tests/testthat/test-charting.R

In cryptoQuotes: Open Access to Cryptocurrency Market Data, Sentiment Indicators and Interactive Charts

# script: test-charing
# date: 2024-01-31
# author: Serkan Korkmaz, serkor1@duck.com
# objective: Test wether the charting
# functions returns a plotly object without errors
# script start;
testthat::test_that(
  desc = "Charting with klines and indicators",
  code = {

    # 1) create chart
    # with klines
    test_chart <- chart(
      ticker     = cryptoQuotes:::control_data$quote,
      main       = kline(),
      sub        = list(
        volume(),
        rsi(),
        macd(),
        smi(),
        fgi(index = cryptoQuotes:::control_data$fgindex),
        lsr(ratio = cryptoQuotes:::control_data$lsratio)
      ),
      indicator  = list(
        donchian_channel(),
        dema(),
        ema(),
        evwma(),
        hma(),
        zlema(),
        sma(),
        wma(),
        evwma(),
        vwap(),
        bollinger_bands(),
        alma()

      )
    )

    # 2) check that there is no erros
    testthat::expect_no_error(
      test_chart
    )

    # 3) check that its a plotly
    # object
    testthat::expect_true(
      object = inherits(
        x =  test_chart,
        what = "plotly"
        ),
    )

  }
)


testthat::test_that(
  desc = "Charting with klines and indicators",
  code = {

    # 1) create chart
    # with klines
    test_chart <- chart(
      ticker     = cryptoQuotes:::control_data$quote,
      main       = pline(),
      sub        = list(
        volume(),
        rsi(),
        macd(),
        smi(),
        fgi(index = cryptoQuotes:::control_data$fgindex),
        lsr(ratio = cryptoQuotes:::control_data$lsratio)
      ),
      indicator  = list(
        donchian_channel(),
        dema(),
        ema(),
        evwma(),
        hma(),
        zlema(),
        sma(),
        wma(),
        evwma(),
        vwap(),
        bollinger_bands(),
        alma()

      )
    )

    # 2) check that there is no erros
    testthat::expect_no_condition(
      test_chart
    )

    # 3) check that its a plotly
    # object
    testthat::expect_true(
      object = inherits(
        x =  test_chart,
        what = "plotly"
      ),
    )

  }
)


testthat::test_that(
  desc = "Charting with ohlc bars and indicators",
  code = {

    # 1) create chart
    # with klines
    test_chart <- chart(
      ticker     = cryptoQuotes:::control_data$quote,
      main       = ohlc(),
      sub        = list(
        volume(),
        rsi(),
        macd(),
        smi(),
        fgi(index = cryptoQuotes:::control_data$fgindex),
        lsr(ratio = cryptoQuotes:::control_data$lsratio)
      ),
      indicator  = list(
        donchian_channel(),
        dema(),
        ema(),
        evwma(),
        hma(),
        zlema(),
        sma(),
        wma(),
        evwma(),
        vwap(),
        bollinger_bands(),
        alma()

      )
    )

    # 2) check that there is no erros
    testthat::expect_no_condition(
      test_chart
    )

    # 3) check that its a plotly
    # object
    testthat::expect_true(
      object = inherits(
        x =  test_chart,
        what = "plotly"
      )
    )

  }
)


testthat::test_that(
  desc = "Charting with event data",
  code = {

    set.seed(1903)
    event_data <- ATOM[
      sample(
        seq_len(nrow(ATOM)),
        size = 2)
    ]

    # 1.1) Extract the index
    # from the event data
    index <- zoo::index(
      event_data
    )

    # 1.2) Convert the coredata
    # into a data.frame
    event_data <- as.data.frame(
      zoo::coredata(event_data)
    )

    # 1.3) Add the index into the data.frame
    # case insensitive
    event_data$index <- index

    # 1.4) add events to the data.
    # here we use Buys and Sells.
    event_data$event <- rep(
      x = c('Buy', 'Sell'),
      lenght.out = nrow(event_data)
    )

    # 1.5) add colors based
    # on the event; here buy is colored
    # darkgrey, and if the position is closed
    # with profit the color is green
    event_data$color <- ifelse(
      event_data$event == 'Buy',
      yes = 'darkgrey',
      no  = ifelse(
        subset(event_data, event == 'Buy')$Close <
          subset(event_data, event == 'Sell')$Close,
        yes = 'green',
        no  = 'red'
      )
    )

    # 1.6) modify the event to add
    # closing price at each event
    event_data$event <- paste0(
      event_data$event, ' @', event_data$Close
    )

    # 2) Chart the the klines
    # and add the buy and sell events
    testthat::expect_true(
      object = inherits(chart(
        ticker     = ATOM,
        main       = kline(),
        sub        = list(
          volume()
        ),
        indicator = list(
          bollinger_bands()
        ),
        event_data = event_data,
        options = list(
          dark = TRUE,
          deficiency = FALSE
        )
      ),
      what = "plotly"
      )
    )


  }
)






# script end;