# -*- coding: utf-8 -*-
from numpy import cos, sin, linspace, pi,sqrt,arctan2, asarray
from plotnine import aes, geom_text, theme_minimal,labs, ylim, xlim, geom_hline, geom_vline, theme, element_line, annotate
#interns functions
from discrimintools.discriminant_analysis.functions.utils import check_is_dataframe, check_is_bool
from .utils import check_is_valid_geom
#list of colors
list_colors = ["black", "red", "green", "blue", "cyan", "magenta","darkgray", "darkgoldenrod", "darkgreen", "violet",
"turquoise", "orange", "lightpink", "lavender", "yellow","lightgreen", "lightgrey", "lightblue", "darkkhaki",
"darkmagenta", "darkolivegreen", "lightcyan", "darkorange","darkorchid", "darkred", "darksalmon",
"darkseagreen","darkslateblue", "darkslategray", "darkslategrey","darkturquoise",
"darkviolet", "lightgray", "lightsalmon","lightyellow", "maroon"]
[docs]
def add_scatter(
p,
data,
axis = [0,1],
geom = ("point","text"),
repel = False,
color = "steelblue",
points_args = dict(shape = "o", size=1.5),
text_args = dict(size=8)
):
"""
Add elements points and/or texts to plotnine graph
Parameters
----------
p : class
An object of class ggplot.
data : DataFrame of shape (n_samples, n_components)
Input data, where ``n_samples`` is the number of samples and ``n_components`` is the number of components.
axis : list, defaul = [0,1]
Dimensions to be plotted
geom : str, list or tuple, default=('point','text')
Geometry to be used for the graph. Possible values are the combinaison of ["point","text"].
- 'point' to show only points,
- 'text' to show only labels,
- ('point','text') to show both types.
repel : bool, default=False
To avoid overplotting text labels.
color : str, default = "steelblue"
Color for the points and texts.
point_args : dict, default=dict(shape = "o", size = 1.5)
Keywords arguments for `geom_point <https://plotnine.org/reference/geom_point.html>`_.
text_args : dict, default=dict(size = 8)
KeywordS arguments for `geom_text <https://plotnine.org/reference/geom_text.html>`_.
Returns
-------
p : class
A object of class ggplot.
Examples
--------
>>> from discrimintools.datasets import load_wine
>>> from discrimintools import CANDISC, add_scatter
>>> from plotnine import ggplot, theme_minimal
>>> D = load_wine("train") # load training dataset
>>> y, X = D["Quality"], D.drop(columns=["Quality"]) # split into X and y
>>> clf = CANDISC()
>>> clf.fit(X,y)
CANDISC()
>>> p = add_scatter(ggplot(),clf.ind_.coord,repel=True)+theme_minimal()
>>> print(p)
.. figure:: ../../../../_static/add_scatter.png
Add individuals points - CANDISC
"""
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
#check if p is an instance of class ggplot
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
if p.__class__.__name__ != "ggplot":
raise TypeError("'p' must be an instance of class ggplot")
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
#check if data is an instance of class pd.DataFrame
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
check_is_dataframe(data)
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
#chack if valid geom
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
check_is_valid_geom(geom,("point","text"))
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
#check is repel is a bool
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
check_is_bool(repel)
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
#set text arguments - add overlap arguments
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
if repel and "text" in geom:
text_args = dict(**text_args,adjust_text=dict(arrowprops=dict(arrowstyle='-',lw=1.0)))
#add points
if "point" in geom:
p = p + annotate("point",x=asarray(data.iloc[:,axis[0]]),y=asarray(data.iloc[:,axis[1]]),color=color,**points_args)
#add texts
if "text" in geom:
p = p + geom_text(data=data,mapping=aes(x = f"Can{axis[0]+1}",y=f"Can{axis[1]+1}",label=data.index),color=color,**text_args)
return p
[docs]
def set_axis(
p,
x_lim = None,
y_lim = None,
x_label = None,
y_label = None,
title = None,
add_hline = True,
add_vline = True,
add_grid = True,
ggtheme = None
):
"""
Set axis to plotnine graph
Parameters
----------
p : class
An object of class ggplot.
x_lim : None, list or tuple, default = None
The range of the plotted ``x`` values
y_lim : None, list or tuple, default = None
The range of the plotted ``y`` values
x_label : None or str, default = None
The label text of ``x``.
y_label : None or str, default = None
The label text of ``y``.
title : None or str, default = None
The title of the graph you draw.
add_hline : bool, default = True
To add a horizontal line.
add_vline : bool, default = True
To add a vertical line.
add_grid : bool, default = True
To add grid customization.
ggtheme : function, default = None
Plotnine `theme <https://plotnine.org/guide/themes-premade.html>`_ name.
Returns
-------
p : class
A object of class ggplot.
Examples
--------
>>> from plotnine import ggplot
>>> from discrimintools import set_axis
>>> p = set_axis(ggplot())
.. figure:: ../../../../_static/set_axis.png
Set axis ggplot
"""
#set title
if title is None:
title = "Map"
p = p + labs(title=title,x=x_label,y=y_label)
#set x limits
if x_lim is not None:
p = p + xlim(x_lim)
#set y limits
if y_lim is not None:
p = p + ylim(y_lim)
#add horizontal line
if add_hline:
p = p + geom_hline(yintercept=0,alpha=0.5,color="black",size=0.5,linetype="dashed")
#add vertical line
if add_vline:
p = p+ geom_vline(xintercept=0,alpha=0.5,color="black",size=0.5,linetype="dashed")
#add grid
if add_grid:
p = p + theme(panel_grid_major=element_line(alpha=None,color="black",size=0.5,linetype="dashed"))
#set ggthme
if ggtheme is None:
ggtheme = theme_minimal()
return p + ggtheme
[docs]
def overlap_coord(
coord,x_name,y_name,repel
):
"""
Overlap text position for segment
Parameters
----------
coord : DataFrame of shape (n_features, n_components)
Input data, where ``n_features`` is the number of features and ``n_components`` is the number of components.
x_name : str
Name of columns for `x` axis.
y_name : str
Name of columns for `y` axis.
repel : bool
To avoid overplotting text labels.
Returns
-------
coord : DataFrame of shape (n_features, n_components + 2)
Output data.
Examples
--------
>>> from discrimintools.datasets import load_wine
>>> from discrimintools import CANDISC, overlap_coord
>>> D = load_wine("train") # load training dataset
>>> y, X = D["Quality"], D.drop(columns=["Quality"]) # split into X and y
>>> clf = CANDISC()
>>> clf.fit(X,y)
CANDISC()
>>> coord = overlap_coord(clf.var_.total,"Can1","Can2",True)
"""
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
#check if coord is an instance of class pd.DataFrame
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
check_is_dataframe(coord)
def rshift(r,theta,a=0.03,b=0.07):
return r + a + b*abs(cos(theta))
if repel:
coord = (coord
.assign(
r = lambda x : sqrt(x[f"{x_name}"]**2+x[f"{y_name}"]**2),
theta = lambda x : arctan2(x[f"{y_name}"],x[f"{x_name}"]),
rnew = lambda x : rshift(r=x["r"],theta=x["theta"]),
xnew = lambda x : x["rnew"]*cos(x["theta"]),
ynew = lambda x : x["rnew"]*sin(x["theta"])
)
.drop(columns=["r","theta","rnew"]))
else:
coord = coord.assign(xnew = lambda x : x[f"{x_name}"], ynew = lambda x : x[f"{y_name}"])
return coord
#drwa circle to plot
[docs]
def fviz_circle(
p, r = 1.0, x0 = 0.0, y0 = 0.0, color = "black"
):
"""
Add a circle with plotnine
Draw (add) a circle with plotnine based on center and radius
Parameters
----------
p : class
An object of class ggplot.
r : float, default = 1.0
Radius.
x0 : float, default = 0.0
``x`` center.
y0 : float, default = 0.0
``y`` center.
color : str, default = 'black'
Color of the circle.
Returns
-------
p : class
A object of class ggplot.
Examples
--------
>>> from plotnine import ggplot, theme_minimal
>>> from discrimintools import fviz_circle
>>> p = fviz_circle(ggplot()) + theme_minimal()
.. figure:: ../../../../_static/fviz_circle.png
Draw circle ggplot
"""
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
#check if p is an instance of class ggplot
#---------------------------------------------------------------------------------------------------------------------------------------------------------------------
if p.__class__.__name__ != "ggplot":
raise TypeError("'p' must be an instance of class ggplot")
x = x0 + r*cos(linspace(0,pi,num=100))
ymin, ymax = y0 + r*sin(linspace(0,-pi,num=100)), y0 + r*sin(linspace(0,pi,num=100))
return p + annotate("ribbon", x=x, ymin=ymin, ymax=ymax,color=color,fill=None)
