Module mpl_plotter.comparison
Expand source code
import numpy as np
import matplotlib as mpl
from mpl_plotter.setup import figure
from mpl_plotter.color.schemes import one
from mpl_plotter.presets.custom import two_d
from mpl_plotter.two_d import line
from alexandria.logic import if_none
from alexandria.shell import print_color
from alexandria.data_structs.array import lists_to_ndarrays, internal_array_shape
def comparison(x,
y,
f=None,
plot_labels=None,
zorders=None, colors=None, alphas=None,
**kwargs):
"""
Plot _n_ arrays of values over _n_ domains.
The limits of the plot will be adjusted to the upper and lower limits
of all _x_ and _y_.
:param x: Domains.
:param y: Values.
:param f: Functions used to plot y(x)
:param plot_labels: Plot labels
:param zorders: Determine plot layout
:param colors: Determine color of each plot
:param alphas: Determine alpha of each plot
:param kwargs: MPL Plotter plotting class keyword arguments for
further customization
:type x: list of lists/ndarrays
:type y: list of lists/ndarrays
:type f: list of MPL Plotter plotting classes
:type zorders: list of floats
:type colors: list of strings
:type plot_labels: list of strings
:type alphas: list of floats
"""
# Input
x, y = lists_to_ndarrays(x, y)
f = f if f else [line for i in range(len(y))]
# Defaults
backend = kwargs.pop('backend', "Qt5Agg") # Setup
fig = kwargs.pop('fig', None)
ax = kwargs.pop('ax', None)
demo_pad_plot = kwargs.pop('demo_pad_plot', False) # Axes
y_label = kwargs.pop('y_label', None) # Labels
legend = kwargs.pop('legend', True if not isinstance(plot_labels, type(None)) else False) # Legend
legend_loc = kwargs.pop('legend_loc', (0.7, 0.2))
# Color scheme
colors = colors if not isinstance(colors, type(None)) else one()
# Limits
y_max = max(y[n].max() for n in range(len(y)))
y_min = min(y[n].min() for n in range(len(y)))
span_y = abs(y_max-y_min)
x_max = max(x[n].max() for n in range(len(x)))
x_min = min(x[n].min() for n in range(len(x)))
span_x = abs(x_max-x_min)
for i in range(len(y)):
if i < (len(y) - 1):
f[i](x=x[i], y=y[i], # Main
color=colors[i], # Customization
zorder=zorders[i] if not isinstance(zorders, type(None)) else None,
alpha=alphas[i] if not isinstance(alphas, type(None)) else None,
plot_label=plot_labels[i] if not isinstance(plot_labels, type(None)) else None,
ax=ax, fig=fig, backend=backend, # **kwargs
resize_axes=False, grid=False, # Default
)
else:
f[i](x=x[i], y=y[i], # Main
color=colors[i], # Customization
zorder=zorders[i] if not isinstance(zorders, type(None)) else None,
alpha=alphas[i] if not isinstance(alphas, type(None)) else None,
plot_label=plot_labels[i] if not isinstance(plot_labels, type(None)) else None,
y_label=y_label,
legend=legend, legend_loc=legend_loc, # Automatic
demo_pad_plot=demo_pad_plot,
x_bounds=[x_min - 0.05 * span_x,
x_max + 0.05 * span_x],
y_bounds=[y_min - 0.05 * span_y,
y_max + 0.05 * span_y],
y_custom_tick_locations=[y_min,
y_max],
x_custom_tick_locations=[x_min,
x_max],
ax=ax, fig=fig, backend=backend, # **kwargs
**kwargs
)
def comparison_input_match(x, y):
if not (internal_array_shape(y) == internal_array_shape(y)[0]).all():
raise ValueError(f"Arrays in _y_ have different shapes:\n{*internal_array_shape(y),}")
if x.shape != y.shape:
if x.ndim == 1:
t = np.array(list([x for n in range(y.shape[1])] for i in range(y.shape[0]))).squeeze()
return t
else:
raise ValueError("_t_ and _y_ mismatch")Functions
def comparison(x, y, f=None, plot_labels=None, zorders=None, colors=None, alphas=None, **kwargs)-
Plot n arrays of values over n domains. The limits of the plot will be adjusted to the upper and lower limits of all x and y.
:param x: Domains. :param y: Values. :param f: Functions used to plot y(x) :param plot_labels: Plot labels :param zorders: Determine plot layout :param colors: Determine color of each plot :param alphas: Determine alpha of each plot :param kwargs: MPL Plotter plotting class keyword arguments for further customization
:type x: list of lists/ndarrays :type y: list of lists/ndarrays :type f: list of MPL Plotter plotting classes :type zorders: list of floats :type colors: list of strings :type plot_labels: list of strings :type alphas: list of floats
Expand source code
def comparison(x, y, f=None, plot_labels=None, zorders=None, colors=None, alphas=None, **kwargs): """ Plot _n_ arrays of values over _n_ domains. The limits of the plot will be adjusted to the upper and lower limits of all _x_ and _y_. :param x: Domains. :param y: Values. :param f: Functions used to plot y(x) :param plot_labels: Plot labels :param zorders: Determine plot layout :param colors: Determine color of each plot :param alphas: Determine alpha of each plot :param kwargs: MPL Plotter plotting class keyword arguments for further customization :type x: list of lists/ndarrays :type y: list of lists/ndarrays :type f: list of MPL Plotter plotting classes :type zorders: list of floats :type colors: list of strings :type plot_labels: list of strings :type alphas: list of floats """ # Input x, y = lists_to_ndarrays(x, y) f = f if f else [line for i in range(len(y))] # Defaults backend = kwargs.pop('backend', "Qt5Agg") # Setup fig = kwargs.pop('fig', None) ax = kwargs.pop('ax', None) demo_pad_plot = kwargs.pop('demo_pad_plot', False) # Axes y_label = kwargs.pop('y_label', None) # Labels legend = kwargs.pop('legend', True if not isinstance(plot_labels, type(None)) else False) # Legend legend_loc = kwargs.pop('legend_loc', (0.7, 0.2)) # Color scheme colors = colors if not isinstance(colors, type(None)) else one() # Limits y_max = max(y[n].max() for n in range(len(y))) y_min = min(y[n].min() for n in range(len(y))) span_y = abs(y_max-y_min) x_max = max(x[n].max() for n in range(len(x))) x_min = min(x[n].min() for n in range(len(x))) span_x = abs(x_max-x_min) for i in range(len(y)): if i < (len(y) - 1): f[i](x=x[i], y=y[i], # Main color=colors[i], # Customization zorder=zorders[i] if not isinstance(zorders, type(None)) else None, alpha=alphas[i] if not isinstance(alphas, type(None)) else None, plot_label=plot_labels[i] if not isinstance(plot_labels, type(None)) else None, ax=ax, fig=fig, backend=backend, # **kwargs resize_axes=False, grid=False, # Default ) else: f[i](x=x[i], y=y[i], # Main color=colors[i], # Customization zorder=zorders[i] if not isinstance(zorders, type(None)) else None, alpha=alphas[i] if not isinstance(alphas, type(None)) else None, plot_label=plot_labels[i] if not isinstance(plot_labels, type(None)) else None, y_label=y_label, legend=legend, legend_loc=legend_loc, # Automatic demo_pad_plot=demo_pad_plot, x_bounds=[x_min - 0.05 * span_x, x_max + 0.05 * span_x], y_bounds=[y_min - 0.05 * span_y, y_max + 0.05 * span_y], y_custom_tick_locations=[y_min, y_max], x_custom_tick_locations=[x_min, x_max], ax=ax, fig=fig, backend=backend, # **kwargs **kwargs ) def comparison_input_match(x, y)-
Expand source code
def comparison_input_match(x, y): if not (internal_array_shape(y) == internal_array_shape(y)[0]).all(): raise ValueError(f"Arrays in _y_ have different shapes:\n{*internal_array_shape(y),}") if x.shape != y.shape: if x.ndim == 1: t = np.array(list([x for n in range(y.shape[1])] for i in range(y.shape[0]))).squeeze() return t else: raise ValueError("_t_ and _y_ mismatch")