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Views: 276
License: APACHE
Kernel: SageMath 8.9

RPy2 in Sage 8.9

  • plotting via ggplot2

  • exchanging data back and forth with R

%load_ext rpy2.ipython

import rpy2.robjects as ro

import math, datetime
import rpy2.robjects.lib.ggplot2 as ggplot2
import rpy2.robjects as ro
from rpy2.robjects.packages import importr, data
base = importr('base')
/ext/sage/sage-8.9_1804/local/lib/python2.7/site-packages/rpy2/robjects/lib/ggplot2.py:67: UserWarning: This was designed againt ggplot2 version 2.1.0 but you have 3.2.1 warnings.warn('This was designed againt ggplot2 version %s but you have %s' % (TARGET_VERSION, ggplot2.__version__)) 
datasets = importr('datasets')
mtcars = data(datasets).fetch('mtcars')['mtcars']

mtcars
R object with classes: ('data.frame',) mapped to: <DataFrame - Python:0x7febbe80cb90 / R:0x55dc724aa428> [Float..., Float..., Float..., ..., Float..., Float..., Float...] mpg: <class 'rpy2.robjects.vectors.FloatVector'> R object with classes: ('numeric',) mapped to: <FloatVector - Python:0x7febbe6bcab8 / R:0x55dc724abf20> [21.000000, 21.000000, 22.800000, ..., 19.700000, 15.000000, 21.400000] cyl: <class 'rpy2.robjects.vectors.FloatVector'> R object with classes: ('numeric',) mapped to: <FloatVector - Python:0x7febbe6bc200 / R:0x55dc73182b60> [6.000000, 6.000000, 4.000000, ..., 6.000000, 8.000000, 4.000000] disp: <class 'rpy2.robjects.vectors.FloatVector'> R object with classes: ('numeric',) mapped to: <FloatVector - Python:0x7febbe659170 / R:0x55dc7318edf0> [160.000000, 160.000000, 108.000000, ..., 145.000000, 301.000000, 121.000000] ... mpg: <class 'rpy2.robjects.vectors.FloatVector'> R object with classes: ('numeric',) mapped to: <FloatVector - Python:0x7febbe659560 / R:0x55dc72a14f40> [1.000000, 1.000000, 1.000000, ..., 1.000000, 1.000000, 1.000000] cyl: <class 'rpy2.robjects.vectors.FloatVector'> R object with classes: ('numeric',) mapped to: <FloatVector - Python:0x7febbe82b830 / R:0x55dc72a159c0> [4.000000, 4.000000, 4.000000, ..., 5.000000, 5.000000, 4.000000] disp: <class 'rpy2.robjects.vectors.FloatVector'> R object with classes: ('numeric',) mapped to: <FloatVector - Python:0x7febbe82b320 / R:0x55dc72a15b00> [4.000000, 4.000000, 1.000000, ..., 6.000000, 8.000000, 2.000000]

Plotting via a temp file

# credits: https://stackoverflow.com/questions/15060838/using-rpy2-with-ipython-notebooks

import uuid
from rpy2.robjects.packages import importr
from IPython.core.display import Image

grdevices = importr('grDevices')


def ggplot_notebook(gg, width=800, height=600, name=None):
    fn = name or '{uuid}.png'.format(uuid=uuid.uuid4())
    grdevices.png(fn, width=width, height=height)
    gg.plot()
    grdevices.dev_off()
    return Image(filename=fn)

pp = ggplot2.ggplot(mtcars) + \
     ggplot2.aes_string(x='wt', y='mpg', col='factor(cyl)') + \
     ggplot2.geom_point() + \
     ggplot2.geom_smooth(ggplot2.aes_string(group = 'cyl'), method = 'lm')

ggplot_notebook(pp, name="rpy2_cars.png", width=1200r, height=500r)
Image in a Jupyter notebook

plotting directly via %%R

%%R -i mtcars -w 7 -h 4 --units in -r 120
require(ggplot2)
pp = ggplot(mtcars) +
     aes_string(x='wt', y='mpg', col='factor(cyl)') +
     geom_point() +
     geom_smooth(aes_string(group = 'cyl'), method = 'lm')
plot(pp)
Image in a Jupyter notebook

Sage → R

xx_sage = random_vector(RDF, 100)
xx_py = xx_sage.numpy()

%%R -i xx_py
summary(xx_py)
Min. 1st Qu. Median Mean 3rd Qu. Max. -0.95542 -0.48588 0.13339 0.06276 0.56787 0.99383 
%%R -i xx_py -w 7 -h 4 --units in -r 120
plot(xx_py)
Image in a Jupyter notebook

Sage → Python → R → Python → Sage

%%R -i xx_py -o yy_py

yy_py = cumsum(xx_py)

yy_py
array([-0.29959186, 0.00819633, 0.5014845 , 1.46897639, 0.51355861, 1.11310686, 2.01407783, 2.57973053, 1.90591932, 2.73190318, 3.6750943 , 4.40820266, 4.77717031, 4.90649039, 4.28637113, 3.66760016, 2.96955911, 3.22482225, 3.33531743, 3.33691204, 3.01120552, 3.55310874, 2.75855311, 2.68736847, 2.69037714, 3.39465425, 3.26428663, 3.52099798, 3.92176095, 3.54252316, 2.87960765, 3.34305752, 4.07628441, 4.25664763, 4.31560434, 3.40292482, 2.97924658, 2.47375642, 1.69119946, 2.58579959, 1.6728068 , 1.88714029, 0.96625172, 0.95218154, 0.6626657 , 0.7187147 , 0.36253844, 1.16840191, 1.65759923, 1.88650748, 2.00241252, 2.58792415, 1.71273724, 2.19807815, 2.61523631, 3.50146605, 4.1164638 , 4.58475693, 3.80959032, 3.89974368, 3.46567204, 2.82161185, 3.22021485, 4.0811679 , 3.43591413, 2.90972107, 3.46071729, 2.68948281, 2.89050262, 3.69664751, 4.69047691, 4.67336452, 5.3910495 , 4.7023384 , 5.62023615, 6.20478371, 6.07401233, 5.27152829, 4.93762454, 5.07509273, 4.37434049, 5.28368852, 4.55822435, 5.13276067, 5.79195922, 4.95525982, 4.50257105, 4.02322958, 4.47746653, 4.97503309, 4.19630878, 4.64587079, 4.68944253, 5.11822637, 5.75665418, 5.04069994, 5.19891447, 5.95971364, 5.66508175, 6.27556709])
yy_sage = vector(RDF, yy_py)
yy_sage
(-0.2995918580329151, 0.008196329254149592, 0.5014844961518963, 1.4689763946714813, 0.5135586103559509, 1.1131068611590293, 2.0140778258627607, 2.5797305251785563, 1.9059193154763727, 2.7319031821256656, 3.6750943015435658, 4.408202657910294, 4.777170306397774, 4.90649039468434, 4.286371126760681, 3.667600164809161, 2.969559108707865, 3.2248222494943075, 3.3353174327743487, 3.3369120400329337, 3.0112055219659424, 3.553108736382056, 2.7585531074578977, 2.6873684671698888, 2.6903771384058555, 3.3946542496864027, 3.264286630036528, 3.520997981555216, 3.921760947873978, 3.5425231566468756, 2.879607645841621, 3.343057524106938, 4.076284410303387, 4.2566476325621805, 4.315604336177528, 3.4029248229195543, 2.9792465827218315, 2.4737564245987187, 1.6911994603052485, 2.585799594624631, 1.672806799350057, 1.8871402888043514, 0.9662517249921629, 0.9521815372301856, 0.6626656993703699, 0.7187147003151491, 0.36253843776469274, 1.1684019085721185, 1.657599229499032, 1.8865074778139324, 2.002412515144969, 2.5879241463887004, 1.7127372443474986, 2.1980781520478585, 2.615236308402098, 3.501466048514162, 4.116463803914343, 4.584756925325859, 3.8095903223593997, 3.899743682010386, 3.4656720359102673, 2.821611851313847, 3.2202148520566016, 4.08116790021166, 3.4359141263909474, 2.9097210677394147, 3.4607172861831117, 2.689482811047208, 2.89050261683574, 3.696647507904658, 4.690476907195403, 4.673364519033066, 5.391049504142999, 4.70233840137289, 5.6202361507185294, 6.204783708010592, 6.0740123253830385, 5.271528287432086, 4.937624539200311, 5.075092727593065, 4.374340492783434, 5.283688515252385, 4.55822435029697, 5.132760669388963, 5.791959218652648, 4.955259818168885, 4.5025710508819365, 4.023229582902598, 4.477466532197614, 4.975033093697473, 4.1963087813872, 4.645870788057704, 4.689442527233158, 5.118226374501228, 5.7566541822511725, 5.040699944588016, 5.19891446728235, 5.959713639263135, 5.665081749771823, 6.275567089682704)
type(yy_sage)
<type 'sage.modules.vector_real_double_dense.Vector_real_double_dense'>
plot(yy_sage)
Image in a Jupyter notebook