shorten filenames with directory structure for travis compliance

Author: chriddyp

.gitignore

@@ -2,4 +2,5 @@ R/.Rhistory
 Rapp.history
 /Karthik_local.R
 *~
-.Rhistory
+.Rhistory
+.RData

run_tests_with_outputs.R

@@ -3,23 +3,22 @@ library(plotly)
 
 setwd("tests")
 
-save_outputs <- function(gg, name, ignore_ggplot=FALSE) {
-  filesystem_name <- gsub('/', '--', name)
-  filesystem_name <- gsub(' ', '_', filesystem_name)
+save_outputs <- function(gg, name, ignore_ggplot=FALSE, file_prefix="test-ggplot-") {
+  filesystem_name <- gsub(' ', '_', name)
   print(paste("running", name))
   py <- plotly("TestBot", "r1neazxo9w")
   u <- py$ggplotly(gg, kwargs=list(filename=paste0("ggplot2/", name),
                                    fileopt="overwrite", auto_open=FALSE))
   plotlyUrl <- u$response$url
-  writeLines(plotlyUrl, paste0("test-ggplot-", filesystem_name, ".url"))
+  writeLines(plotlyUrl, paste0(file_prefix, filesystem_name, ".url"))
   pngdata <- getURLContent(paste0(u$response$url, ".png"))
-  writeBin(as.raw(pngdata), paste0("test-ggplot-", filesystem_name, "-plotly.png"))
+  writeBin(as.raw(pngdata), paste0(file_prefix, filesystem_name, "-plotly.png"))
   if (!ignore_ggplot) {
-    ggsave(paste0("test-ggplot-", filesystem_name, "-ggplot2.png"), plot=gg, w=7, h=5)
+    ggsave(paste0(file_prefix, filesystem_name, "-ggplot2.png"), plot=gg, w=7, h=5)
   }
 
   # save the json
-  writeLines(getURL(paste0(plotlyUrl, ".json")), paste0("test-ggplot-", filesystem_name, ".json"))
+  writeLines(getURL(paste0(plotlyUrl, ".json")), paste0(file_prefix, filesystem_name, ".json"))
 }
 
 test_check("plotly")

tests/cookbook-test-suite/axes.R

@@ -1,11 +1,11 @@
 bp <- ggplot(PlantGrowth, aes(x=group, y=weight)) + geom_boxplot()
 
 bp1 <- bp + coord_flip()
-save_outputs(bp1, 'axes/coord flip')
+save_outputs(bp1, 'axes/coord flip', file_prefix="")
 
 # Manually set the order of a discrete-valued axis
 bp2 <- bp + scale_x_discrete(limits=c("trt1","trt2","ctrl"))
-save_outputs(bp2, 'axes/discrete valued axes')
+save_outputs(bp2, 'axes/discrete valued axes', file_prefix="")
 
 # Reverse the order of a discrete-valued axis
 # Get the levels of the factor
@@ -15,66 +15,66 @@ flevels <- levels(PlantGrowth$group)
 flevels <- rev(flevels)
 # "trt2" "trt1" "ctrl"
 bp3 <- bp + scale_x_discrete(limits=flevels)
-save_outputs(bp3, 'axes/reversed ordered axes - 1')
+save_outputs(bp3, 'axes/reversed ordered axes - 1', file_prefix="")
 
 # Or it can be done in one line:
 bp4 <- bp + scale_x_discrete(limits = rev(levels(PlantGrowth$group)) )
-save_outputs(bp4, 'axes/reversed ordered axes - 2')
+save_outputs(bp4, 'axes/reversed ordered axes - 2', file_prefix="")
 
 bp5 <- bp + scale_x_discrete(breaks=c("ctrl", "trt1", "trt2"), labels=c("Control", "Treat 1", "Treat 2"))
-save_outputs(bp5, 'axes/setting tick mark labels')
+save_outputs(bp5, 'axes/setting tick mark labels', file_prefix="")
 
 # Hide x tick marks, labels, and grid lines
 bp6 <- bp + scale_x_discrete(breaks=NULL)
-save_outputs(bp6, 'axes/hidden tick marks labels gridline')
+save_outputs(bp6, 'axes/hidden tick marks labels gridline', file_prefix="")
 
 # Hide all tick marks and labels (on X axis), but keep the gridlines
 bp7 <- bp + theme(axis.ticks = element_blank(), axis.text.x = element_blank())
-save_outputs(bp7, 'axes/hidden tick marks and labels')
+save_outputs(bp7, 'axes/hidden tick marks and labels', file_prefix="")
 
 # Set the range of a continuous-valued axis
 # These are equivalent
 bp8 <- bp + ylim(0,8)
-save_outputs(bp8, 'axes/set range of continuous-valued axis - 1')
+save_outputs(bp8, 'axes/set range of continuous-valued axis - 1', file_prefix="")
 bp9 <- bp + scale_y_continuous(limits=c(0,8))
-save_outputs(bp9, 'axes/set range of continuous-valued axis - 2')
+save_outputs(bp9, 'axes/set range of continuous-valued axis - 2', file_prefix="")
 
 # These two do the same thing; all data points outside the graphing range are dropped,
 # resulting in a misleading box plot
 bp10 <- bp + ylim(5, 7.5)
-save_outputs(bp10, 'axes/misleading range')
+save_outputs(bp10, 'axes/misleading range', file_prefix="")
 bp + scale_y_continuous(limits=c(5, 7.5))
 
 # Using coord_cartesian "zooms" into the area
 bp11 <- bp + coord_cartesian(ylim=c(5, 7.5))
-save_outputs(bp11, 'axes/coord_cartesian')
+save_outputs(bp11, 'axes/coord_cartesian', file_prefix="")
 
 # Specify tick marks directly
 bp12 <- bp + coord_cartesian(ylim=c(5, 7.5)) +
   scale_y_continuous(breaks=seq(0, 10, 0.25))  # Ticks from 0-10, every .25
-save_outputs(bp12, 'axes/specify tick marks directly')
+save_outputs(bp12, 'axes/specify tick marks directly', file_prefix="")
 
 # Reverse order of a continuous-valued axis
 bp13 <- bp + scale_y_reverse()
-save_outputs(bp13, 'axes/reverse y scale')
+save_outputs(bp13, 'axes/reverse y scale', file_prefix="")
 
 # Setting the tick marks on an axis
 # This will show tick marks on every 0.25 from 1 to 10
 # The scale will show only the ones that are within range (3.50-6.25 in this case)
 bp14 <- bp + scale_y_continuous(breaks=seq(1,10,1/4))
-save_outputs(bp14, 'axes/manual tick marks')
+save_outputs(bp14, 'axes/manual tick marks', file_prefix="")
 
 # The breaks can be spaced unevenly
 bp15 <- bp + scale_y_continuous(breaks=c(4, 4.25, 4.5, 5, 6,8))
-save_outputs(bp15, 'axes/uneven tick marks')
+save_outputs(bp15, 'axes/uneven tick marks', file_prefix="")
 
 # Suppress ticks and gridlines
 bp16 <- bp + scale_y_continuous(breaks=NULL)
-save_outputs(bp16, 'axes/suppress y ticks labels and gridlines')
+save_outputs(bp16, 'axes/suppress y ticks labels and gridlines', file_prefix="")
 
 # Hide tick marks and labels (on Y axis), but keep the gridlines
 bp17 <- bp + theme(axis.ticks = element_blank(), axis.text.y = element_blank())
-save_outputs(bp17, 'axes/suppress y ticks and labels')
+save_outputs(bp17, 'axes/suppress y ticks and labels', file_prefix="")
 
 # Create some noisy exponentially-distributed data
 xval = c(0.26932812,-0.05341404,0.36977717,0.91504712,0.46329006,0.37956526, 0.93290644,0.75558976,0.67633497,0.48655293,0.79478162,0.55109982, 0.51681398,0.81073512,0.49406579,0.93919618,0.90472008,0.98732256, 0.94379876,0.95790909,0.54614241,1.13356941,1.13299144,1.18159277, 1.16428407,1.22955005,1.21030897,1.23314811,1.53822718,1.53674330, 1.80020468,1.40774011,1.74573515,1.26651625,2.06607711,1.50237263, 1.38480531,1.83625381,2.35275649,1.99004291,2.80396442,2.20863240, 2.42998876,2.12801180,2.26290348,2.38185989,2.14936036,2.66587947, 2.64586596,2.44240603,2.39266452,3.11831215,2.70258927,2.65529134, 2.65634690,2.95984290,2.71058076,2.87919480,3.07739358,2.66841935, 3.10792706,3.17134285,3.98070271,3.55497279,3.36831009,3.31390892, 3.32753965,2.86981968,3.22741000,3.78806438,3.74434536,3.56928928, 3.83783177,3.24485807,4.05766233,4.13619455,4.26888054,3.47546258, 3.93045819,3.77620080,4.66676431,3.88059240,4.54694485,4.03915767, 4.25556093,4.39251819,4.42692029,4.23262929,4.44890758,4.84981161, 4.51104252,4.33004508,5.06350705,4.89714069,4.21599077,4.55457578, 5.04044393,4.89111297,5.03105215,4.64113164)
@@ -84,34 +84,34 @@ dat <- data.frame(xval = xval, yval = yval)
 
 # A scatterplot with regular (linear) axis scaling
 sp <- ggplot(dat, aes(xval, yval)) + geom_point()
-save_outputs(sp, 'axes/linear axes')
+save_outputs(sp, 'axes/linear axes', file_prefix="")
 
 # log2 scaling of the y axis (with visually-equal spacing)
 library(scales)     # Need the scales package
 sp1 <- sp + scale_y_continuous(trans=log2_trans())
-save_outputs(sp1, 'axes/ln y axes with visual-equal spacing')
+save_outputs(sp1, 'axes/ln y axes with visual-equal spacing', file_prefix="")
 
 # log2 coordinate transformation (with visually-diminishing spacing)
 sp2 <- sp + coord_trans(y="log2")
-save_outputs(sp2, 'axes/ln y axes with visually diminishing spacing')
+save_outputs(sp2, 'axes/ln y axes with visually diminishing spacing', file_prefix="")
 
 sp3 <- sp + scale_y_continuous(trans = log2_trans(),
                                breaks = trans_breaks("log2", function(x) 2^x),
                                labels = trans_format("log2", math_format(2^.x)))
-save_outputs(sp3, 'axes/ln y axes with exponent tick marks')
+save_outputs(sp3, 'axes/ln y axes with exponent tick marks', file_prefix="")
 
 dat10 <- data.frame(xval = xval, yval = yval)
 
 sp10 <- ggplot(dat10, aes(xval, yval)) + geom_point()
 
 # log10
 sp101 <- sp10 + scale_y_log10()
-save_outputs(sp101, 'axes/log_10 y axes')
+save_outputs(sp101, 'axes/log_10 y axes', file_prefix="")
 
 # log10 with exponents on tick labels
 sp102 <- sp10 + scale_y_log10(breaks = trans_breaks("log10", function(x) 10^x),
                               labels = trans_format("log10", math_format(10^.x)))
-save_outputs(sp102, 'axes/log_10 y axes with exponent tick marks')
+save_outputs(sp102, 'axes/log_10 y axes with exponent tick marks', file_prefix="")
 
 # Data where x ranges from 0-10, y ranges from 0-30
 set.seed(202)
@@ -120,35 +120,35 @@ sp <- ggplot(dat, aes(xval, yval)) + geom_point()
 
 # Force equal scaling
 sp4 <- sp + coord_fixed()
-save_outputs(sp4, 'axes/forced equal spacing')
+save_outputs(sp4, 'axes/forced equal spacing', file_prefix="")
 
 # Equal scaling, with each 1 on the x axis the same length as y on x axis
 sp5 <- sp + coord_fixed(ratio=1/3)
-save_outputs(sp5, 'axes/forced equal scaling')
+save_outputs(sp5, 'axes/forced equal scaling', file_prefix="")
 
 bp10 <- bp + theme(axis.title.x = element_blank()) +   # Remove x-axis label
   ylab("Weight (Kg)")                    # Set y-axis label
-save_outputs(bp10, 'axes/axes labels')
+save_outputs(bp10, 'axes/axes labels', file_prefix="")
 
 # Also possible to set the axis label with the scale
 # Note that vertical space is still reserved for x's label
 bp11 <- bp + scale_x_discrete(name="") +
   scale_y_continuous(name="Weight (Kg)")
-save_outputs(bp11, 'axes/axes labels set with scale')
+save_outputs(bp11, 'axes/axes labels set with scale', file_prefix="")
 
 # Change font options:
 # X-axis label: bold, red, and 20 points
 # X-axis tick marks: rotate 90 degrees CCW, move to the left a bit (using vjust,
 #   since the labels are rotated), and 16 points
 bp12 <- bp + theme(axis.title.x = element_text(face="bold", colour="#990000", size=20),
                    axis.text.x  = element_text(angle=90, vjust=0.5, size=16))
-save_outputs(bp12, 'axes/axes labels with formatting')
+save_outputs(bp12, 'axes/axes labels with formatting', file_prefix="")
 
 # Label formatters
 library(scales)   # Need the scales package
 bp13 <- bp + scale_y_continuous(labels=percent) +
   scale_x_discrete(labels=abbreviate)  # In this particular case, it has no effect
-save_outputs(bp13, 'axes/axes labels with percent labels')
+save_outputs(bp13, 'axes/axes labels with percent labels', file_prefix="")
 
 # Self-defined formatting function for times.
 timeHMS_formatter <- function(x) {
@@ -161,20 +161,20 @@ timeHMS_formatter <- function(x) {
 }
 
 bp14 <- bp + scale_y_continuous(label=timeHMS_formatter)
-save_outputs(bp14, 'axes/axes labels with custom time labels')
+save_outputs(bp14, 'axes/axes labels with custom time labels', file_prefix="")
 
 # Hide all the gridlines
 bp15 <- bp + theme(panel.grid.minor=element_blank(), panel.grid.major=element_blank())
-save_outputs(bp15, 'axes/hidden gridlines')
+save_outputs(bp15, 'axes/hidden gridlines', file_prefix="")
 
 # Hide just the minor gridlines
 bp16 <- bp + theme(panel.grid.minor=element_blank())
-save_outputs(bp16, 'axes/hidden minor gridlines')
+save_outputs(bp16, 'axes/hidden minor gridlines', file_prefix="")
 
 # Hide all the horizontal gridlines
 bp17 <- bp + theme(panel.grid.minor.x=element_blank(), panel.grid.major.x=element_blank())
-save_outputs(bp17, 'axes/hidden horizontal gridlines')
+save_outputs(bp17, 'axes/hidden horizontal gridlines', file_prefix="")
 
 # Hide all the vertical gridlines
 bp18 <- bp + theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank())
-save_outputs(bp18, 'axes/hidden vertical gridlines')
+save_outputs(bp18, 'axes/hidden vertical gridlines', file_prefix="")