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color constrains put outside _parse_fit_constraints()
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dataset for color and blending constrain can be define by index or lable
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Mateusz Mroz committed May 13, 2024
1 parent e8796b6 commit 6bab7ad
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Showing 2 changed files with 96 additions and 43 deletions.
10 changes: 5 additions & 5 deletions examples/example_16/ob03235_2_full.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -38,13 +38,13 @@ fit_constraints:
#negative_blending_flux_sigma_mag: 20. 1 3
# Alternative sharp constraint:
# no_negative_blending_flux: True
#color constrains, where color=flux_S_dataset_no._k/flux_S_dataset_no._m: gauss mu sigma k m
color : gauss 25. 5. 1 2
#color constrains, where color=flux_S_dataset_k/flux_S_dataset_m: gauss mu sigma k m
color : gauss 25. 5. "OGLE I-band" "OB03235_MOA.txt"
#Alternative for binary source models:
#color source 1 : gauss 25. 5. 1 2
#color source 1 : gauss 25. 5. "OGLE I-band" "OB03235_MOA.txt"
#and/or
#color source 2 : gauss 25. 5. 1 2

#color source 2 : gauss 25. 5. 0 1
prior:
t_E: Mroz et al. 2017
# Other possibility:
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129 changes: 91 additions & 38 deletions examples/example_16/ulens_model_fit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
import warnings
import math
import numpy as np
import shlex
from scipy.interpolate import interp1d
from matplotlib import pyplot as plt
from matplotlib import gridspec, rcParams, rcParamsDefault
Expand Down Expand Up @@ -1470,49 +1471,66 @@ def _parse_fit_constraints(self):
value = self._fit_constraints[key]

if key == "negative_blending_flux_sigma_mag":
self._parse_fit_constraints_soft_blending(key, value)

if isinstance(value, (float, int)):
sigma = float(value)
sets = list(range(1, len(self._datasets) + 1))
else:
sigma = float(value.split()[0])
sets = list(map(int, value.split()[1:]))
if len(sets) > len(self._datasets):
raise ValueError(
'dataset number specified in negative_blending_flux_sigma_mag do not match with provided datasets')
elif key in ['color', 'color source 1', 'color source 2']:
self._parse_fit_constraints_color(key, value)

self._fit_constraints[key] = [
mm.Utils.get_flux_from_mag(sigma), sets]
if 'prior' in self._fit_constraints:
self._parse_fit_constraints_prior()

elif key in ['color', 'color source 1', 'color source 2']:
def _parse_fit_constraints_soft_blending(self, key, value):
"""
Check if soft fit constraint on blending flux are correctly defined.
"""
if isinstance(value, (float, int)):
sigma = float(value)
sets = list(range(1, len(self._datasets) + 1))
else:
sigma = float(value.split()[0])
sets = list(map(int, value.split()[1:]))
if len(sets) > len(self._datasets):
raise ValueError(
'dataset number specified in negative_blending_flux_sigma_mag do not match with provided datasets')

words = value.split()
if len(words) != 5 or words[0] != 'gauss':
msg = "Something went wrong in parsing prior for "
msg += "{:}: {:}"
if len(words) == 3 and words[0] == 'gauss':
msg += ' color priors require the specification of datasets that should be used for color calculation '
raise ValueError(msg.format(key, value))
try:
settings = [words[0], float(words[1]), float(
words[2]), int(words[3]), int(words[4])]
except Exception:
raise ValueError('error in parsing: ' + words[1] + " " +
words[2] + " " + words[3] + " " + words[4])
if settings[2] < 0.:
raise ValueError('sigma cannot be negative: ' + words[2])
if settings[3] == settings[4]:
raise ValueError(
"in " + key + " fluxes have to be from different datasets")
self._fit_constraints[key] = [
mm.Utils.get_flux_from_mag(sigma), sets]

if (0 >= settings[3] >= len(self._datasets)+1) or (0 >= settings[4] >= len(self._datasets)+1):
raise ValueError(
'dataset number specified in color prior do not match with provided datasets')
def _parse_fit_constraints_color(self, key, value):
"""
Check if fit constraint on color are correctly defined.
"""
words = shlex.split(value, posix=False)
if len(words) != 5 or words[0] != 'gauss':
msg = "Something went wrong in parsing prior for "
msg += "{:}: {:}"
if len(words) == 3 and words[0] == 'gauss':
msg += ' color priors require the specification of datasets that should be used for color calculation '
raise ValueError(msg.format(key, value))
try:
settings = [words[0], float(words[1]), float(
words[2]), words[3], words[4]]
except Exception:
raise ValueError('error in parsing: ' + words[1] + " " +
words[2] + " " + words[3] + " " + words[4])
if settings[2] < 0.:
raise ValueError('sigma cannot be negative: ' + words[2])
if settings[3] == settings[4]:
raise ValueError(
"in " + key + " fluxes have to be from different datasets")

self._fit_constraints[key] = settings
if isinstance(settings[3], str) and isinstance(settings[4], str):
settings[3] = settings[3].strip('"')
settings[4] = settings[4].strip('"')
settings[3] = self._get_no_of_dataset_by_lable(settings[3])
settings[4] = self._get_no_of_dataset_by_lable(settings[4])

if 'prior' in self._fit_constraints:
self._parse_fit_constraints_prior()
if isinstance(settings[3], int) and isinstance(settings[4], int):
if (0 >= settings[3] >= len(self._datasets)-1) or (0 >= settings[4] >= len(self._datasets)-1):
raise ValueError(
'dataset specified in color prior do not match with provided datasets')

self._fit_constraints[key] = settings

def _parse_fit_constraints_prior(self):
"""
Expand Down Expand Up @@ -1551,6 +1569,25 @@ def _parse_fit_constraints_prior(self):
if len(priors) > 0:
self._priors = priors

def _get_no_of_dataset_by_lable(self, label):
"""
Returns the index of a dataset with a specific label.
Parameters
----------
label : str
Label of the dataset defined by MulensData.plot_properties['label'].
Returns
-------
int
Sequential index of the dataset [1,2,...,n_datasets]
"""
for (i, dataset) in enumerate(self._datasets):
if dataset.plot_properties['label'] == label:
return i
return -99

def _read_prior_t_E_data(self):
"""
read data that specify t_E prior and parse them appropriately
Expand Down Expand Up @@ -2165,10 +2202,26 @@ def _get_fluxes(self):
return fluxes

def _sumup_inside_prior(self, fluxes, key, inside, idx_plus):
"""
Calculates the contribution to the ln_prior from specified color constraints
Parameters
----------
fluxes : array
Array with fluxes of the current model.
key : str
inside : float
idx_plus : int
For a single source, idx_plus=0;
for a binary source, idx_plus=0 or 1.
Returns
-------
inside : float
"""

settings = self._fit_constraints[key]
index1 = (settings[3]-1)*self._n_fluxes_per_dataset + idx_plus
index2 = (settings[4]-1)*self._n_fluxes_per_dataset + idx_plus
index1 = (settings[3])*self._n_fluxes_per_dataset + idx_plus
index2 = (settings[4])*self._n_fluxes_per_dataset + idx_plus
value = fluxes[index1]/fluxes[index2]
inside += self._get_ln_prior_for_1_parameter(value, settings[:-2])

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