class LightParam(object): """ """ def __init__(self, light_model_list, kwargs_fixed, kwargs_lower=None, kwargs_upper=None, type='light', linear_solver=True): self._lightModel = LightModel(light_model_list=light_model_list) self._param_name_list = self._lightModel.param_name_list self._type = type self.model_list = light_model_list self.kwargs_fixed = kwargs_fixed if linear_solver: self.kwargs_fixed = self._lightModel.add_fixed_linear(self.kwargs_fixed) self._linear_solve = linear_solver if kwargs_lower is None: kwargs_lower = [] for func in self._lightModel.func_list: kwargs_lower.append(func.lower_limit_default) if kwargs_upper is None: kwargs_upper = [] for func in self._lightModel.func_list: kwargs_upper.append(func.upper_limit_default) self.lower_limit = kwargs_lower self.upper_limit = kwargs_upper @property def param_name_list(self): return self._param_name_list def getParams(self, args, i): """ :param args: :param i: :return: """ kwargs_list = [] for k, model in enumerate(self.model_list): kwargs = {} kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if not name in kwargs_fixed: if model in ['SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP'] and name == 'amp': if 'n_max' in kwargs_fixed: n_max = kwargs_fixed['n_max'] else: raise ValueError('n_max needs to be fixed in %s.' % model) if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1) ** 2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) kwargs['amp'] = args[i:i + num_param] i += num_param elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE'] and name == 'amp': if 'sigma' in kwargs_fixed: num_param = len(kwargs_fixed['sigma']) else: raise ValueError('sigma needs to be fixed in %s.' % model) kwargs['amp'] = args[i:i + num_param] i += num_param elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2'] and name == 'amp': if 'n_scales' in kwargs_fixed and 'n_pixels' in kwargs_fixed: n_scales = kwargs_fixed['n_scales'] n_pixels = kwargs_fixed['n_pixels'] else: raise ValueError("'n_scales' and 'n_pixels' both need to be fixed in %s." % model) num_param = n_scales * n_pixels kwargs['amp'] = args[i:i + num_param] i += num_param else: kwargs[name] = args[i] i += 1 else: kwargs[name] = kwargs_fixed[name] kwargs_list.append(kwargs) return kwargs_list, i def setParams(self, kwargs_list): """ :param kwargs_list: :param bounds: bool, if True, ellitpicity of min/max :return: """ args = [] for k, model in enumerate(self.model_list): kwargs = kwargs_list[k] kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if not name in kwargs_fixed: if model in ['SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP'] and name == 'amp': n_max = kwargs_fixed.get('n_max', kwargs['n_max']) if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1) ** 2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) for i in range(num_param): args.append(kwargs[name][i]) elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2'] and name == 'amp': if 'n_scales' in kwargs_fixed: n_scales = kwargs_fixed['n_scales'] else: raise ValueError("'n_scakes' for SLIT_STARLETS not found in kwargs_fixed") if 'n_pixels' in kwargs_fixed: n_pixels = kwargs_fixed['n_pixels'] else: raise ValueError("'n_pixels' for SLIT_STARLETS not found in kwargs_fixed") num_param = n_scales * n_pixels for i in range(num_param): args.append(kwargs[name][i]) elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2'] and name in ['n_scales', 'n_pixels', 'scale', 'center_x', 'center_y']: raise ValueError("'{}' must be a fixed keyword argument for STARLETS-like models".format(name)) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE'] and name == 'amp': num_param = len(kwargs['sigma']) for i in range(num_param): args.append(kwargs[name][i]) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE'] and name == 'sigma': raise ValueError("'sigma' must be a fixed keyword argument for MULTI_GAUSSIAN") else: args.append(kwargs[name]) return args def num_param(self): """ :return: """ num = 0 list = [] for k, model in enumerate(self.model_list): kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if not name in kwargs_fixed: if model in ['SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP'] and name == 'amp': if 'n_max' not in kwargs_fixed: raise ValueError("n_max needs to be fixed in this configuration!") n_max = kwargs_fixed['n_max'] if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1) ** 2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) num += num_param for i in range(num_param): list.append(str(name + '_' + self._type + str(k))) elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2'] and name == 'amp': if 'n_scales' not in kwargs_fixed or 'n_pixels' not in kwargs_fixed: raise ValueError("n_scales and n_pixels need to be fixed when using STARLETS-like models!") n_scales = kwargs_fixed['n_scales'] n_pixels = kwargs_fixed['n_pixels'] num_param = n_scales * n_pixels num += num_param for i in range(num_param): list.append(str(name + '_' + self._type + str(k))) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE'] and name == 'amp': num_param = len(kwargs_fixed['sigma']) num += num_param for i in range(num_param): list.append(str(name + '_' + self._type + str(k))) else: num += 1 list.append(str(name + '_' + self._type + str(k))) return num, list def num_param_linear(self): """ :return: number of linear basis set coefficients """ return self._lightModel.num_param_linear(kwargs_list=self.kwargs_fixed)
class LightParam(object): """ class manages the parameters corresponding to the LightModel() module. Also manages linear parameter handling. """ def __init__(self, light_model_list, kwargs_fixed, kwargs_lower=None, kwargs_upper=None, param_type='light', linear_solver=True): """ :param light_model_list: list of light models :param kwargs_fixed: list of keyword arguments corresponding to parameters held fixed during sampling :param kwargs_lower: list of keyword arguments indicating hard lower limit of the parameter space :param kwargs_upper: list of keyword arguments indicating hard upper limit of the parameter space :param param_type: string (optional), adding specifications in the output strings (such as lens light or source light) :param linear_solver: bool, if True fixes the linear amplitude parameters 'amp' (avoid sampling) such that they get overwritten by the linear solver solution. """ self._lightModel = LightModel(light_model_list=light_model_list) self._param_name_list = self._lightModel.param_name_list self._type = param_type self.model_list = light_model_list self.kwargs_fixed = kwargs_fixed if linear_solver: self.kwargs_fixed = self._lightModel.add_fixed_linear( self.kwargs_fixed) self._linear_solve = linear_solver if kwargs_lower is None: kwargs_lower = [] for func in self._lightModel.func_list: kwargs_lower.append(func.lower_limit_default) if kwargs_upper is None: kwargs_upper = [] for func in self._lightModel.func_list: kwargs_upper.append(func.upper_limit_default) self.lower_limit = kwargs_lower self.upper_limit = kwargs_upper @property def param_name_list(self): return self._param_name_list def get_params(self, args, i): """ :param args: list of floats corresponding ot the arguments being sampled :param i: int, index of the first argument that is managed/read-out by this class :return: keyword argument list of the light profile, index after reading out the arguments corresponding to this class """ kwargs_list = [] for k, model in enumerate(self.model_list): kwargs = {} kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if name not in kwargs_fixed: if model in [ 'SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP' ] and name == 'amp': if 'n_max' in kwargs_fixed: n_max = kwargs_fixed['n_max'] else: raise ValueError('n_max needs to be fixed in %s.' % model) if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1)**2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) kwargs['amp'] = args[i:i + num_param] i += num_param elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'amp': if 'sigma' in kwargs_fixed: num_param = len(kwargs_fixed['sigma']) else: raise ValueError('sigma needs to be fixed in %s.' % model) kwargs['amp'] = args[i:i + num_param] i += num_param elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2' ] and name == 'amp': if 'n_scales' in kwargs_fixed and 'n_pixels' in kwargs_fixed: n_scales = kwargs_fixed['n_scales'] n_pixels = kwargs_fixed['n_pixels'] else: raise ValueError( "'n_scales' and 'n_pixels' both need to be fixed in %s." % model) num_param = n_scales * n_pixels kwargs['amp'] = args[i:i + num_param] i += num_param else: kwargs[name] = args[i] i += 1 else: kwargs[name] = kwargs_fixed[name] kwargs_list.append(kwargs) return kwargs_list, i def set_params(self, kwargs_list): """ :param kwargs_list: list of keyword arguments of the light profile (free parameter as well as optionally the fixed ones) :return: list of floats corresponding to the free parameters """ args = [] for k, model in enumerate(self.model_list): kwargs = kwargs_list[k] kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if name not in kwargs_fixed: if model in [ 'SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP' ] and name == 'amp': n_max = kwargs_fixed.get('n_max', kwargs['n_max']) if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1)**2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) for i in range(num_param): args.append(kwargs[name][i]) elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2' ] and name == 'amp': if 'n_scales' in kwargs_fixed: n_scales = kwargs_fixed['n_scales'] else: raise ValueError( "'n_scales' for SLIT_STARLETS not found in kwargs_fixed" ) if 'n_pixels' in kwargs_fixed: n_pixels = kwargs_fixed['n_pixels'] else: raise ValueError( "'n_pixels' for SLIT_STARLETS not found in kwargs_fixed" ) num_param = n_scales * n_pixels for i in range(num_param): args.append(kwargs[name][i]) elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2' ] and name in [ 'n_scales', 'n_pixels', 'scale', 'center_x', 'center_y' ]: raise ValueError( "'{}' must be a fixed keyword argument for STARLETS-like models" .format(name)) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'amp': num_param = len(kwargs['sigma']) for i in range(num_param): args.append(kwargs[name][i]) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'sigma': raise ValueError( "'sigma' must be a fixed keyword argument for MULTI_GAUSSIAN" ) else: args.append(kwargs[name]) return args def num_param(self, latex_style=False): """ :param latex_style: boolena; if True, returns latex strings for plotting :return: int, list of strings with param names """ num = 0 name_list = [] for k, model in enumerate(self.model_list): kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if name not in kwargs_fixed: if model in [ 'SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP' ] and name == 'amp': if 'n_max' not in kwargs_fixed: raise ValueError( "n_max needs to be fixed in this configuration!" ) n_max = kwargs_fixed['n_max'] if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1)**2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) num += num_param for i in range(num_param): name_list.append( str(name + '_' + self._type + str(k))) elif model in ['SLIT_STARLETS', 'SLIT_STARLETS_GEN2' ] and name == 'amp': if 'n_scales' not in kwargs_fixed or 'n_pixels' not in kwargs_fixed: raise ValueError( "n_scales and n_pixels need to be fixed when using STARLETS-like models!" ) n_scales = kwargs_fixed['n_scales'] n_pixels = kwargs_fixed['n_pixels'] num_param = n_scales * n_pixels num += num_param for i in range(num_param): name_list.append( str(name + '_' + self._type + str(k))) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'amp': num_param = len(kwargs_fixed['sigma']) num += num_param for i in range(num_param): name_list.append( str(name + '_' + self._type + str(k))) else: num += 1 name_list.append(str(name + '_' + self._type + str(k))) return num, name_list def num_param_linear(self): """ :return: number of linear basis set coefficients """ return self._lightModel.num_param_linear(kwargs_list=self.kwargs_fixed)
class LightParam(object): """ """ def __init__(self, light_model_list, kwargs_fixed, kwargs_lower=None, kwargs_upper=None, type='light', linear_solver=True): self._lightModel = LightModel(light_model_list=light_model_list) self._param_name_list = self._lightModel.param_name_list self._type = type self.model_list = light_model_list self.kwargs_fixed = kwargs_fixed if linear_solver: self.kwargs_fixed = self._lightModel.add_fixed_linear( self.kwargs_fixed) self._linear_solve = linear_solver if kwargs_lower is None: kwargs_lower = [] for func in self._lightModel.func_list: kwargs_lower.append(func.lower_limit_default) if kwargs_upper is None: kwargs_upper = [] for func in self._lightModel.func_list: kwargs_upper.append(func.upper_limit_default) self.lower_limit = kwargs_lower self.upper_limit = kwargs_upper @property def param_name_list(self): return self._param_name_list def getParams(self, args, i): """ :param args: :param i: :return: """ kwargs_list = [] for k, model in enumerate(self.model_list): kwargs = {} kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if not name in kwargs_fixed: if model in [ 'SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP' ] and name == 'amp': if 'n_max' in kwargs_fixed: n_max = kwargs_fixed['n_max'] else: raise ValueError('n_max needs to be fixed in %s.' % model) if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1)**2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) kwargs['amp'] = args[i:i + num_param] i += num_param elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'amp': if 'sigma' in kwargs_fixed: num_param = len(kwargs_fixed['sigma']) else: raise ValueError('sigma needs to be fixed in %s.' % model) kwargs['amp'] = args[i:i + num_param] i += num_param else: kwargs[name] = args[i] i += 1 else: kwargs[name] = kwargs_fixed[name] kwargs_list.append(kwargs) return kwargs_list, i def setParams(self, kwargs_list): """ :param kwargs_list: :param bounds: bool, if True, ellitpicity of min/max :return: """ args = [] for k, model in enumerate(self.model_list): kwargs = kwargs_list[k] kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if not name in kwargs_fixed: if model in [ 'SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP' ] and name == 'amp': n_max = kwargs_fixed.get('n_max', kwargs['n_max']) if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1)**2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) for i in range(num_param): args.append(kwargs[name][i]) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'amp': num_param = len(kwargs['sigma']) for i in range(num_param): args.append(kwargs[name][i]) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'sigma': raise ValueError( "'sigma' must be a fixed keyword argument for MULTI_GAUSSIAN" ) else: args.append(kwargs[name]) return args def num_param(self): """ :return: """ num = 0 list = [] for k, model in enumerate(self.model_list): kwargs_fixed = self.kwargs_fixed[k] param_names = self._param_name_list[k] for name in param_names: if not name in kwargs_fixed: if model in [ 'SHAPELETS', 'SHAPELETS_POLAR', 'SHAPELETS_POLAR_EXP' ] and name == 'amp': if 'n_max' not in kwargs_fixed: raise ValueError( "n_max needs to be fixed in this configuration!" ) n_max = kwargs_fixed['n_max'] if model in ['SHAPELETS_POLAR_EXP']: num_param = int((n_max + 1)**2) else: num_param = int((n_max + 1) * (n_max + 2) / 2) num += num_param for i in range(num_param): list.append(str(name + '_' + self._type + str(k))) elif model in ['MULTI_GAUSSIAN', 'MULTI_GAUSSIAN_ELLIPSE' ] and name == 'amp': num_param = len(kwargs_fixed['sigma']) num += num_param for i in range(num_param): list.append(str(name + '_' + self._type + str(k))) else: num += 1 list.append(str(name + '_' + self._type + str(k))) return num, list def num_param_linear(self): """ :return: number of linear basis set coefficients """ return self._lightModel.num_param_linear(kwargs_list=self.kwargs_fixed) def check_positive_flux_profile(self, kwargs_list): pos_bool = True for k, model in enumerate(self.model_list): if 'amp' in kwargs_list[k]: if model in [ 'SERSIC', 'SERSIC_ELLIPSE', 'CORE_SERSIC', 'HERNQUIST', 'PJAFFE', 'PJAFFE_ELLIPSE', 'HERNQUIST_ELLIPSE', 'GAUSSIAN', 'GAUSSIAN_ELLIPSE', 'POWER_LAW', 'NIE', 'CHAMELEON', 'DOUBLE_CHAMELEON' ]: if kwargs_list[k]['amp'] < 0: pos_bool = False break return pos_bool