def get_chord_single_offline(chord):
quality = quality_filter(chord)
remaining_extensions = remaining_extension_filter(chord, quality)
quality_semitones = quality_to_semitones(quality)
first_semitone_revision, remaining_extensions = suspension_scanner(
remaining_extensions, quality_semitones)
final_semitone_revision = extension_scanner(remaining_extensions,
first_semitone_revision,
quality)
if final_semitone_revision is None:
pass
elif repeated_interval_filter(final_semitone_revision) is not True:
final_semitone_strings, semitone_indices_to_replace = \
extension_replacement_scan(
semitones_to_strings(final_semitone_revision), chord)
final_semitone_revision = remove_element_by_index_scan(
final_semitone_revision, semitone_indices_to_replace)
return chord, final_semitone_revision, final_semitone_strings
def there_is_quality_overlap(chord):
quality_order_search_index = len(quality_filter(chord))
for i in dictionaries.doubled_potential_quality_orders():
if i in chord[:quality_order_search_index] and i in chord[
quality_order_search_index:]:
return True
return False
def get_chord_web(chord):
chord = space_bracket_comma_filter(chord)
chord = chord[0].upper() + chord[1:]
chord, no3_flag = no3_filter(chord)
chord, slash_content, slash_found = slash_chord_filter(chord)
root, rootless_chord = root_filter(chord, True)
quality = quality_filter(chord, root)
root_position = root_position_filter(root)
output_template = get_chord_single(rootless_chord, quality)
try:
all_extensions, semitone_jumps, interval_strings = output_template
except TypeError:
return
if no3_flag:
semitone_jumps, interval_strings = no3_scanner(semitone_jumps,
interval_strings)
else:
pass
default_keyboard_values = semitones_to_keyboard_inputs(
root, semitone_jumps)
interval_strings.insert(0, "R")
interval_indices = semitones_to_indices(semitone_jumps, root_position)
interval_notes = indices_to_notes(interval_indices, root)
if slash_found is True:
scan_interval_notes, scan_interval_strings, scan_keyboard_values = \
slash_chord_scanner(slash_content, list(interval_notes), interval_strings, default_keyboard_values)
return slash_chord_recursion_scanner(interval_notes,
scan_interval_notes,
scan_interval_strings,
scan_keyboard_values)
else:
final_object_template = interval_notes, interval_strings, default_keyboard_values
return final_object_template
def get_chord_multiple():
chord_inputs = open("COMBINED_PRE_QUALS.txt", "r")
for i in chord_inputs:
stripped_chord = i.replace("\n", "")
quality = quality_filter(stripped_chord)
remaining_extensions = remaining_extension_filter(
stripped_chord, quality)
quality_semitones = quality_to_semitones(quality)
first_semitone_revision, remaining_extensions = suspension_scanner(
remaining_extensions, quality_semitones)
final_semitone_revision = extension_scanner(remaining_extensions,
first_semitone_revision,
quality)
final_output_template = []
if final_semitone_revision is None:
pass
elif repeated_interval_filter(final_semitone_revision) is not True:
final_semitone_strings, semitone_indices_to_replace = \
extension_replacement_scan(semitones_to_strings(
final_semitone_revision), stripped_chord)
final_semitone_revision = remove_element_by_index_scan(
final_semitone_revision, semitone_indices_to_replace)
final_output_template.insert(0, final_semitone_strings)
final_output_template.insert(0, final_semitone_revision)
final_output_template.insert(0, [stripped_chord])
print(final_output_template, file=open("database.txt", "a"))
def user_input():
"""Receives input from user. Scans and filters to segment chord into root, quality, and extensions
Args:
No arguments
Returns:
Tuple of root, quality and extensions (string, string, string)
"""
chord = input("Enter chord: ")
chord = chord[0].upper() + chord[1:]
root = root_filter(chord)
quality = quality_filter(chord, root)
remaining_extensions = remaining_extension_filter(chord, quality, root)
final_input = root, quality, remaining_extensions
return final_input
if (mode == 0):
print('mode = 0: running only on real data')
elif (mode == 1):
print('mode = 1: running on real data and simulated data')
# inject objects for simulated object of mc_source_id
sim_data = simple_utils.construct_sim_data(pix_nside_neighbors,
mc_source_id)
data = simple_utils.inject_sim(data, sim_data, mc_source_id)
elif (mode == 2):
print('mode = 2: running only on real data')
else:
print('No/unsupported mode specified; running only on real data')
# Quality cut
quality = filters.quality_filter(survey, data)
data = data[quality]
# Deredden magnitudes
data = filters.dered_mag(survey, data)
print('Found {} objects...').format(len(data))
if (len(data) == 0):
print('Ending search prematurely. Look at data for debugging.')
nan_array = [np.nan]
simple_utils.write_output(results_dir, nside, pix_nside_select, nan_array,
nan_array, nan_array, nan_array, nan_array,
nan_array, nan_array, nan_array, [mc_source_id],
mode, outfile)
exit()
def analysis(targ_ra, targ_dec, mod, mc_source_id):
"""Analyze a candidate"""
pix_nside_select = ugali.utils.healpix.angToPix(nside, targ_ra, targ_dec)
ra_select, dec_select = ugali.utils.healpix.pixToAng(
nside, pix_nside_select)
pix_nside_neighbors = np.concatenate([[pix_nside_select],
healpy.get_all_neighbours(
nside, pix_nside_select)])
# Construct data
#data = simple_utils.construct_modal_data(mode, pix_nside_neighbors)
data = simple_utils.construct_real_data(pix_nside_neighbors)
if (mode == 0):
print('mode = 0: running only on real data')
elif (mode == 1):
print('mode = 1: running on real data and simulated data')
# inject objects for simulated object of mc_source_id
sim_data = simple_utils.construct_sim_data(pix_nside_neighbors,
mc_source_id)
data = simple_utils.inject_sim(data, sim_data, mc_source_id)
else:
print('No mode specified; running only on real data')
print('Loading data...')
data = simple_utils.construct_modal_data(mode, pix_nside_neighbors,
mc_source_id)
quality_cut = filters.quality_filter(survey, data)
data = data[quality_cut]
print('Found {} objects...').format(len(data))
data = filters.dered_mag(survey, data)
# This should be generalized to also take the survey
iso = isochrone_factory(name=isoname,
survey=isosurvey,
age=12,
z=0.0001,
distance_modulus=mod,
band_1=band_1.lower(),
band_2=band_2.lower())
# g_radius estimate
filter = filters.star_filter(survey, data)
iso_filter = simple_utils.cut_isochrone_path(data[mag_dered_1],
data[mag_dered_2],
data[mag_err_1],
data[mag_err_2],
iso,
radius=0.1,
return_all=False)
angsep = ugali.utils.projector.angsep(targ_ra, targ_dec, data[basis_1],
data[basis_2])
bins = np.linspace(0, 0.4, 21) # deg
centers = 0.5 * (bins[1:] + bins[0:-1])
area = np.pi * (bins[1:]**2 - bins[0:-1]**2) * 60**2
hist = np.histogram(angsep[(angsep < 0.4) & filter & iso_filter],
bins=bins)[0] # counts
f_interp = interpolate.interp1d(
np.linspace(centers[0], centers[-1], len(hist)), hist / area, 'cubic')
f_range = np.linspace(centers[0], centers[-1], 1000)
f_val = f_interp(f_range)
pairs = zip(f_range, f_val)
peak = max(pairs[:len(pairs) / 4],
key=lambda x: x[1]) # find peak within first quarter
def peak_index(pairs, peak):
for i in range(len(pairs)):
if pairs[i] == peak:
return i
osc = int(
0.04 / 0.4 *
1000) # +/- 0.04 (rounded down) deg oscillation about local extremum
relmin = argrelextrema(f_val, np.less, order=osc)[0]
try:
if len(relmin) > 0:
#half_point = f_range[relmin[0]]
i = 0
while ((f_range[relmin[i]] <= f_range[peak_index(pairs, peak)]) &
(i <= len(relmin) - 1)):
i += 1
half_point = f_range[relmin[i]]
elif len(relmin) == 0:
half_peak = (
peak[1] + np.mean(f_val[len(f_val) / 4:])
) / 2. # normalized to background (after first quarter)
#half_peak = np.mean(f_val[len(f_val)/4:])
half_pairs = []
for i in pairs[peak_index(pairs, peak):len(pairs) /
2]: # start after peak, stay within first quarter
if i != peak:
half_pairs.append((i[0], abs(i[1] - half_peak)))
half_point = min(half_pairs, key=lambda x: x[1])[0] # deg
except:
half_point = 0.1 # fixed value to catch errors
g_min = 0.5 / 60. # deg
g_max = 12. / 60. # deg
if half_point < g_min:
g_radius = g_min
elif half_point > g_max:
g_radius = g_max
else:
g_radius = half_point # deg
angsep = ugali.utils.projector.angsep(targ_ra, targ_dec, data[basis_1],
data[basis_2])
nbhd = (angsep < g_radius)
return (data, iso, g_radius, nbhd)