Plotting Module

class mmpp.plotting.PlotConfig(figsize=(12, 8), dpi=100, style='paper', colormap='viridis', line_alpha=0.7, line_width=1.5, grid=True, legend=True, title_fontsize=14, label_fontsize=12, tick_fontsize=10, use_custom_fonts=True, font_family='Arial', colors=None, max_legend_params=4, sort_results=True)[source]

Bases: object

Configuration for plotting operations.

Parameters:

figsize (tuple)
dpi (int)
style (str)
colormap (str)
line_alpha (float)
line_width (float)
grid (bool)
legend (bool)
title_fontsize (int)
label_fontsize (int)
tick_fontsize (int)
use_custom_fonts (bool)
font_family (str)
colors (Optional[dict[str, str]])
max_legend_params (int)
sort_results (bool)

figsize: tuple = (12, 8)

dpi: int = 100

style: str = 'paper'

colormap: str = 'viridis'

line_alpha: float = 0.7

line_width: float = 1.5

grid: bool = True

legend: bool = True

title_fontsize: int = 14

label_fontsize: int = 12

tick_fontsize: int = 10

use_custom_fonts: bool = True

font_family: str = 'Arial'

colors: Optional[dict[str, str]] = None

max_legend_params: int = 4

sort_results: bool = True

__post_init__()[source]

Initialize default colors.

Return type:: None

__init__(figsize=(12, 8), dpi=100, style='paper', colormap='viridis', line_alpha=0.7, line_width=1.5, grid=True, legend=True, title_fontsize=14, label_fontsize=12, tick_fontsize=10, use_custom_fonts=True, font_family='Arial', colors=None, max_legend_params=4, sort_results=True)

Parameters:

figsize (tuple)
dpi (int)
style (str)
colormap (str)
line_alpha (float)
line_width (float)
grid (bool)
legend (bool)
title_fontsize (int)
label_fontsize (int)
tick_fontsize (int)
use_custom_fonts (bool)
font_family (str)
colors (Optional[dict[str, str]])
max_legend_params (int)
sort_results (bool)

class mmpp.plotting.FontManager[source]

Bases: object

Font management utilities for plotting.

static get_available_fonts()[source]

Get list of available fonts on the system.

Return type:: list[str]

class mmpp.plotting.PlotterProxy(results, mmpp_instance=None)[source]

Bases: object

Proxy class to provide plotting functionality to search results.

Parameters:

results (list[Any])
mmpp_instance (Optional[Any])

__init__(results, mmpp_instance=None)[source]

Initialize the plotter proxy.

Parameters:

resultsList[Any]: List of results to plot
mmpp_instanceOptional[Any]: Reference to MMPP instance

param results:
type results:: list[Any]
param mmpp_instance:
type mmpp_instance:: Optional[Any]

__getattr__(name)[source]

Delegate attribute access to MMPPlotter.

Parameters:: name (str)
Return type:: Any

__repr__()[source]

String representation of the proxy.

Return type:: str

mmpp.plotting.setup_custom_fonts(verbose=False)[source]

Setup custom fonts including Arial.

Parameters:: verbose (bool)
Return type:: bool

mmpp.plotting.load_paper_style(verbose=False)[source]

Load custom paper style.

Parameters:: verbose (bool)
Return type:: bool

mmpp.plotting.apply_custom_colors(colors)[source]

Apply custom colors to matplotlib rcParams.

Parameters:: colors (dict[str, str])
Return type:: None

class mmpp.plotting.MMPPlotter(results, mmpp_instance=None)[source]

Bases: object

Advanced plotting functionality for MMPP results.

This class provides comprehensive plotting capabilities including: - Time series plotting with averaging - Multiple datasets comparison - Component selection (x, y, z) - Professional styling and customization - Custom fonts and paper-ready styling

Parameters:

results (Union[list[Any], Any])
mmpp_instance (Optional[Any])

__init__(results, mmpp_instance=None)[source]

Initialize the plotter.

Parameters:

resultsList or single result: ZarrJobResult objects to plot
mmpp_instanceMMPP, optional: Reference to the parent MMPP instance

param results:
type results:: Union[list[Any], Any]
param mmpp_instance:
type mmpp_instance:: Optional[Any]

__repr__()[source]

Rich representation of the plotter.

Return type:: str

configure(**kwargs)[source]

Configure plot settings.

Return type:: MMPPlotter

Parameters:

**kwargsAny: Configuration options: - figsize : tuple - Figure size (width, height), default (12, 8) - dpi : int - Figure DPI, default 100 - style : str - Matplotlib style, default “paper” - colormap : str - Colormap name, default “viridis” - line_alpha : float - Line transparency, default 0.7 - line_width : float - Line width, default 1.5 - grid : bool - Show grid, default True - legend : bool - Show legend, default True - title_fontsize : int - Title font size, default 14 - label_fontsize : int - Label font size, default 12 - tick_fontsize : int - Tick font size, default 10 - use_custom_fonts : bool - Use custom fonts, default True - font_family : str - Font family, default “Arial” - colors : dict - Custom colors for text/axes/grid - max_legend_params : int - Max parameters in legend, default 4 - sort_results : bool - Sort results by parameters, default True

Returns:

: MMPPlotter

Self for method chaining

Examples:

>>> plotter.configure(sort_results=False, max_legend_params=6)
>>> plotter.configure(style='dark_background', grid=False)

reset_style()[source]

Reset to paper style with Arial font.

Return type:: MMPPlotter

Returns:

: MMPPlotter

Self for method chaining

set_style(style_name)[source]

Set matplotlib style.

Return type:: MMPPlotter

Parameters:

style_namestr: Name of the matplotlib style

Returns:

: MMPPlotter

Self for method chaining

param style_name:
type style_name:: str

get_available_styles()[source]

Get list of available matplotlib styles.

Return type:: list[str]

Returns:

: List[str]

List of available style names

plot(x_series, y_series, comp=None, average=None, figsize=None, title=None, xlabel=None, ylabel=None, legend_labels=None, legend_variables=None, colors=None, save_path=None, paper_ready=False, **kwargs)[source]

Create a plot for the specified data series.

Return type:: tuple

Parameters:

x_seriesstr: Name of x-axis data (e.g., ‘t’ for time)
y_seriesstr: Name of y-axis dataset (e.g., ‘m_z11’)
compUnion[str, int], optional: Component to plot (‘x’/’y’/’z’ or 0/1/2)
averagetuple, optional: Axes to average over (e.g., (1,2,3) for spatial averaging)
figsizetuple, optional: Figure size (width, height)
titleUnion[str, List[str]], optional: Plot title. Can be: - str: Custom title text - List[str]: Parameter names to show in title (e.g., [‘amp’, ‘f0’] -> “Amp = 0.1, F0 = 1e9”)
xlabelstr, optional: X-axis label
ylabelstr, optional: Y-axis label
legend_labelsList[str], optional: Custom legend labels
legend_variablesList[str], optional: Specific variables to show in legend (e.g., [‘maxerr’, ‘f0’]). If provided, overrides automatic varying parameter detection.
colorsList[str], optional: Custom colors for each line
save_pathstr, optional: Path to save the figure
paper_readybool, optional: If True, apply paper-ready styling (default: False)
**kwargsAny: Additional matplotlib plot arguments

Returns:

: tuple

(figure, axes) matplotlib objects

param x_series:
type x_series:: str
param y_series:
type y_series:: str
param comp:
type comp:: Union[str, int, None]
param average:
type average:: Optional[tuple[Any, ...]]
param figsize:
type figsize:: Optional[tuple[Any, ...]]
param title:
type title:: Union[str, list[str], None]
param xlabel:
type xlabel:: Optional[str]
param ylabel:
type ylabel:: Optional[str]
param legend_labels:
type legend_labels:: Optional[list[str]]
param legend_variables:
type legend_variables:: Optional[list[str]]
param colors:
type colors:: Optional[list[str]]
param save_path:
type save_path:: Optional[str]
param paper_ready:
type paper_ready:: bool
param kwargs:
type kwargs:: Any

plot_time_series(dataset, comp='z', average=(1, 2, 3), **kwargs)[source]

Convenience method for time series plotting.

Return type:: tuple

Parameters:

datasetstr: Dataset name (e.g., ‘m_z11’)
compUnion[str, int], optional: Component (‘x’/’y’/’z’ or 0/1/2, default: ‘z’)
averagetuple, optional: Spatial axes to average over (default: (1,2,3))
**kwargsAny: Additional arguments passed to plot()

Returns:

: tuple

(figure, axes) matplotlib objects

param dataset:
type dataset:: str
param comp:
type comp:: Union[str, int]
param average:
type average:: tuple
param kwargs:
type kwargs:: Any

plot_components(dataset, time_slice=-1, average=(1, 2, 3), **kwargs)[source]

Plot all three components of a dataset.

Return type:: tuple

Parameters:

datasetstr: Dataset name
time_sliceint, optional: Time slice to plot (default: -1 for last)
averagetuple, optional: Axes to average over
**kwargsAny: Additional plot arguments

Returns:

: tuple

(figure, axes) matplotlib objects

param dataset:
type dataset:: str
param time_slice:
type time_slice:: int
param average:
type average:: tuple
param kwargs:
type kwargs:: Any

get_plot_data()[source]

Get data from the last plot for further analysis.

Return type:: list[dict]

Returns:

: List[Dict]

List of dictionaries containing plot data and metadata

save_all_data(filename, format='npz')[source]

Save all plotted data to file.

Return type:: None

Parameters:

filenamestr: Output filename
formatstr, optional: Format (‘npz’, ‘csv’, ‘json’)

param filename:
type filename:: str
param format:
type format:: str

snapshot(dset=None, z=0, t=-1, ax=None, repeat=1, zero=None)[source]

Create a snapshot visualization of magnetization data.

Return type:: Any

Parameters:

dsetstr, optional: Dataset name. If None, automatically selects the largest m dataset. Dataset name to visualize
zint, default 0: Z-slice to display
tint, default -1: Time step to display (-1 for last)
axOptional[Axes], default None: Matplotlib axes to plot on (creates new if None)
repeatint, default 1: Number of times to tile the image
zeroOptional[bool], default None: Reference time step to subtract (for difference plots)

Returns:

: Axes

Matplotlib axes object with the plot

param dset:
type dset:: Optional[str]
param z:
type z:: int
param t:
type t:: int
param ax:
type ax:: Optional[Any]
param repeat:
type repeat:: int
param zero:
type zero:: Optional[bool]

mmpp.plotting.hsl2rgb(hsl)[source]

Convert HSL color space to RGB.

Return type:: ndarray

Parameters:

hslnp.ndarray: HSL color array with shape (…, 3)

Returns:

: np.ndarray

RGB color array with same shape

param hsl:
type hsl:: ndarray

mmpp.plotting.rgb2hsl(rgb)[source]

Convert RGB color space to HSL.

Return type:: ndarray

Parameters:

rgbnp.ndarray: RGB color array with shape (…, 3)

Returns:

: np.ndarray

HSL color array with same shape

param rgb:
type rgb:: ndarray

class mmpp.plotting.FontUtils[source]

Bases: object

Utility object for font management.

static get_available()[source]

Get available fonts.

Return type:: list[str]

static setup_custom(verbose=True)[source]

Setup custom fonts.

Parameters:: verbose (bool)
Return type:: bool

Plotting Classes

MMPPlotter

class mmpp.plotting.MMPPlotter(results, mmpp_instance=None)[source]

Bases: object

Advanced plotting functionality for MMPP results.

This class provides comprehensive plotting capabilities including: - Time series plotting with averaging - Multiple datasets comparison - Component selection (x, y, z) - Professional styling and customization - Custom fonts and paper-ready styling

Parameters:

results (Union[list[Any], Any])
mmpp_instance (Optional[Any])

__init__(results, mmpp_instance=None)[source]

Initialize the plotter.

Parameters:

resultsList or single result: ZarrJobResult objects to plot
mmpp_instanceMMPP, optional: Reference to the parent MMPP instance

param results:
type results:: Union[list[Any], Any]
param mmpp_instance:
type mmpp_instance:: Optional[Any]

__repr__()[source]

Rich representation of the plotter.

Return type:: str

configure(**kwargs)[source]

Configure plot settings.

Return type:: MMPPlotter

Parameters:

**kwargsAny: Configuration options: - figsize : tuple - Figure size (width, height), default (12, 8) - dpi : int - Figure DPI, default 100 - style : str - Matplotlib style, default “paper” - colormap : str - Colormap name, default “viridis” - line_alpha : float - Line transparency, default 0.7 - line_width : float - Line width, default 1.5 - grid : bool - Show grid, default True - legend : bool - Show legend, default True - title_fontsize : int - Title font size, default 14 - label_fontsize : int - Label font size, default 12 - tick_fontsize : int - Tick font size, default 10 - use_custom_fonts : bool - Use custom fonts, default True - font_family : str - Font family, default “Arial” - colors : dict - Custom colors for text/axes/grid - max_legend_params : int - Max parameters in legend, default 4 - sort_results : bool - Sort results by parameters, default True

Returns:

: MMPPlotter

Self for method chaining

Examples:

>>> plotter.configure(sort_results=False, max_legend_params=6)
>>> plotter.configure(style='dark_background', grid=False)

reset_style()[source]

Reset to paper style with Arial font.

Return type:: MMPPlotter

Returns:

: MMPPlotter

Self for method chaining

set_style(style_name)[source]

Set matplotlib style.

Return type:: MMPPlotter

Parameters:

style_namestr: Name of the matplotlib style

Returns:

: MMPPlotter

Self for method chaining

param style_name:
type style_name:: str

get_available_styles()[source]

Get list of available matplotlib styles.

Return type:: list[str]

Returns:

: List[str]

List of available style names

plot(x_series, y_series, comp=None, average=None, figsize=None, title=None, xlabel=None, ylabel=None, legend_labels=None, legend_variables=None, colors=None, save_path=None, paper_ready=False, **kwargs)[source]

Create a plot for the specified data series.

Return type:: tuple

Parameters:

x_seriesstr: Name of x-axis data (e.g., ‘t’ for time)
y_seriesstr: Name of y-axis dataset (e.g., ‘m_z11’)
compUnion[str, int], optional: Component to plot (‘x’/’y’/’z’ or 0/1/2)
averagetuple, optional: Axes to average over (e.g., (1,2,3) for spatial averaging)
figsizetuple, optional: Figure size (width, height)
titleUnion[str, List[str]], optional: Plot title. Can be: - str: Custom title text - List[str]: Parameter names to show in title (e.g., [‘amp’, ‘f0’] -> “Amp = 0.1, F0 = 1e9”)
xlabelstr, optional: X-axis label
ylabelstr, optional: Y-axis label
legend_labelsList[str], optional: Custom legend labels
legend_variablesList[str], optional: Specific variables to show in legend (e.g., [‘maxerr’, ‘f0’]). If provided, overrides automatic varying parameter detection.
colorsList[str], optional: Custom colors for each line
save_pathstr, optional: Path to save the figure
paper_readybool, optional: If True, apply paper-ready styling (default: False)
**kwargsAny: Additional matplotlib plot arguments

Returns:

: tuple

(figure, axes) matplotlib objects

param x_series:
type x_series:: str
param y_series:
type y_series:: str
param comp:
type comp:: Union[str, int, None]
param average:
type average:: Optional[tuple[Any, ...]]
param figsize:
type figsize:: Optional[tuple[Any, ...]]
param title:
type title:: Union[str, list[str], None]
param xlabel:
type xlabel:: Optional[str]
param ylabel:
type ylabel:: Optional[str]
param legend_labels:
type legend_labels:: Optional[list[str]]
param legend_variables:
type legend_variables:: Optional[list[str]]
param colors:
type colors:: Optional[list[str]]
param save_path:
type save_path:: Optional[str]
param paper_ready:
type paper_ready:: bool
param kwargs:
type kwargs:: Any

plot_time_series(dataset, comp='z', average=(1, 2, 3), **kwargs)[source]

Convenience method for time series plotting.

Return type:: tuple

Parameters:

datasetstr: Dataset name (e.g., ‘m_z11’)
compUnion[str, int], optional: Component (‘x’/’y’/’z’ or 0/1/2, default: ‘z’)
averagetuple, optional: Spatial axes to average over (default: (1,2,3))
**kwargsAny: Additional arguments passed to plot()

Returns:

: tuple

(figure, axes) matplotlib objects

param dataset:
type dataset:: str
param comp:
type comp:: Union[str, int]
param average:
type average:: tuple
param kwargs:
type kwargs:: Any

plot_components(dataset, time_slice=-1, average=(1, 2, 3), **kwargs)[source]

Plot all three components of a dataset.

Return type:: tuple

Parameters:

datasetstr: Dataset name
time_sliceint, optional: Time slice to plot (default: -1 for last)
averagetuple, optional: Axes to average over
**kwargsAny: Additional plot arguments

Returns:

: tuple

(figure, axes) matplotlib objects

param dataset:
type dataset:: str
param time_slice:
type time_slice:: int
param average:
type average:: tuple
param kwargs:
type kwargs:: Any

get_plot_data()[source]

Get data from the last plot for further analysis.

Return type:: list[dict]

Returns:

: List[Dict]

List of dictionaries containing plot data and metadata

save_all_data(filename, format='npz')[source]

Save all plotted data to file.

Return type:: None

Parameters:

filenamestr: Output filename
formatstr, optional: Format (‘npz’, ‘csv’, ‘json’)

param filename:
type filename:: str
param format:
type format:: str

snapshot(dset=None, z=0, t=-1, ax=None, repeat=1, zero=None)[source]

Create a snapshot visualization of magnetization data.

Return type:: Any

Parameters:

dsetstr, optional: Dataset name. If None, automatically selects the largest m dataset. Dataset name to visualize
zint, default 0: Z-slice to display
tint, default -1: Time step to display (-1 for last)
axOptional[Axes], default None: Matplotlib axes to plot on (creates new if None)
repeatint, default 1: Number of times to tile the image
zeroOptional[bool], default None: Reference time step to subtract (for difference plots)

Returns:

: Axes

Matplotlib axes object with the plot

param dset:
type dset:: Optional[str]
param z:
type z:: int
param t:
type t:: int
param ax:
type ax:: Optional[Any]
param repeat:
type repeat:: int
param zero:
type zero:: Optional[bool]

PlotterProxy

class mmpp.plotting.PlotterProxy(results, mmpp_instance=None)[source]

Bases: object

Proxy class to provide plotting functionality to search results.

Parameters:

results (list[Any])
mmpp_instance (Optional[Any])

__init__(results, mmpp_instance=None)[source]

Initialize the plotter proxy.

Parameters:

resultsList[Any]: List of results to plot
mmpp_instanceOptional[Any]: Reference to MMPP instance

param results:
type results:: list[Any]
param mmpp_instance:
type mmpp_instance:: Optional[Any]

__getattr__(name)[source]

Delegate attribute access to MMPPlotter.

Parameters:: name (str)
Return type:: Any

__repr__()[source]

String representation of the proxy.

Return type:: str

Configuration Classes

class mmpp.plotting.PlotConfig(figsize=(12, 8), dpi=100, style='paper', colormap='viridis', line_alpha=0.7, line_width=1.5, grid=True, legend=True, title_fontsize=14, label_fontsize=12, tick_fontsize=10, use_custom_fonts=True, font_family='Arial', colors=None, max_legend_params=4, sort_results=True)[source]

Bases: object

Configuration for plotting operations.

Parameters:

figsize (tuple)
dpi (int)
style (str)
colormap (str)
line_alpha (float)
line_width (float)
grid (bool)
legend (bool)
title_fontsize (int)
label_fontsize (int)
tick_fontsize (int)
use_custom_fonts (bool)
font_family (str)
colors (Optional[dict[str, str]])
max_legend_params (int)
sort_results (bool)

figsize: tuple = (12, 8)

dpi: int = 100

style: str = 'paper'

colormap: str = 'viridis'

line_alpha: float = 0.7

line_width: float = 1.5

grid: bool = True

legend: bool = True

title_fontsize: int = 14

label_fontsize: int = 12

tick_fontsize: int = 10

use_custom_fonts: bool = True

font_family: str = 'Arial'

colors: Optional[dict[str, str]] = None

max_legend_params: int = 4

sort_results: bool = True

__post_init__()[source]

Initialize default colors.

Return type:: None

__init__(figsize=(12, 8), dpi=100, style='paper', colormap='viridis', line_alpha=0.7, line_width=1.5, grid=True, legend=True, title_fontsize=14, label_fontsize=12, tick_fontsize=10, use_custom_fonts=True, font_family='Arial', colors=None, max_legend_params=4, sort_results=True)

Parameters:

figsize (tuple)
dpi (int)
style (str)
colormap (str)
line_alpha (float)
line_width (float)
grid (bool)
legend (bool)
title_fontsize (int)
label_fontsize (int)
tick_fontsize (int)
use_custom_fonts (bool)
font_family (str)
colors (Optional[dict[str, str]])
max_legend_params (int)
sort_results (bool)

Usage Examples

Basic Plotting

import mmpp as mp

# Load results
op = mp.open("/path/to/simulations")
results = op.find(solver=3)

# Create plots
results.plot("time", "my")
results.plot("B_ext", "frequency", comp="z")

Advanced Plotting Options

# Customize plot appearance
results.set_style("paper")

# Plot with custom parameters
results.plot(
    "time", "mx",
    figsize=(10, 6),
    title="Magnetization Evolution",
    xlabel="Time (ns)",
    ylabel="Mx Component"
)

Snapshot Visualization

# Create spatial snapshots
result = op[0]
result.matplotlib.snapshot(
    dset="m",
    z=5,
    t=-1,  # Last time step
    repeat=2
)