`geom_curve()`¶

Arguments:

curvature

A numeric value that indicates the amount of curvature. Negative values produce left-hand curves, positive values produce right-hand curves and zero produces a straight line. Default = 0.5.

angle

A numeric value between 0 and 180 that indicates the amount by which the control points of the curve should be skewed. Values less than 90 skew the curve towards the start point and values greater than 90 skew the curve towards the end point. Default = 90.

ncp

The number of control points used to draw the curve. More control points produce a smoother curve. Default = 5.

In [1]:

import pandas as pd

from lets_plot import *

In [2]:

LetsPlot.setup_html()

In [3]:

LetsPlot.set_theme(theme_grey())

In [4]:

DEF_ANGLE = 90.0
DEF_CURVATURE = 0.5
DEF_NCP = 5

def curve_plot(curvature=DEF_CURVATURE, angle=DEF_ANGLE, ncp=DEF_NCP):
    return ggplot() \
            + geom_point(aes('x', 'y'), data = { 'x': [-30, 30], 'y': [-10,10] }) \
            + geom_curve(x = -20, y = 1, xend = 10, yend = -1, 
                         curvature = curvature, angle = angle, ncp = ncp,
                         arrow=arrow(ends='both')) \
            + ggtitle("curvature={0}, angle={1}, ncp={2}".format(curvature, angle, ncp))

def curves(curvature=DEF_CURVATURE, angle=DEF_ANGLE, ncp=DEF_NCP):
    return gggrid([
        curve_plot(curvature=curvature, angle=angle, ncp=ncp),
        curve_plot(curvature=curvature, angle=-angle, ncp=ncp),
        curve_plot(curvature=-curvature, angle=angle, ncp=ncp),
        curve_plot(curvature=-curvature, angle=-angle, ncp=ncp)
    ], ncol = 2)


def curves_flipped(curvature=DEF_CURVATURE, angle=DEF_ANGLE, ncp=DEF_NCP):
    return gggrid([
        curve_plot(curvature=curvature, angle=angle, ncp=ncp) + coord_flip(),
        curve_plot(curvature=curvature, angle=-angle, ncp=ncp)+ coord_flip(),
        curve_plot(curvature=-curvature, angle=angle, ncp=ncp)+ coord_flip(),
        curve_plot(curvature=-curvature, angle=-angle, ncp=ncp)+ coord_flip()
    ], ncol = 2)

In [5]:

# straight line

curve_plot(curvature=0)

Out[5]:

In [6]:

# straight line

gggrid([
    curve_plot(angle=0),
    curve_plot(angle=180)
])

Out[6]:

In [7]:

gggrid([
    curve_plot(curvature=0.5, ncp=1),
    curve_plot(curvature=-0.5, ncp=1),
    curve_plot(curvature=0.5),
    curve_plot(curvature=-0.5)    
], ncol=2)

Out[7]:

In [8]:

gggrid([
    curve_plot(curvature=1, ncp=1),
    curve_plot(curvature=-1, ncp=1),
    curve_plot(curvature=1),
    curve_plot(curvature=-1)
], ncol=2)

Out[8]:

In [ ]:

In [9]:

# angle: negative
# -30 == 150
# -240 == 120

gggrid([
    curve_plot(angle=-30), curve_plot(angle=150),
    curve_plot(angle=-240), curve_plot(angle=120),
], ncol=2)

Out[9]:

In [10]:

# 45 == -315 == 405
gggrid([
    curve_plot(angle=45),
    curve_plot(angle=405),
    curve_plot(angle=-315)
])

Out[10]:

In [11]:

curves(curvature=0.9, angle=45)

Out[11]:

In [12]:

curves_flipped(curvature=0.9, angle=45)

Out[12]:

In [13]:

curves(curvature=1.3, angle=135)

Out[13]:

Aesthetics to Adjust Start/End¶

size_start,start_end and stroke_start,stroke_end

When a curve is used in combination with a point layer, objects may overlap. To avoid this, use the aesthetics to offset the start and end coordinates according to the size of points: size_start, size_end and stroke_start,stroke_end.

There is also an optional spacer parameter that defines a value in pixels to shorten the curve by moving the start/end.

In [14]:

x = [-1, 0, 1]
y = [-1, 1, -1]
shape = [1, 16, 21]
size = [1, 2, 3]
stroke = [1, 0, 2]

x_end = x[1:] + [x[0]]
y_end = y[1:] + [y[0]]

data = {
    'x': x,
    'y': y,
    'shape': shape,
    'size': size,
    'stroke': stroke,
    'x_end': x_end,
    'y_end': y_end
}

Default plot:

In [15]:

plot = ggplot(data, aes('x','y')) \
    + geom_point(aes(size='size', shape='shape', stroke='stroke'), color='#4575b4', fill='#abd9e9') \
    + scale_size(range=[20,30], guide='none') \
    + scale_stroke(range=[0,10], guide='none') \
    + scale_shape_identity() \
    + lims(x=[-1.5, 1.5], y=[-1.5, 1.5])


plot + geom_curve(aes(xend='x_end', yend='y_end'),
                  curvature=-0.2,
                  arrow=arrow(ends='both')) 

Out[15]:

Let's define new aesthetics:

In [16]:

size_end = size[1:] + [size[0]]
stroke_end = stroke[1:] + [stroke[0]]

data.update({
    'size_end': size_end,
    'stroke_end': stroke_end,
})

plot + geom_curve(aes(xend='x_end', yend='y_end', 
                      size_start='size', size_end='size_end',
                      stroke_start='stroke', stroke_end='stroke_end'),
                  curvature=-0.2,
                  arrow=arrow(ends='both'))

Out[16]:

Additional padding:

In [17]:

plot + geom_curve(aes(xend='x_end', yend='y_end', 
                      size_start='size', size_end='size_end',
                      stroke_start='stroke', stroke_end='stroke_end'),
                  curvature=-0.2,
                  arrow=arrow(ends='both'),
                  spacer=5) 

Out[17]:

In [18]:

# More examples

def curve(curvature, angle):
    return ggplot() + \
        geom_point(x=0, y=0, size=12, alpha=0.5, color="red") + \
        geom_curve(x=0, y=-0.5, xend=0, yend=0, 
                   size=1, 
                   size_end=12, 
                   curvature=curvature, angle=angle,
                   arrow=arrow(ends='last')) + \
       ylim(-0.5, 0.1)

(gggrid([
    curve(0.5, 90),curve(-0.5, 30),
    curve(1.2,-20),curve(-1.2, 80),
    curve(0.9,-20),curve(-0.9, 5)],
    ncol=2))    

Out[18]:

Simple Graph Visualization¶

In [19]:

nodes = pd.DataFrame({
    'node': ["Living\nThings", "Animals", "Plants", "Dogs", "Cows", "Herbs"],
    'x': [0, -1, 1, -2, 0, 2],
    'y': [1, 0, 0, -1, -1, -1]
})

edges = pd.DataFrame({
    'from': ["Animals", "Plants", "Dogs", "Cows", "Cows", "Herbs"],
    'to': ["Living\nThings", "Living\nThings", "Animals", "Animals", "Herbs", "Plants"],
    'relation': ["is", "is", "is", "is", "eat", "is"]
})
edges = pd.merge(edges, nodes, left_on='from', right_on='node')
edges = pd.merge(edges, nodes, left_on='to', right_on='node', suffixes=('', '_to'))
edges

Out[19]:

	from	to	relation	node	x	y	node_to	x_to	y_to
0	Animals	Living\nThings	is	Animals	-1	0	Living\nThings	0	1
1	Plants	Living\nThings	is	Plants	1	0	Living\nThings	0	1
2	Dogs	Animals	is	Dogs	-2	-1	Animals	-1	0
3	Cows	Animals	is	Cows	0	-1	Animals	-1	0
4	Cows	Herbs	eat	Cows	0	-1	Herbs	2	-1
5	Herbs	Plants	is	Herbs	2	-1	Plants	1	0

In [20]:

ggplot(nodes, aes(x='x', y='y')) \
  + geom_curve(aes(x='x', y='y', xend='x_to', yend='y_to', color='relation'), data=edges, 
               size_end=25,
               curvature=0.2, arrow=arrow()) \
  + geom_point(color='#2166ac', fill='#d1e5f0', shape=21, size=25) \
  + scale_color_manual(['#2166ac', '#d6604d']) \
  + geom_text(aes(label='node')) \
  + coord_cartesian([-3,3],[-1.5,1.5]) \
  + theme_void()

Out[20]:

On LiveMap¶

In [21]:

def set_stay_time(data):
    current_moves = moves_df[(moves_df.departure == data['name'])|(moves_df.arrival == data['name'])]
    years = current_moves.year.sort_values().unique()
    years_combined = []
    for year in years:
        if len(years_combined) == 0 or years_combined[-1][1] + 1 != year:
            years_combined.append((year, year))
        else:
            years_combined[-1] = (years_combined[-1][0], year)
    years_combined = [str(year_from) if year_from == year_to else '{0}-{1}'.format(year_from, year_to) \
                      for year_from, year_to in years_combined]
    data['years'] = ', '.join(years_combined)
    return data

places_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/pushkin/places.csv')
moves_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/pushkin/moves.csv')
df = moves_df.merge(places_df, left_on='departure', right_on='name')\
             .rename(columns=dict(longitude='from_lon', latitude='from_lat'))\
             .drop(columns=['name'])\
             .merge(places_df, left_on='arrival', right_on='name')\
             .rename(columns=dict(longitude='to_lon', latitude='to_lat'))\
             .drop(columns=['name'])
places_df['years'] = ''
places_df = places_df.apply(set_stay_time, axis=1)
places_df.head(3)

Out[21]:

	name	latitude	longitude	years
0	Erzurum	39.908610	41.276940	1829
1	Boldino	55.004477	45.308850	1830, 1833
2	Vitebsk	55.187222	30.205116	1820, 1824

In [22]:

ggplot() + \
    geom_livemap(const_size_zoomin=3) + \
    geom_curve(aes(x='from_lon', y='from_lat', xend='to_lon', yend='to_lat', color='path'), data=df,
                 size_start=3, size_end=3,
                 tooltips=layer_tooltips().title("Trip").line("@path"),
                 curvature=0.2,
                 arrow=arrow(type='open', length=4), size=0.5) + \
    geom_point(aes(x='longitude', y='latitude'), data=places_df, size=3, color='light_grey',
               tooltips=layer_tooltips().title('@name').line('visited in|@years')) + \
    geom_point(aes(x='longitude', y='latitude'), data=places_df, size=1.7, color='black',
               tooltips='none') + \
    scale_color_manual(name='trip name', values=['#addd8e', '#e34a33', '#8856a7', '#2c7fb8',
                                                 '#1c9099', '#006d2c', '#fec44f', '#636363']) + \
    coord_cartesian(xlim=[26, 58], ylim=[38, 62]) + \
    ggtitle("Alexander Pushkin's Trips") + \
    ggsize(800, 600) + \
    theme(axis_title='blank', axis_text='blank', axis_ticks='blank', axis_line='blank')

Out[22]:

In [23]:

msk = places_df.loc[places_df['name'] == 'Moscow'].iloc[0]
pointSize = 2

def fromPoint(onMap: bool):
    p = ggplot(places_df, aes(x='longitude', y='latitude'))
    if (onMap):
        p += geom_livemap()
    p += geom_point(size=pointSize, color='red')
    p += geom_curve(xend=msk['longitude'], yend=msk['latitude'],
                    size=0.2,
                    size_start=pointSize, size_end=pointSize)
    return p

fromPoint(True)

Out[23]:

In [24]:

fromPoint(False)

Out[24]:

geom_curve()¶

Aesthetics to Adjust Start/End¶

Simple Graph Visualization¶

On LiveMap¶

`geom_curve()`¶