Kernel: SageMath 8.6

Sage 8.6

First tests on CoCalc in "Experimental" software environment.

In [1]:

version()

'SageMath version 8.6, Release Date: 2019-01-15'

In [2]:

graphs.Balaban10Cage().show()

In [3]:

r.summary(r.c(-1,8,-5,3,4,3,2,3))

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 -5.000   1.250   3.000   2.125   3.250   8.000

In [4]:

EllipticCurve('123a').plot()

In [5]:

import rpy2.robjects as robjects
ro_x = robjects.r.rnorm(100r)
robjects.r['print'](ro_x)
ro_x

  [1] -1.189133828 -0.836819676 -0.442810106  1.122136653 -0.784009230
  [6] -0.993369747 -0.673212001  0.206063823 -0.589471948 -0.298967878
 [11]  0.644007462  1.015746212  0.205503429  0.209110249  1.594347218
 [16]  0.003689496  0.001722255 -0.875462496 -0.462871842 -0.127531305
 [21]  1.711617341  0.120556035 -0.436398662  0.506860541  0.324467298
 [26] -0.001974837 -0.952005432 -0.434153442 -0.922783537  0.173266958
 [31] -0.031136536  1.145629492  1.162439694  1.896267385 -0.639952963
 [36]  0.792292860 -1.094769332  0.807824124  0.483236296  0.955261456
 [41] -0.763748078 -0.184643613 -0.432223085  0.522058052  1.135119358
 [46] -2.185715836  0.438690955  0.799953106 -0.622378705 -1.096847114
 [51]  1.529592591  0.583753307  0.500377045 -0.565527181 -0.356021698
 [56]  1.228573124  1.084419727  0.464340508  0.382095447  0.468568054
 [61] -2.034404915  1.542029779 -0.826578792  2.871675812  0.735527698
 [66] -1.294764552  1.245475086  1.312503543 -0.525470127  0.935469394
 [71]  0.297056514 -0.475678952  0.939198872  0.064521583 -0.022206196
 [76]  0.974813990 -1.126664370  1.508208059  0.037994704 -1.657658761
 [81] -1.875740662 -0.460146188 -0.110762892 -0.510032398 -0.892853896
 [86]  1.682180311 -1.667291928  0.801983028  0.365993263  0.241076817
 [91] -0.427597042  0.127901074 -0.387795816 -0.760522673  0.074028576
 [96] -0.552704609  0.096485459 -0.143279443 -0.786070997 -0.745633523

R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x7f84012b9f38 / R:0x55881d072360>
[-1.189134, -0.836820, -0.442810, ..., -0.143279, -0.786071, -0.745634]

In [6]:

robjects.r.summary(ro_x)

R object with classes: ('summaryDefault', 'table') mapped to:
<FloatVector - Python:0x7f83f34065f0 / R:0x55881dcf3458>
[-2.185716, -0.597699, 0.020842, 0.047959, 0.749719, 2.871676]

In [0]: