Viewer Tests

cp(
test2.csv
, "/results/test.csv");

using CSV

foo = CSV.read(
test2.csv
)

using DataFrames

DataFrame(x = rand(10), asjdkasdj = rand(10))

import pandas as pd

import numpy as np

x = pd.DataFrame({"x": np.random.rand(10), "asjdkasdj": np.random.rand(10)})

x

x = runif(10)

asjdkasdj = runif(10)

data.frame(x, asjdkasdj)

echo "\"x\",\"asjdkasdj\"

0.886204954236746,0.994749354198575

0.939964033663273,0.348342207027599

0.841421562014148,0.251535881310701

0.191597430035472,0.169539803639054

0.552916625980288,0.957168905297294

0.649154531303793,0.336226592073217

0.834337387699634,0.292891587363556

0.940559577196836,0.0146519427653402

0.062867890112102,0.192729525500908

0.500695133814588,0.318394189001992

" > /results/test.csv

HTML("<h3>hi</h3>")

class HTML(object):

  def _repr_html_(self):

    return '<h3>hi</h3>'

HTML()

{:nextjournal/viewer "html" :nextjournal.viewer/value "<h3>hi</h3>"}

echo '<h3>hi</h3>' > /results/test.html

using WebSockets, WebIO, Interact

s = @manipulate for i in 1:10

	"hello number: $i"

end

WebIO.node(:div, s, style = Dict(:height => 80))

library(leaflet)

options(nextjournal.display.htmlwidgetsEnabled=TRUE)

leaflet() %>%

  addTiles() %>%  # Add default OpenStreetMap map tiles

  addMarkers(lng=174.768, lat=-36.852, popup="The birthplace of R")

struct PNG end

function Base.show(io::IO, ::MIME"image/png", ::PNG)

  write(io, read(
test.png
))

end

PNG()

class PNG(object):

  def _repr_png_(self):

    f = open(
test.png
, "rb")

    bin = f.read()

    f.close()

    return bin

PNG()

cp NJ__REF_ /results/test.png

struct JPEG end

function Base.show(io::IO, ::MIME"image/jpeg", ::JPEG)

  write(io, read(
test_image.jpg
))

end

JPEG()

class JPEG(object):

  def _repr_jpeg_(self):

    f = open(
test_image.jpg
, "rb")

    bin = f.read()

    f.close()

    return bin

JPEG()

cp NJ__REF_ /results/test.jpg

struct SVG end

function Base.show(io::IO, ::MIME"image/svg+xml", ::SVG)

  write(io, read(
test.svg
))

end

SVG()

class SVG(object):

  def _repr_svg_(self):

    f = open(
test.svg
, "r")

    bin = f.read()

    f.close()

    return bin

SVG()

cp NJ__REF_ /results/test.svg

using PlotlyBase

PlotlyBase.Plot(1:10, (1:10) .^ 2)

import plotly.graph_objs as go

import numpy as np

x = np.arange(10)

fig = go.Figure(data=[go.Scatter(x=x, y=x**2)])

fig

^{:nextjournal/viewer :plotly}

{:data [{

	:x [1 2 3 4 5 6 7 8 9 10] 

  :y [1 4 9 16 25 36 49 64 81 100]

}]}

^{:nextjournal/viewer "vega-lite"}

{:width 650

 :height 400

 :data

 {:url "https://vega.github.io/vega-datasets/data/us-10m.json"

  :format

  {:type "topojson" :feature "counties"}}

 :transform

 [{:lookup "id"

   :from

   {:data {:url "https://vega.github.io/vega-datasets/data/unemployment.tsv"}

    :key "id"

    :fields ["rate"]}}]

 :projection {:type "albersUsa"}

 :mark "geoshape"

 :encoding

 {:color {:field "rate" :type "quantitative"}}}

echo '{

  "width": 500, "height": 300,

  "data": {"url": "https://vega.github.io/vega-datasets/data/unemployment-across-industries.json"},

  "mark": "area",

  "encoding": {

    "x": {

      "timeUnit": "yearmonth", "field": "date", "type": "temporal",

      "axis": {"domain": false, "format": "%Y", "tickSize": 0}

    },

    "y": {

      "aggregate": "sum", "field": "count","type": "quantitative",

      "axis": null,

      "stack": "center"

    },

    "color": {

    	"field":"series",

      "type":"nominal",

      "scale":{"scheme": "category20b"}

    }

  }

}' > /results/plot.vl.json

pip install altair

import altair as alt

source = "https://vega.github.io/vega-datasets/data/unemployment-across-industries.json"

alt.Chart(source).mark_area().encode(

    alt.X('yearmonth(date):T',

        axis=alt.Axis(format='%Y', domain=False, tickSize=0)

    ),

    alt.Y('sum(count):Q', stack='center', axis=None),

    alt.Color('series:N',

        scale=alt.Scale(scheme='category20b')

    )

).interactive()

struct Latex end

function Base.show(io::IO, ::MIME"text/latex", ::Latex)

  print(io, "\\int_0^\\infty e^{-x^2} dx=\\frac{\\sqrt{\\pi}}{2}")

end

Latex()

class Latex(object):

  def _repr_latex_(self):

    return "\\int_0^\\infty e^{-x^2} dx=\\frac{\\sqrt{\\pi}}{2}"

Latex()

echo "\\int_0^\\infty e^{-x^2} dx=\\frac{\\sqrt{\\pi}}{2}" > "/results/test.latex"

{:nextjournal/viewer "formula" :nextjournal.viewer/value "\\int_0^\\infty e^{-x^2} dx=\\frac{\\sqrt{\\pi}}{2}"}

1:10

()-> "this is a function"

class Plain:

  def test():

    return ""

Plain()

def func(msg):

  print(msg)

func

{:nextjournal/viewer "text" :nextjournal.viewer/value "hi"}

echo "hi" > /results/test.txt

list(1, 2, 3)

f <- function(x){x + 1}

f

struct APP_JSON end

function Base.show(io::IO, ::MIME"application/json", ::APP_JSON)

  JSON.print(io, Dict(:data => [2,3,4]))

end

APP_JSON()

class JSON(object):

  def _repr_json_(self):

    return "{\"data\":[2,3,4]}"

JSON()

echo "{\"data\":[2,3,4]}" > /results/test.json

{:data [2 3 4]}