lib.data_vector.plotting.BaseDataPlotStyle¶

class lib.data_vector.plotting.BaseDataPlotStyle(style=None, **kwargs)¶

Bases: cosmopipe.lib.plotting.BasePlotStyle

Base data plotting class. It holds default attributes (xlabel, ylabel, colors, etc.) that can be set at initialization (style = BaseDataPlotStyle(colors='r')) or at any time using update().

Initialize BaseDataPlotStyle.

Parameters

style (BaseDataPlotStyle, default=None) – A plotting style to start from, which will be updated with kwargs.
kwargs (dict) – Attributes for BaseDataPlotStyle.

Methods

`copy`	Return shallow copy of `self`.
`deepcopy`
`from_state`	Instantiate and initalize class with state dictionary.
`get`	Return `value` if not `None`, else attribute `name` if not `None`, else `default`.
`get_color`	Return color corresponding to projection name `proj`.
`get_covstd`	Return standard deviation corresponding to the input covariance matrix.
`get_covx`	Return x-coordinates of input covariance matrix.
`get_covy`	Return mean y-coordinates provided in the input covariance matrix.
`get_label`	Return label corresponding to projection name `proj`.
`get_list`	Same as `get()`, but ensuring returned value is a list.
`get_projs`	Return projection names of input data vector.
`get_x`	Return x-coordinates of input data vector.
`get_y`	Return y-coordinates of input data vector.
`get_ylabel`	Return y-label, to be overriden.
`is_mpi_broadcast`
`is_mpi_gathered`
`is_mpi_root`
`is_mpi_scattered`
`load`	Load class in numpy binary format from disk.
`load_auto`	If different formats are possible, this method should between them based on file name extension.
`log_critical`
`log_debug`
`log_error`
`log_info`
`log_warning`
`plot`	Plot data vectors, optionally with error bars / shaded area from covariance.
`save`	Save class to disk.
`save_auto`	If different formats are possible, this method should between them based on file name extension.
`savefig`	Save figure to `filename`.
`update`	Update attibutes with those in `kwargs`.

Attributes

`logger`
`mpiattrs`	MPI attributes
`mpicomm`
`mpiroot`
`mpistate`

copy()¶: Return shallow copy of self.

classmethod from_state(state, mpiroot=0, mpicomm=None)¶: Instantiate and initalize class with state dictionary.

get(name, value=None, default=None)¶

Return value if not None, else attribute name if not None, else default.

Parameters

name (string) – Attribute name. If None, defaults to default.
value (object, default=None) – Value. If None, returns attribute name.
default (object, default=None) – Default value.

get_color(proj, projs=None)¶: Return color corresponding to projection name proj. If colors is a list, return colors at index of proj in list of projection names projs.

get_covstd(covariance, *args, **kwargs)¶: Return standard deviation corresponding to the input covariance matrix.

get_covx(covariance, *args, **kwargs)¶: Return x-coordinates of input covariance matrix.

get_covy(covariance, *args, **kwargs)¶: Return mean y-coordinates provided in the input covariance matrix.

get_label(proj)¶: Return label corresponding to projection name proj.

get_list(name, value=None, default=None)¶: Same as get(), but ensuring returned value is a list. Default length (see make_list()) is taken as default length.

get_projs(data_vector=None)¶: Return projection names of input data vector.

get_x(data_vector, *args, **kwargs)¶: Return x-coordinates of input data vector.

get_y(data_vector, *args, **kwargs)¶: Return y-coordinates of input data vector.

get_ylabel()¶: Return y-label, to be overriden.

classmethod load(filename, mpiroot=0, mpicomm=None)¶: Load class in numpy binary format from disk. If the loaded state contains __class__ and that exists in cls._registry, return instance of cls._registry[__class__] (instead of cls).

load_auto(*args, **kwargs)¶: If different formats are possible, this method should between them based on file name extension.

property mpiattrs¶: MPI attributes

plot(data_vectors=None, covariance=None, error_mean=None, ax=None, filename=None)¶

Plot data vectors, optionally with error bars / shaded area from covariance.

Parameters

data_vectors (list, DataVector, default=None) – Data vector(s) to plot. If None, data_vectors attribute is used.
covariance (CovarianceMatrix, default=None) – If not None, covariance matrix to use for error bars.
error_mean (int, default=None) – If not None, index of data vector in data_vectors to use as mean when plotting error bars.
ax (matplotlib.axes.Axes, default=None) – Axes where to plot data vectors. If None, takes current axes.
filename (string, default=None) – If not None, file name where to save figure.

Returns

ax

Return type

matplotlib.axes.Axes

save(filename)¶: Save class to disk.

save_auto(*args, **kwargs)¶: If different formats are possible, this method should between them based on file name extension.

savefig(filename, fig=None)¶

Save figure to filename.

Parameters

filename (string) – Path where to save figure.
fig (matplotlib.figure.Figure, default=None) – Figure to save. Defaults to current figure.

update(**kwargs)¶: Update attibutes with those in kwargs.