.044, +65:35:39.156).
# Field size: 28.9649 x 16.3092 arcminutes
# Field rotation angle: up is 1.76056 degrees E of N
# Field parity: pos
# [...]
output_regexes = {
'pixel_scale':
r'^.*pixel scale (?P<scale>[\d\.]*) (?P<unit>[\w\/]*)\..*$',
'center_deg':
r'^.*Field center: \(RA,Dec\) = \((?P<ra>[\d\.]*), (?P<dec>[\-\d\.]*)\) deg\..*$',
'center':
r'^.*Field center: \(RA H:M:S, Dec D:M:S\) = \((?P<ra>[\d\.\:]*), (?P<dec>[\d\.\:\+\-]*)\)\..*$',
'size':
r'^.*Field size: (?P<width>[\d\.]*) x (?P<height>[\d\.]*) (?P<unit>\w*).*$',
'rotation':
r'^.*Field rotation angle: up is (?P<angle>[\-\d\.]*) degrees (?P<direction>[WE]) of N.*$',
'parity': r'^.*Field parity: (?P<parity>pos|neg).*$',
}
parsed_data = {}
for output_key, output_regex in output_regexes.items():
rx = re.compile(output_regex, re.DOTALL)
match = rx.match(output)
if not match:
print(
f'WARN: No match found for "{output_key}" in output of solve-field of file {filepath}.'
)
print(
f'Field may not have been solved or the output of the solver could not be parsed. Full output:\n{output}'
)
return None
parsed_data[output_key] = match.groupdict()
return CalibrationData(
pixel_scale=float(parsed_data['pixel_scale']['scale']),
pixel_scale_unit=str(parsed_data['pixel_scale']['unit']),
center_deg=Coordinates(float(parsed_data['center_deg']['ra']),
float(parsed_data['center_deg']['dec'])),
rotation_angle=float(parsed_data['rotation']['angle']),
rotation_direction=str(parsed_data['rotation']['direction']),
parity=str(parsed_data['parity']['parity']),
)