hedvis configuration classes¶

Visualization configuration¶

Configuration classes for HED visualizations.

class hedvis.core.visualization_config.WordCloudConfig(width: int = 800, height: int = 600, background_color: str | None = None, prefer_horizontal: float = 0.75, min_font_size: int = 8, max_font_size: int | None = None, font_path: str | None = None, colormap: str = 'nipy_spectral', color_range: tuple = (0.0, 0.5), color_step_range: tuple = (0.15, 0.25), use_mask: bool = False, mask_path: str | None = None, contour_width: float = 3.0, contour_color: str = 'black', scale_adjustment: float = 0.0, relative_scaling: float = 1.0)[source]¶

Bases: object

Configuration for word cloud visualizations.

width¶

Width of word cloud in pixels.

Type:: int

height¶

Height of word cloud in pixels.

Type:: int

background_color¶

Background color name or None for transparent.

Type:: str | None

prefer_horizontal¶

Fraction of words oriented horizontally (0.0-1.0).

Type:: float

min_font_size¶

Minimum font size in points.

Type:: int

max_font_size¶

Maximum font size in points (auto-calculated if None).

Type:: int | None

font_path¶

Path to TTF/OTF font file (None uses default).

Type:: str | None

colormap¶

Matplotlib colormap name for word colors.

Type:: str

color_range¶

Tuple of (min, max) values from colormap to use.

Type:: tuple

color_step_range¶

Tuple of (min, max) step sizes through colormap.

Type:: tuple

use_mask¶

Whether to use a mask image to shape the cloud.

Type:: bool

mask_path¶

Path to mask image file (PNG/JPEG).

Type:: str | None

contour_width¶

Width of contour line around masked region.

Type:: float

contour_color¶

Color name for contour line.

Type:: str

scale_adjustment¶

Adjustment factor for log-transformed frequencies.

Type:: float

relative_scaling¶

Scaling factor for word sizes (0.0-1.0).

Type:: float

width: int = 800¶

height: int = 600¶

background_color: str | None = None¶

prefer_horizontal: float = 0.75¶

min_font_size: int = 8¶

max_font_size: int | None = None¶

font_path: str | None = None¶

colormap: str = 'nipy_spectral'¶

color_range: tuple = (0.0, 0.5)¶

color_step_range: tuple = (0.15, 0.25)¶

use_mask: bool = False¶

mask_path: str | None = None¶

contour_width: float = 3.0¶

contour_color: str = 'black'¶

scale_adjustment: float = 0.0¶

relative_scaling: float = 1.0¶

classmethod from_dict(config_dict: Dict[str, Any]) → WordCloudConfig[source]¶

Create configuration from dictionary.

Parameters:: config_dict – Dictionary with configuration parameters.
Returns:: Configuration object.
Return type:: WordCloudConfig

to_dict() → Dict[str, Any][source]¶

Convert configuration to dictionary.

Returns:: Dictionary representation of configuration.
Return type:: dict

__init__(width: int = 800, height: int = 600, background_color: str | None = None, prefer_horizontal: float = 0.75, min_font_size: int = 8, max_font_size: int | None = None, font_path: str | None = None, colormap: str = 'nipy_spectral', color_range: tuple = (0.0, 0.5), color_step_range: tuple = (0.15, 0.25), use_mask: bool = False, mask_path: str | None = None, contour_width: float = 3.0, contour_color: str = 'black', scale_adjustment: float = 0.0, relative_scaling: float = 1.0) → None¶

class hedvis.core.visualization_config.VisualizationConfig(output_formats: ~typing.List[str] = <factory>, save_directory: str | None = None, word_cloud: ~hedvis.core.visualization_config.WordCloudConfig | None = None)[source]¶

Bases: object

Master configuration for all HED visualizations.

output_formats¶

List of output formats (‘svg’, ‘png’, ‘jpg’, etc.).

Type:: List[str]

save_directory¶

Directory path for saving visualizations (None = don’t save).

Type:: str | None

word_cloud¶

Configuration for word cloud visualization (None = don’t generate).

Type:: hedvis.core.visualization_config.WordCloudConfig | None

output_formats: List[str]¶

save_directory: str | None = None¶

word_cloud: WordCloudConfig | None = None¶

classmethod from_dict(config_dict: Dict[str, Any]) → VisualizationConfig[source]¶

Create configuration from dictionary.

Parameters:: config_dict – Dictionary with configuration parameters.
Returns:: Configuration object.
Return type:: VisualizationConfig

Notes

Nested dictionaries are automatically converted to appropriate config objects.

to_dict() → Dict[str, Any][source]¶

Convert configuration to dictionary.

Returns:: Dictionary representation of configuration.
Return type:: dict

__init__(output_formats: ~typing.List[str] = <factory>, save_directory: str | None = None, word_cloud: ~hedvis.core.visualization_config.WordCloudConfig | None = None) → None¶

VisualizationConfig¶

Bases: object

Master configuration for all HED visualizations.

output_formats¶

List of output formats (‘svg’, ‘png’, ‘jpg’, etc.).

Type:: List[str]

save_directory¶

Directory path for saving visualizations (None = don’t save).

Type:: str | None

word_cloud¶

Configuration for word cloud visualization (None = don’t generate).

Type:: hedvis.core.visualization_config.WordCloudConfig | None

Main configuration class for visualization generation.

Attributes:

word_cloud (WordCloudConfig) - Word cloud settings
output_formats (list) - List of output formats [‘png’, ‘svg’]
save_directory (str) - Directory for saving outputs
save_files (bool) - Whether to automatically save files

Example:

from hedvis import VisualizationConfig, WordCloudConfig

config = VisualizationConfig(
    word_cloud=WordCloudConfig(width=1000, height=600),
    output_formats=["png", "svg"],
    save_directory="./outputs",
    save_files=True
)

From dictionary:

config_dict = {
    "word_cloud": {"width": 800, "height": 600},
    "output_formats": ["svg"]
}
config = VisualizationConfig.from_dict(config_dict)

output_formats: List[str]¶

save_directory: str | None = None¶

word_cloud: WordCloudConfig | None = None¶

classmethod from_dict(config_dict: Dict[str, Any]) → VisualizationConfig[source]¶

Create configuration from dictionary.

Parameters:: config_dict – Dictionary with configuration parameters.
Returns:: Configuration object.
Return type:: VisualizationConfig

Notes

Nested dictionaries are automatically converted to appropriate config objects.

to_dict() → Dict[str, Any][source]¶

Convert configuration to dictionary.

Returns:: Dictionary representation of configuration.
Return type:: dict

__init__(output_formats: ~typing.List[str] = <factory>, save_directory: str | None = None, word_cloud: ~hedvis.core.visualization_config.WordCloudConfig | None = None) → None¶

WordCloudConfig¶

Bases: object

Configuration for word cloud visualizations.

width¶

Width of word cloud in pixels.

Type:: int

height¶

Height of word cloud in pixels.

Type:: int

background_color¶

Background color name or None for transparent.

Type:: str | None

prefer_horizontal¶

Fraction of words oriented horizontally (0.0-1.0).

Type:: float

min_font_size¶

Minimum font size in points.

Type:: int

max_font_size¶

Maximum font size in points (auto-calculated if None).

Type:: int | None

font_path¶

Path to TTF/OTF font file (None uses default).

Type:: str | None

colormap¶

Matplotlib colormap name for word colors.

Type:: str

color_range¶

Tuple of (min, max) values from colormap to use.

Type:: tuple

color_step_range¶

Tuple of (min, max) step sizes through colormap.

Type:: tuple

use_mask¶

Whether to use a mask image to shape the cloud.

Type:: bool

mask_path¶

Path to mask image file (PNG/JPEG).

Type:: str | None

contour_width¶

Width of contour line around masked region.

Type:: float

contour_color¶

Color name for contour line.

Type:: str

scale_adjustment¶

Adjustment factor for log-transformed frequencies.

Type:: float

relative_scaling¶

Scaling factor for word sizes (0.0-1.0).

Type:: float

Configuration for word cloud visualizations.

Dimension Attributes:

width (int) - Width in pixels (default: 800)
height (int) - Height in pixels (default: 600)

Appearance Attributes:

background_color (str or None) - Background color (None for transparent)
prefer_horizontal (float) - Fraction of horizontal text (0.0-1.0)
min_font_size (int) - Minimum font size
max_font_size (int or None) - Maximum font size (auto if None)

Font Attributes:

font_path (str or None) - Path to custom font file (.ttf, .otf)

Color Scheme Attributes:

colormap (str) - Matplotlib colormap name (default: ‘nipy_spectral’)
color_range (tuple) - (min, max) range of colormap to use
color_step_range (tuple) - (min, max) step sizes through colormap

Mask Attributes:

use_mask (bool) - Whether to use mask image
mask_path (str or None) - Path to mask image
contour_width (int) - Width of contour line
contour_color (str) - Color of contour line

Scaling Attributes:

scale_adjustment (float) - Frequency scaling adjustment
relative_scaling (float) - Word size scaling factor (0.0-1.0)

Example:

Basic configuration:

from hedvis import WordCloudConfig

config = WordCloudConfig(
    width=1200,
    height=800,
    background_color="white",
    colormap="viridis"
)

Masked word cloud:

config = WordCloudConfig(
    use_mask=True,
    mask_path="brain_outline.png",
    background_color="white",
    contour_width=3,
    contour_color="navy"
)

Custom colors and fonts:

config = WordCloudConfig(
    font_path="/path/to/custom-font.ttf",
    colormap="plasma",
    color_range=(0.2, 0.8),
    prefer_horizontal=0.9
)

width: int = 800¶

height: int = 600¶

background_color: str | None = None¶

prefer_horizontal: float = 0.75¶

min_font_size: int = 8¶

max_font_size: int | None = None¶

font_path: str | None = None¶

colormap: str = 'nipy_spectral'¶

color_range: tuple = (0.0, 0.5)¶

color_step_range: tuple = (0.15, 0.25)¶

use_mask: bool = False¶

mask_path: str | None = None¶

contour_width: float = 3.0¶

contour_color: str = 'black'¶

scale_adjustment: float = 0.0¶

relative_scaling: float = 1.0¶

classmethod from_dict(config_dict: Dict[str, Any]) → WordCloudConfig[source]¶

Create configuration from dictionary.

Parameters:: config_dict – Dictionary with configuration parameters.
Returns:: Configuration object.
Return type:: WordCloudConfig

to_dict() → Dict[str, Any][source]¶

Convert configuration to dictionary.

Returns:: Dictionary representation of configuration.
Return type:: dict

__init__(width: int = 800, height: int = 600, background_color: str | None = None, prefer_horizontal: float = 0.75, min_font_size: int = 8, max_font_size: int | None = None, font_path: str | None = None, colormap: str = 'nipy_spectral', color_range: tuple = (0.0, 0.5), color_step_range: tuple = (0.15, 0.25), use_mask: bool = False, mask_path: str | None = None, contour_width: float = 3.0, contour_color: str = 'black', scale_adjustment: float = 0.0, relative_scaling: float = 1.0) → None¶