Time Series Plots
Contents
Time Series Plots#
This module holds time-series plotting functions.
These plotting functions have in common, that they represent some kind of time series. The time may be visualized on the x-axis or in some other way, e.g. via the color of scatter points.
- utopya.plot_funcs.time_series.density(dm: utopya.datamanager.DataManager, *, uni: utopya.datagroup.UniverseGroup, hlpr: utopya.plotting.PlotHelper, model_name: str, path_to_data: str, mean_of: Tuple[str], preprocess: Optional[Tuple[Union[dict, str]]] = None, transformations_log_level: int = 10, sizes_from: Optional[str] = None, size_factor: float = 1.0, **plot_kwargs) None [source]
Plot the density of a mask, i.e. of a dataset holding booleans.
This plotting function is useful when creating a plot from data that is encoded in a binary fashion, e.g.: arrays containing True to denote the existence of some entity or some value and False to denote its absence.
If the dataset chosen via
path_to_data
is not already of boolean data type, thepreprocess
argument is to be used to generate the array-like boolean. By means of this argument, a binary operation of formdata <operator> rhs_value
is carried out, which results in the desired mask.Another feature of this plotting function is that it can include another data source to use for the sizes of the plots; in that case, a scatter plot rather than a line plot is carried out.
- Parameters
dm (DataManager) – The data manager from which to retrieve the data
uni (UniverseGroup) – The selected universe data
hlpr (PlotHelper) – The PlotHelper that instantiates the figure and takes care of plot aesthetics (labels, title, …) and saving
model_name (str) – The name of the model the data resides in, i.e. the base path within the UniverseGroup.
path_to_data (str) – Which data to use as the mask
mean_of (Tuple[str], optional) – which data dimensions to calculate the density over. If this evaluates to False, the operation will be skipped
preprocess (Tuple[Union[str, dict]], optional) – Apply pre-processing transformations to the selected data. With the parameters specified here, multiple transformations can be applied to the data. This can be used for dimensionality reduction of the data, but also for other operations, e.g. to select only a slice of the data. See
utopya.dataprocessing.transform()
for more info. NOTE The operations are carried out _before_ calculating the density over the parameters specified inmean_of
. Thepreprocess
ing should not be used for calculating the mean.transformations_log_level (int, optional) – With which log level to perform the preprocess. Useful for debugging.
sizes_from (str, optional) – If given, this is expected to be the path to a dataset that contains size values for a scatter plot. This leads to a scatter rather than a line-plot. The sizes are not used directly but are normalized by dividing with the maximum size; this makes configuration via the
size_factor
parameter feasible.size_factor (float, optional) – The factor by which to scale the sizes given in the
sizes_from
argument.**plot_kwargs – Passed on to plt.plot or plt.scatter
- Raises
ValueError – If the selected data is not a boolean mask. This error can be alleviated by providing the
preprocess
argument.- Returns
Description
- Return type
None
- utopya.plot_funcs.time_series.densities(dm: utopya.datamanager.DataManager, *, uni: utopya.datagroup.UniverseGroup, hlpr: utopya.plotting.PlotHelper, model_name: str, to_plot: dict, **common_plot_kwargs)[source]
Like density, but for several specifications given by the
to_plot
argument.- Parameters
dm (DataManager) – The data manager from which to retrieve the data
uni (UniverseGroup) – The selected universe data
hlpr (PlotHelper) – The PlotHelper that instantiates the figure and takes care of plot aesthetics (labels, title, …) and saving
model_name (str) – The name of the model the data resides in, i.e. the base path within the UniverseGroup.
to_plot (dict) – Which data to plot the densities of. The keys of this dict are used as
path_to_data
for thedensity
function. The values are unpacked and passed todensity
**common_plot_kwargs – Passed along to the
density
plot function for all calls. Note that this may not contain any keys that are given withinto_plot
!
- utopya.plot_funcs.time_series.phase_space(dm: utopya.datamanager.DataManager, *, uni: utopya.datagroup.UniverseGroup, hlpr: utopya.plotting.PlotHelper, model_name: str, x: str, y: str, cmap: Optional[str] = None, **scatter_kwargs)[source]
Plots
x
andy
data in a phase space plot. Ifcmap
is given, the time development will be colour coded.Note
This automatically calculates the mean over all but the
time
dimension of the data.- Parameters
dm (DataManager) – The data manager from which to retrieve the data
uni (UniverseGroup) – The universe from which to plot the data
hlpr (PlotHelper) – The PlotHelper instance
model_name (str) – The model name from which to take the data
x (str) – The path to the data relative to the model_name which to plot on the x axis of the phase space plot.
y (str) – The path to the data relative to the model_name which to plot on the x axis of the phase space plot
cmap (str, optional) – The cmap which is used to color-code the time development. If not given, will not color-code it.
**scatter_kwargs – Passed on to plt.scatter
Density#
- utopya.plot_funcs.time_series.density(dm: utopya.datamanager.DataManager, *, uni: utopya.datagroup.UniverseGroup, hlpr: utopya.plotting.PlotHelper, model_name: str, path_to_data: str, mean_of: Tuple[str], preprocess: Optional[Tuple[Union[dict, str]]] = None, transformations_log_level: int = 10, sizes_from: Optional[str] = None, size_factor: float = 1.0, **plot_kwargs) None [source]
Plot the density of a mask, i.e. of a dataset holding booleans.
This plotting function is useful when creating a plot from data that is encoded in a binary fashion, e.g.: arrays containing True to denote the existence of some entity or some value and False to denote its absence.
If the dataset chosen via
path_to_data
is not already of boolean data type, thepreprocess
argument is to be used to generate the array-like boolean. By means of this argument, a binary operation of formdata <operator> rhs_value
is carried out, which results in the desired mask.Another feature of this plotting function is that it can include another data source to use for the sizes of the plots; in that case, a scatter plot rather than a line plot is carried out.
- Parameters
dm (DataManager) – The data manager from which to retrieve the data
uni (UniverseGroup) – The selected universe data
hlpr (PlotHelper) – The PlotHelper that instantiates the figure and takes care of plot aesthetics (labels, title, …) and saving
model_name (str) – The name of the model the data resides in, i.e. the base path within the UniverseGroup.
path_to_data (str) – Which data to use as the mask
mean_of (Tuple[str], optional) – which data dimensions to calculate the density over. If this evaluates to False, the operation will be skipped
preprocess (Tuple[Union[str, dict]], optional) – Apply pre-processing transformations to the selected data. With the parameters specified here, multiple transformations can be applied to the data. This can be used for dimensionality reduction of the data, but also for other operations, e.g. to select only a slice of the data. See
utopya.dataprocessing.transform()
for more info. NOTE The operations are carried out _before_ calculating the density over the parameters specified inmean_of
. Thepreprocess
ing should not be used for calculating the mean.transformations_log_level (int, optional) – With which log level to perform the preprocess. Useful for debugging.
sizes_from (str, optional) – If given, this is expected to be the path to a dataset that contains size values for a scatter plot. This leads to a scatter rather than a line-plot. The sizes are not used directly but are normalized by dividing with the maximum size; this makes configuration via the
size_factor
parameter feasible.size_factor (float, optional) – The factor by which to scale the sizes given in the
sizes_from
argument.**plot_kwargs – Passed on to plt.plot or plt.scatter
- Raises
ValueError – If the selected data is not a boolean mask. This error can be alleviated by providing the
preprocess
argument.- Returns
Description
- Return type
None
Multiple Densities#
- utopya.plot_funcs.time_series.densities(dm: utopya.datamanager.DataManager, *, uni: utopya.datagroup.UniverseGroup, hlpr: utopya.plotting.PlotHelper, model_name: str, to_plot: dict, **common_plot_kwargs)[source]
Like density, but for several specifications given by the
to_plot
argument.- Parameters
dm (DataManager) – The data manager from which to retrieve the data
uni (UniverseGroup) – The selected universe data
hlpr (PlotHelper) – The PlotHelper that instantiates the figure and takes care of plot aesthetics (labels, title, …) and saving
model_name (str) – The name of the model the data resides in, i.e. the base path within the UniverseGroup.
to_plot (dict) – Which data to plot the densities of. The keys of this dict are used as
path_to_data
for thedensity
function. The values are unpacked and passed todensity
**common_plot_kwargs – Passed along to the
density
plot function for all calls. Note that this may not contain any keys that are given withinto_plot
!
Phase Space#
- utopya.plot_funcs.time_series.phase_space(dm: utopya.datamanager.DataManager, *, uni: utopya.datagroup.UniverseGroup, hlpr: utopya.plotting.PlotHelper, model_name: str, x: str, y: str, cmap: Optional[str] = None, **scatter_kwargs)[source]
Plots
x
andy
data in a phase space plot. Ifcmap
is given, the time development will be colour coded.Note
This automatically calculates the mean over all but the
time
dimension of the data.- Parameters
dm (DataManager) – The data manager from which to retrieve the data
uni (UniverseGroup) – The universe from which to plot the data
hlpr (PlotHelper) – The PlotHelper instance
model_name (str) – The model name from which to take the data
x (str) – The path to the data relative to the model_name which to plot on the x axis of the phase space plot.
y (str) – The path to the data relative to the model_name which to plot on the x axis of the phase space plot
cmap (str, optional) – The cmap which is used to color-code the time development. If not given, will not color-code it.
**scatter_kwargs – Passed on to plt.scatter