# -*- coding: utf-8 -*-
from .....Functions.Plot.plot_2D_Data import plot_2D_Data as plot_2D_Data_fct
from .....Functions.init_fig import init_fig
from SciDataTool import VectorField
[docs]def plot_2D_Data(
self,
Data_str,
*arg_list,
is_norm=False,
unit="SI",
data_list=[],
component_list=None,
legend_list=[],
color_list=[],
save_path=None,
x_min=None,
x_max=None,
y_min=None,
y_max=None,
is_logscale_x=False,
is_logscale_y=False,
is_disp_title=True,
is_grid=True,
is_auto_ticks=True,
fig=None,
ax=None,
barwidth=100,
type_plot=None,
fund_harm_dict=None,
is_show_fig=None,
):
"""Plots a field as a function of time
Parameters
----------
self : Output
an Output object
Data_str : str
name of the Data Object to plot (e.g. "mag.Br")
*arg_list : list of str
arguments to specify which axes to plot
is_norm : bool
boolean indicating if the field must be normalized
unit : str
unit in which to plot the field
data_list : list
list of Data objects to compare
component_list : list
list of component names to plot in separate figures
legend_list : list
list of legends to use for each Data object (including reference one) instead of data.name
color_list : list
list of colors to use for each Data object
save_path : str
full path of the png file where the figure is saved if save_path is not None
x_min : float
minimum value for the x-axis
x_max : float
maximum value for the x-axis
y_min : float
minimum value for the y-axis
y_max : float
maximum value for the y-axis
is_logscale_x : bool
boolean indicating if the x-axis must be set in logarithmic scale
is_logscale_y : bool
boolean indicating if the y-axis must be set in logarithmic scale
is_disp_title : bool
boolean indicating if the title must be displayed
is_grid : bool
boolean indicating if the grid must be displayed
is_auto_ticks : bool
in fft, adjust ticks to freqs (deactivate if too close)
fig : Matplotlib.figure.Figure
existing figure to use if None create a new one
ax : Matplotlib.axes.Axes object
ax on which to plot the data
barwidth : float
barwidth scaling factor, only if type_plot = "bargraph"
type_plot : str
type of 2D graph : "curve", "bargraph", "barchart" or "quiver"
fund_harm_dict : dict
Dict containing axis name as key and frequency/order/wavenumber of fundamental harmonic as value to display fundamental harmonic in red in the fft
is_show_fig : bool
True to show figure after plot
"""
# Get Data object names
data = self.get_data_from_str(data_str=Data_str)
# Get fundamental harmonic properties from Output
if fund_harm_dict is None:
fund_harm_dict = self.get_fund_harm(data)
# Call the plot function
if isinstance(data, VectorField):
if component_list is None: # default: extract all components
component_list = data.components.keys()
for i, comp in enumerate(component_list):
# (fig, axes, patch_leg, label_leg) = init_fig(None, shape="rectangle")
if save_path is not None:
save_path_comp = (
save_path.split(".")[0] + "_" + comp + "." + save_path.split(".")[1]
)
else:
save_path_comp = None
plot_2D_Data_fct(
data.components[comp],
arg_list,
is_norm=is_norm,
unit=unit,
data_list=[dat.components[comp] for dat in data_list],
legend_list=legend_list,
color_list=color_list,
save_path=save_path_comp,
x_min=x_min,
x_max=x_max,
y_min=y_min,
y_max=y_max,
is_logscale_x=is_logscale_x,
is_logscale_y=is_logscale_y,
is_disp_title=is_disp_title,
is_grid=is_grid,
is_auto_ticks=is_auto_ticks,
fig=fig,
ax=ax,
barwidth=barwidth,
type_plot=type_plot,
fund_harm_dict=fund_harm_dict,
is_show_fig=is_show_fig,
)
else:
# (fig, axes, patch_leg, label_leg) = init_fig(None, shape="rectangle")
plot_2D_Data_fct(
data,
arg_list,
is_norm=is_norm,
unit=unit,
data_list=data_list,
legend_list=legend_list,
color_list=color_list,
save_path=save_path,
x_min=x_min,
x_max=x_max,
y_min=y_min,
y_max=y_max,
is_logscale_x=is_logscale_x,
is_logscale_y=is_logscale_y,
is_disp_title=is_disp_title,
is_grid=is_grid,
is_auto_ticks=is_auto_ticks,
fig=fig,
ax=ax,
barwidth=barwidth,
type_plot=type_plot,
fund_harm_dict=fund_harm_dict,
is_show_fig=is_show_fig,
)
