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Work in Progress¤
The full API of
+ocelot
is likely to change a lot before its first proper release. +This API page for ocelot.calculate is just a demo to help us make sure thatmkdocstrings
is working.
ocelot.calculate.position.mean_position(longitudes, latitudes, degrees=True)
+
+¤Calculates the spherical mean of angular positions, specified as longitudes and +latitudes. This uses directional statistics to do so in a way that is aware of +discontinuities, such as the fact that 0° = 360°.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ longitudes
+ |
+
+ array - like
+ |
+
+
+
+ Array of longitudinal positions of stars in your cluster (e.g. right ascensions +or galactic longitudes.) Assumed to be in the range [0°, 360°]. + |
+ + required + | +
+ latitudes
+ |
+
+ array - like
+ |
+
+
+
+ Array of latitudinal positions of stars in your cluster (e.g. declinations or +galactic latitudes.) Assumed to be in the range [-90°, 90°]. + |
+ + required + | +
+ degrees
+ |
+
+ bool
+ |
+
+
+
+ Whether longitudes and latitudes are in degrees, and whether to return an answer +in degrees. Defaults to True. If False, longitudes and latitudes are assumed to +be in radians, with ranges [0, 2π] and [-π/2, π/2] respectively. + |
+
+ True
+ |
+
Returns:
+Name | Type | +Description | +
---|---|---|
mean_longitude |
+ float
+ |
+
+
+
+
+ |
+
mean_latitude |
+ float
+ |
+
+
+
+
+ |
+
This function explicitly assumes that your star cluster has a well-defined mean +position. Some configurations (such as points uniformly distributed in at least one +axis of a sphere) will not have a meaningful mean position.
+Internally, this function uses scipy.stats.directional_stats
, with a definition
+taken from [1]. See [2] for more background.
[1] Mardia, Jupp. (2000). Directional Statistics (p. 163). Wiley. +[2] https://en.wikipedia.org/wiki/Directional_statistics
+See also: introductory tutorial on how to simulate a cluster.
+ + +ocelot.simulate.cluster.SimulatedCluster
+
+
+¤A class for simulating and keeping track of a simulated cluster - including its +original membership list and any observations simulated from it.
+This class is the main entry point in ocelot for simulating star clusters.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ parameters
+ |
+
+ SimulatedClusterParameters or dict
+ |
+
+
+
+ Parameters of the simulated cluster to generate. Should be a +SimulatedClusterParameters object, but may also be a dict with keys for required +parameters such as position, etc. + |
+ + required + | +
+ models
+ |
+
+ (SimulatedClusterModels, dict or None)
+ |
+
+
+
+ SimulatedClusterModels object or dict containing models used to overwrite or +augment certain simulation features. Default: None + |
+
+ None
+ |
+
+ prune_simulated_cluster
+ |
+
+ str
+ |
+
+
+
+ Optional string used early during cluster simulation to prune a simulated +cluster. Will be passed to pandas.DataFrame.query(). It can access parameters +read directly from cluster isochrones, including magnitude, temperature, +and luminosity. Default: "" + |
+
+ ''
+ |
+
+ random_seed
+ |
+
+ int or None
+ |
+
+
+
+ Random seed to use for cluster generation. When set, cluster generation with the +same seed should be identical. Default: None + |
+
+ None
+ |
+
+ features
+ |
+
+ SimulatedClusterFeatures or dict or None
+ |
+
+
+
+ A SimulatedClusterFeatures or dict object specifying features of cluster +generation to turn off. Mostly intended to aid with testing. Default: None + |
+
+ None
+ |
+
+ observations
+ |
+
+ list of str or None
+ |
+
+
+
+ List of observations to generate. Soon to be deprecated; do not use. + |
+
+ None
+ |
+
Attributes:
+Name | +Type | +Description | +
---|---|---|
isochrone |
+
+ DataFrame
+ |
+
+
+
+ Dataframe containing the isochrone used to simulate this cluster. + |
+
cluster |
+
+ DataFrame
+ |
+
+
+
+ Dataframe containing the true members of the cluster. + |
+
observations |
+
+ dict of pd.DataFrame
+ |
+
+
+
+ Dict of dataframes, with each one containing a different observation of the +same cluster. + |
+
make()
+
+¤Makes entire cluster according to specification set at initialization.
+This is the main function that should be used to simulate a cluster.
+ + +Returns:
+Type | +Description | +
---|---|
+ SimulatedCluster
+ |
+
+
+
+ A reference to the SimulatedCluster object. + |
+
make_cluster()
+
+¤Creates the true stars and positions in a cluster.
+In general, just calling .make() is the recommended method for most users.
+ + +Returns:
+Type | +Description | +
---|---|
+ SimulatedCluster
+ |
+
+
+
+ A reference to the SimulatedCluster object. + |
+
make_observations()
+
+¤Makes all observations of the cluster.
+In general, just calling .make() is the recommended method for most users.
+ + +Returns:
+Type | +Description | +
---|---|
+ SimulatedCluster
+ |
+
+
+
+ A reference to the SimulatedCluster object. + |
+
make_observation(survey, seed=None)
+
+¤Makes one observation of the cluster.
+In general, just calling .make() is the recommended method for most users.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ survey
+ |
+
+ str
+ |
+
+
+
+ Name of the survey (i.e. name in self.observations) to make. + |
+ + required + | +
+ seed
+ |
+
+ None
+ |
+
+
+
+ Seed used to reseed the random generator. Useful for doing multiple +different simulated observations of the same cluster. May not be supported +by all cluster observation models. Default: None, meaning that the current +cluster random number generator generated from the seed specified during +class initialization is used. + |
+
+ None
+ |
+
Returns:
+Type | +Description | +
---|---|
+ DataFrame
+ |
+
+
+
+ The simulated cluster observation made by this method. + |
+
ocelot.simulate.cluster.SimulatedClusterParameters
+
+
+
+ dataclass
+
+
+¤Class for keeping track of parameters specified for a cluster to simulate.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ position
+ |
+
+ SkyCoord
+ |
+
+
+
+ Position of the cluster as an astropy SkyCoord. Must have full 3D distance and +3D velocity information. + |
+ + required + | +
+ mass
+ |
+
+ float
+ |
+
+
+
+ Mass of the cluster in solar masses. + |
+ + required + | +
+ log_age
+ |
+
+ float
+ |
+
+
+
+ Age of the cluster in log (base 10) years. + |
+ + required + | +
+ metallicity
+ |
+
+ float
+ |
+
+
+
+ The metallicity of the cluster, [Fe/H]. + |
+ + required + | +
+ r_core
+ |
+
+ float
+ |
+
+
+
+ The core radius of the cluster, in parsecs. + |
+ + required + | +
+ r_tidal
+ |
+
+ float
+ |
+
+
+
+ The tidal radius of the cluster, in parsecs. + |
+ + required + | +
+ extinction
+ |
+
+ float
+ |
+
+
+
+ The extinction (A_V / A_0) of the cluster in magnitudes. + |
+ + required + | +
+ differential_extinction
+ |
+
+ float
+ |
+
+
+
+ Amount of differential extinction to apply to the cluster, also in magnitudes. +Default: 0. + |
+
+ 0.0
+ |
+
+ minimum_stars
+ |
+
+ int
+ |
+
+
+
+ Specify the minimum number of stars the cluster can have. Default: 0 + |
+
+ 1
+ |
+
+ virial_ratio
+ |
+
+ float
+ |
+
+
+
+ Virial ratio of the cluster. Acts as a square-root scale factor to the cluster's +velocity dispersion. Default: 0.5, meaning that the cluster is virialized. + |
+
+ 0.5
+ |
+
+ eta_virial_ratio
+ |
+
+ float
+ |
+
+
+
+ Scale factor of the 1D velocity dispersion equation. Default: 10, which is a +good approximation for most clusters. + |
+
+ 10.0
+ |
+
+ id
+ |
+
+ int
+ |
+
+
+
+ ID of the simulated cluster. When set, this allows for unique identification of +different simulated clusters. Default: 0. + |
+
+ 0
+ |
+
Attributes:
+Name | +Type | +Description | +
---|---|---|
r_50 |
+
+ float
+ |
+
+
+
+ The half-light radius of the cluster in parsecs. + |
+
velocity_dispersion_1d |
+
+ float
+ |
+
+
+
+ The 1D velocity dispersion of the cluster in metres per second. + |
+
ocelot.simulate.cluster.SimulatedClusterModels
+
+
+
+ dataclass
+
+
+¤Class for keeping track of all models that a generated SimulatedCluster will use.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ distribution
+ |
+
+ BaseClusterDistributionModel or None
+ |
+
+
+
+ The distribution model for the cluster. Must be an instance of +BaseClusterDistributionModel. Default: None, meaning that a King62 model is used + |
+
+ None
+ |
+
+ binaries
+ |
+
+ BaseBinaryStarModel or None
+ |
+
+
+
+ The binary star model for the cluster. Must be an instance of +BaseBinaryStarModel. Default: None, meaning that a +MoeDiStefanoMultiplicityRelation (with Duchene-Kraus+13 below 1 MSun) is used. + |
+
+ None
+ |
+
+ differential_reddening
+ |
+
+ BaseDifferentialReddeningModel or None
+ |
+
+
+
+ The differential reddening model for the cluster. Must be an instance of +BaseDifferentialReddeningModel. Default: None, meaning that a +FractalDifferentialReddening model is used. + |
+
+ None
+ |
+
+ observations
+ |
+
+ list or tuple of BaseObservation
+ |
+
+
+
+ A list or tuple of observation models for the cluster. Each model must be an +instance of a BaseObservation. These observation models will be iterated through +when generating cluster observations to generate as many (or few) observation +simulations of a cluster as you'd like. Observation models must be unique. +Default: None, meaning that no cluster observation simulation will be generated. + |
+
+ tuple()
+ |
+
Attributes:
+Name | +Type | +Description | +
---|---|---|
observations_dict |
+
+ dict of BaseObservation models
+ |
+
+
+
+ Same as the observations parameter, but with observations instead organized into +a dictionary. + |
+
initialise_defaults(parameters, seed)
+
+¤For all class attributes, replace None values with sensible default models.
+This method is called during simulated cluster generation and should not need +to be used by users.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ parameters
+ |
+
+ SimulatedClusterParameters
+ |
+
+
+
+ The parameters of the cluster to simulate. + |
+ + required + | +
+ seed
+ |
+
+ int
+ |
+
+
+
+ Random seed to use for default models that incorporate randomness. + |
+ + required + | +
with_default_options(parameters, seed)
+
+
+ staticmethod
+
+
+¤Return an instance of a SimulatedClusterModels model with default options.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ parameters
+ |
+
+ SimulatedClusterParameters
+ |
+
+
+
+ The parameters of the cluster to simulate. + |
+ + required + | +
+ seed
+ |
+
+ int
+ |
+
+
+
+ Random seed to use for default models that incorporate randomness. + |
+ + required + | +
Returns:
+Type | +Description | +
---|---|
+ SimulatedClusterModels
+ |
+
+
+
+ An instance of SimulatedClusterModels with default options already set up. + |
+
ocelot.simulate.cluster.SimulatedClusterFeatures
+
+
+
+ dataclass
+
+
+¤Class for keeping track of all features used to simulate a cluster.
+This class mostly exists to aid in testing parts of ocelot.simulate with certain +physical effects turned on or off.
+ + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
+ binary_stars
+ |
+
+ bool
+ |
+
+
+
+ Whether or not to simulate binary stars in the cluster. Default: True + |
+
+ True
+ |
+
+ differential_extinction
+ |
+
+ bool
+ |
+
+
+
+ Whether or not to simulate differential extinction of the cluster. Default: True + |
+
+ True
+ |
+
+ selection_effects
+ |
+
+ bool
+ |
+
+
+
+ Whether or not to simulate selection effects in simulated observations of the +cluster. Default: True + |
+
+ True
+ |
+
+ astrometric_uncertainties
+ |
+
+ bool
+ |
+
+
+
+ Whether or not to apply astrometric uncertainties to observations of the +cluster. Default: True + |
+
+ True
+ |
+
+ photometric_uncertainties
+ |
+
+ bool
+ |
+
+
+
+ Whether or not to apply photometric uncertainties to observations of the +cluster. Default: True + |
+
+ True
+ |
+