galaxychop.plot
module
Plot helper for the galaxy object.
- class galaxychop.plot.GalaxyPlotter(galaxy)[source]
Bases:
object
Make plots of DecisionMatrix.
- get_df_and_hue(ptypes, attributes, labels, lmap)[source]
Dataframe and Hue constructor for plot implementations.
- Parameters
ptypes (keys of
ParticleSet class
parameters.) – Particle type.attributes (keys of
ParticleSet class
parameters.) – Names ofParticleSet class
parameters.labels (keys of
ParticleSet class
parameters.) – Variable to map plot aspects to different colors.lmap (dicts) – Name assignment to the label.
- Returns
df (pandas.DataFrame) – DataFrame of galaxy properties with labels added.
hue (keys of
ParticleSet class
parameters.) – Labels of all galaxy particles.
- pairplot(ptypes=None, attributes=None, labels='ptype', lmap=None, **kwargs)[source]
Draw a pairplot of the galaxy properties.
By default, this function will create a grid of Axes such that each numeric variable in data will by shared across the y-axes across a single row and the x-axes across a single column. The diagonal plots drow a univariate distribution to show the marginal distribution of the data in each column. This function groups the values of all galaxy particles according to some
ParticleSet class
parameter.- Parameters
ptypes (keys of
ParticleSet class
parameters.) – Particle type. Default value = Noneattributes (keys of
ParticleSet class
parameters.) – Names ofParticleSet class
parameters. Default value = Nonelabels (keys of
ParticleSet class
parameters.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.pairplot
.
- Returns
- Return type
seaborn.axisgrid.PairGrid
- scatter(x, y, ptypes=None, labels=None, lmap=None, **kwargs)[source]
Draw a scatter plot of galaxy properties.
Shows the relationship between x and y. This function groups the values of all galaxy particles according to some
ParticleSet class
parameter.- Parameters
x (keys of
ParticleSet class
parameters.) – Variables that specify positions on the x and y axes. Default value y = None.y (keys of
ParticleSet class
parameters.) – Variables that specify positions on the x and y axes. Default value y = None.ptypes (keys of
ParticleSet class
parameters.) – Particle type. Default value = Nonelabels (keys of
ParticleSet class
parameters.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.scatterplot
.
- Returns
- Return type
matplotlib.axes.Axes
- hist(x, y=None, ptypes=None, labels=None, lmap=None, **kwargs)[source]
Draw a histogram of galaxy properties.
Plot univariate or bivariate histograms to show distributions of datasets. This function groups the values of all galaxy particles according to some
ParticleSet class
parameter.- Parameters
x (keys of
ParticleSet class
parameters.) – Variables that specify positions on the x and y axes. Default value y = None.y (keys of
ParticleSet class
parameters.) – Variables that specify positions on the x and y axes. Default value y = None.ptypes (keys of
ParticleSet class
parameters.) – Particle type. Default value = Nonelabels (keys of
ParticleSet class
parameters.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.histplot
.
- Returns
- Return type
matplotlib.axes.Axes
- kde(x, y=None, ptypes=None, labels=None, lmap=None, **kwargs)[source]
Draw a Kernel Density plot of galaxy properties.
Plot univariate or bivariate distributions using kernel density estimation (KDE). This plot represents the galaxy properties using a continuous probability density curve in one or more dimensions. This function groups the values of all galaxy particles according to some
ParticleSet class
parameter.- Parameters
x (keys of
ParticleSet class
parameters.) – Variables that specify positions on the x and y axes. Default value y = None.y (keys of
ParticleSet class
parameters.) – Variables that specify positions on the x and y axes. Default value y = None.ptypes (keys of
ParticleSet class
parameters.) – Particle type. Default value = Nonelabels (keys of
ParticleSet class
parameters.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.kdeplot
.
- Returns
- Return type
matplotlib.axes.Axes
- get_circ_df_and_hue(cbins, attributes, labels, lmap)[source]
Dataframe and Hue constructor for plot implementations.
- Parameters
cbins (tuple) – It contains the two widths of bins necessary for the calculation of the circular angular momentum. Shape: (2,). Dafult value = (0.05, 0.005).
attributes (keys of
JCirc
tuple.) – Keys of the normalized specific energy, the circularity parameter (J_z/J_circ) and/or the projected circularity parameter (J_p/J_circ) of the stellar particles.labels (keys of
JCirc
tuple.) – Variable to map plot aspects to different colors.lmap (dicts) – Name assignment to the label.
- Returns
df (pandas.DataFrame) – DataFrame of the normalized specific energy, the circularity parameter (J_z/J_circ) and/or the projected circularity parameter (J_p/J_circ) of the stellar particles with labels added.
hue (keys of
JCirc
tuple.) – Labels of stellar particles.
- circ_pairplot(cbins=(0.05, 0.005), attributes=None, labels=None, lmap=None, **kwargs)[source]
Draw a pairplot of circularity and normalized energy.
By default, this function will create a grid of Axes such that each numeric variable in data will by shared across the y-axes across a single row and the x-axes across a single column. The diagonal plots drow a univariate distribution to show the marginal distribution of the data in each column. This function groups the values of stellar particles according to some keys of
JCirc
tuple.- Parameters
cbins (tuple) – It contains the two widths of bins necessary for the calculation of the circular angular momentum. Shape: (2,). Dafult value = (0.05, 0.005).
attributes (keys of
ParticleSet class
parameters.) – Names ofParticleSet class
parameters. Default value = Nonelabels (keys of
JCirc
tuple.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.pairplot
.
- Returns
- Return type
seaborn.axisgrid.PairGrid
- circ_scatter(x, y, cbins=(0.05, 0.005), labels=None, lmap=None, **kwargs)[source]
Draw a scatter plot of circularity and normalized energy.
Shows the relationship between x and y. This function groups the values of stellar particles according to some keys of
JCirc
tuple.- Parameters
x (keys of
JCirc
tuple.) – Variables that specify positions on the x and y axes. Default value y = None.y (keys of
JCirc
tuple.) – Variables that specify positions on the x and y axes. Default value y = None.cbins (tuple) – It contains the two widths of bins necessary for the calculation of the circular angular momentum. Shape: (2,). Dafult value = (0.05, 0.005).
labels (keys of
JCirc
tuple.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.scatterplot
.
- Returns
- Return type
matplotlib.axes.Axes
- circ_hist(x, y=None, cbins=(0.05, 0.005), labels=None, lmap=None, **kwargs)[source]
Draw a histogram of circularity and normalized energy.
Plot univariate or bivariate histograms to show distributions of datasets. This function groups the values of stellar particles according to some keys of
JCirc
tuple.- Parameters
x (keys of
JCirc
tuple.) – Variables that specify positions on the x and y axes. Default value y = None.y (keys of
JCirc
tuple.) – Variables that specify positions on the x and y axes. Default value y = None.cbins (tuple) – It contains the two widths of bins necessary for the calculation of the circular angular momentum. Shape: (2,). Dafult value = (0.05, 0.005).
labels (keys of
JCirc
tuple.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.histplot
.
- Returns
- Return type
matplotlib.axes.Axes
- circ_kde(x, y=None, cbins=(0.05, 0.005), labels=None, lmap=None, **kwargs)[source]
Draw a Kernel Density plot of circularity and normalized energy.
Plot univariate or bivariate distributions using kernel density estimation (KDE). This plot represents normalized specific energy, the circularity parameter (J_z/J_circ) and/or the projected circularity parameter (J_p/J_circ) of the stellar particles using a continuous probability density curve in one or more dimensions. This function groups the values of stellar particles according to some keys of
JCirc
tuple.- Parameters
x (keys of
JCirc
tuple.) – Variables that specify positions on the x and y axes. Default value y = None.y (keys of
JCirc
tuple.) – Variables that specify positions on the x and y axes. Default value y = None.cbins (tuple) – It contains the two widths of bins necessary for the calculation of the circular angular momentum. Shape: (2,). Dafult value = (0.05, 0.005).
labels (keys of
JCirc
tuple.) – Variable to map plot aspects to different colors. Default value = Nonelmap (dicts) – Name assignment to the label. Default value = None
**kwargs – Additional keyword arguments are passed and are documented in
seaborn.kdeplot
.
- Returns
- Return type
matplotlib.axes.Axes