wolfhece.matplotlib_fig

Module Contents

wolfhece.matplotlib_fig.sanitize_fmt(fmt)

Sanitizes the given format string for numerical formatting. This function ensures that the format string is in a valid format for floating-point number representation. If the input format string is ‘None’ or an empty string, it defaults to ‘.2f’. Otherwise, it ensures that the format string contains a decimal point and ends with ‘f’ for floating-point representation. If the format string is ‘.f’, it defaults to ‘.2f’.

Parameters:

fmt (str) – The format string to be sanitized.

Returns:

A sanitized format string suitable for floating-point number formatting.

Return type:

str

class wolfhece.matplotlib_fig.Matplotlib_ax_properties(ax=None)

property is_equal

reset_selection()

select_line(idx: int)

set_ax(ax: matplotlib.axes.Axes)

_set_props()

Set the properties UI

populate()

Populate the properties UI

ui()

destroyprop()

bounds_lines()

fill_property(verbosity=True)

set_properties(ax: matplotlib.axes.Axes = None)

get_properties(ax: matplotlib.axes.Axes = None)

to_dict() → str

properties to dict

from_dict(props: dict, frame: wx.Frame = None)

properties from dict

serialize()

Serialize the properties

deserialize(props: str)

Deserialize the properties

add_props_to_sizer(frame: wx.Frame, sizer: wx.BoxSizer)

Add the properties to a sizer

show_props()

Show the properties

hide_props()

Hide the properties

hide_all_props()

Hide all properties

del_line(idx: int)

Delete a line

wolfhece.matplotlib_fig.MARKERS_MPL = ['None', 'o', 'v', '^', '<', '>', 's', 'p', 'P', '*', 'h', 'H', '+', 'x', 'X', 'D', 'd', '|', '_']

wolfhece.matplotlib_fig.LINESTYLE_MPL = ['-', '--', '-.', ':', 'solid', 'dashed', 'dashdot', 'dotted', 'None']

wolfhece.matplotlib_fig.convert_colorname_rgb(color: str) → str

Convert a given color name or abbreviation to its corresponding RGB tuple.

Parameters:

color (str) – The color name or abbreviation to convert. Supported colors are ‘b’/’blue’, ‘g’/’green’, ‘r’/’red’, ‘c’/’cyan’, ‘m’/’magenta’, ‘y’/’yellow’, ‘k’/’black’, ‘w’/’white’, and ‘o’/’orange’.

Returns:

A tuple representing the RGB values of the color. If the color is not recognized, returns (0, 0, 0) which corresponds to black.

Return type:

tuple

wolfhece.matplotlib_fig.convert_color(value: str | tuple) → tuple

Convert a hex color to RGB

class wolfhece.matplotlib_fig.Matplolib_line_properties(line: matplotlib.lines.Line2D = None, ax_props: Matplotlib_ax_properties = None)

property ax_props

property ax

property fig

property selected

property linestyle

property marker

copy()

presets(preset: str)

Set the properties to a preset

set_line(line: matplotlib.lines.Line2D)

on_pick(line: matplotlib.lines.Line2D, mouseevent: matplotlib.backend_bases.MouseEvent)

get_properties(line: matplotlib.lines.Line2D = None)

_set_props()

Set the properties UI

populate()

Populate the properties UI

ui()

destroyprop()

fill_property(verbosity: bool = True)

set_properties(line: matplotlib.lines.Line2D = None)

show_properties()

to_dict() → str

properties to dict

from_dict(props: dict)

properties from dict

add_props_to_sizer(frame: wx.Frame, sizer: wx.BoxSizer)

Add the properties to a sizer

show_props()

Show the properties

hide_props()

Hide the properties

delete()

Delete the properties

class wolfhece.matplotlib_fig.PRESET_LAYOUTS

Bases: enum.Enum

Generic enumeration.

Derive from this class to define new enumerations.

DEFAULT = (1, 1)

MAT2X2 = (2, 2)

class wolfhece.matplotlib_fig.Matplotlib_Figure(layout: tuple | list | dict | PRESET_LAYOUTS = None)

Bases: wx.Frame

Matplotlib Figure with wx Frame

property layout

property fig_properties: Matplotlib_figure_properties

property _axes_properties: list[Matplotlib_ax_properties]

property nbrows

property nbcols

property nb_axes

property cur_ax: matplotlib.axes.Axes

property cur_ax_properties: Matplotlib_ax_properties

property cur_line_properties: Matplolib_line_properties

property cur_line: matplotlib.lines.Line2D

presets(which: PRESET_LAYOUTS = PRESET_LAYOUTS.DEFAULT)

Presets

apply_layout(layout: tuple | list | dict | PRESET_LAYOUTS)

Apply the layout

Choose between (subplots, subplot_mosaic, gridspec) according to the type of layout (tuple, list[str], dict)

set_wx()

Set the wx Frame Design

on_save(event)

Save the figure

on_load(event)

Load the figure

ChangeCursor(event: matplotlib.backend_bases.MouseEvent)

UpdateStatusBar(event: matplotlib.backend_bases.MouseEvent)

_mask_all_axes_props()

_show_axes_props(idx: int)

get_figax()

on_close(event)

on_fig_properties(event)

Show the figure properties

show_fig_properties()

_fill_lines_ax(idx: int = None)

on_ax_choice(event)

on_ax_properties(event)

Show the ax properties

show_curax_properties()

on_line_properties(event)

Show the line properties

show_curline_properties()

onapply_properties(event)

Apply the properties

_hide_all_props()

on_line_choose(event)

on_size(event)

Resize event

update_layout()

on_collaps_pane(event)

Collapsible pane event

OnKeyCanvas(event: matplotlib.backend_bases.KeyEvent)

OnClickCanvas(event: matplotlib.backend_bases.MouseEvent)

fill_grid_with_xy(line: matplotlib.lines.Line2D = None, grid: wolfhece.CpGrid.CpGrid = None, colx: int = 0, coly: int = 1)

update_line_from_grid(event)

add_row_to_grid(event)

onadd_line(event)

Add a plot to the current ax

_get_xy_from_grid(grid: wolfhece.CpGrid.CpGrid, colx: int = 0, coly: int = 1)

Get the xy from a grid

add_line(xy: numpy.ndarray, ax: matplotlib.axes.Axes = None, **kwargs)

Add a plot to the current ax

ondel_line(event)

Remove a plot from the current ax

del_line(idx: int)

Delete a line

get_ax_idx(key: str | int | matplotlib.axes.Axes = None) → matplotlib.axes.Axes

plot(x: numpy.ndarray, y: numpy.ndarray, ax: matplotlib.axes.Axes | int | str = None, **kwargs)

to_dict() → dict

properties to dict

from_dict(props: dict)

properties from dict

serialize()

Serialize the properties

deserialize(props: str)

Deserialize the properties

save(filename: str)

load(filename: str)

save_image(filename: str, dpi: int = 100)

set_x_bounds(xmin: float, xmax: float, ax: matplotlib.axes.Axes | int | str = None)

set_y_bounds(ymin: float, ymax: float, ax: matplotlib.axes.Axes | int | str = None)

class wolfhece.matplotlib_fig.Matplotlib_figure_properties(parent: Matplotlib_Figure = None, fig: matplotlib.figure.Figure = None)

set_fig(fig: matplotlib.figure.Figure)

_set_props()

Set the properties UI

populate()

Populate the properties UI

ui()

Create the properties UI

destroyprop()

fill_property()

set_properties(fig: matplotlib.figure.Figure = None)

get_properties(fig: matplotlib.figure.Figure = None)

to_dict() → str

properties to dict

from_dict(props: dict)

properties from dict

add_props_to_sizer(frame: wx.Frame, sizer: wx.BoxSizer)

Add the properties to a sizer

show_props()

Show the properties

hide_props()

Hide the properties

wolfhece.matplotlib_fig.COLORS_MPL = ['b', 'g', 'r', 'c', 'm', 'y', 'k', 'w', 'blue', 'green', 'red', 'cyan', 'magenta', 'yellow',...