I want to use data.table to join two dataframes that each have a sf geometry column, and I want to do a cross join in data.table. Reproducible data below and my code is as follows:
library(data.table)
#convert data from data frames to data table
#add the dummy key 'k' and remove it at the end
setkey(as.data.table(data1)[,c(k=1,.SD)],k)[as.data.table(data2).
[,c(k=1,.SD)],allow.cartesian=TRUE][,k:=NULL]
This gives the following result
Using data.table changes the sf geometry column. How can I use data.table while preserving the original format of the geometry column?
For instance, the orginial dataframe geometry column for data1 looks like this:
Reproducible data:
data1:
structure(list(shape = c("polygon 1", "polygon 2"), geometry = structure(list(
structure(list(structure(c(-4e-04, -4e-04, -3e-05, -3e-05,
-4e-04, 51.199, 51.1975, 51.1975, 51.199, 51.199), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg"), precision = 0, bbox = structure(c(xmin = -4e-04,
ymin = 51.1975, xmax = -3e-05, ymax = 51.199), class = "bbox"), crs = structure(list(
input = NA_character_, wkt = NA_character_), class = "crs"), n_empty = 0L),
structure(list(structure(c(5e-05, 5e-05, 0.003, 0.003, 5e-05,
51.1972, 51.1967, 51.1967, 51.1972, 51.1972), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg"), precision = 0, bbox = structure(c(xmin = 5e-05,
ymin = 51.1967, xmax = 0.003, ymax = 51.1972), class = "bbox"), crs = structure(list(
input = NA_character_, wkt = NA_character_), class = "crs"), n_empty = 0L)), class =
c("sfc_POLYGON",
"sfc"), precision = 0, bbox = structure(c(xmin = -4e-04, ymin = 51.1967,
xmax = 0.003, ymax = 51.199), class = "bbox"), crs = structure(list(
input = NA_character_, wkt = NA_character_), class = "crs"), n_empty = 0L)), row.names = c(NA,
-2L), sf_column = "geometry", agr = structure(c(shape = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"), class = c("sf",
"tbl_df", "tbl", "data.frame"))
data2:
structure(list(shape = c("polygon 1", "polygon 2"), geometry = structure(list(
structure(list(structure(c(0.0095, 0.0085, 0.0075, 0.0075,
0.01055, 0.01055, 0.012, 0.0115, 0.0095, 51.21, 51.199, 51.199,
51.197, 51.196, 51.198, 51.198, 51.21, 51.21), .Dim = c(9L,
2L))), class = c("XY", "POLYGON", "sfg"), precision = 0, bbox = structure(c(xmin = 0.0075,
ymin = 51.196, xmax = 0.012, ymax = 51.21), class = "bbox"), crs = structure(list(
input = NA_character_, wkt = NA_character_), class = "crs"), n_empty = 0L),
structure(list(structure(c(0.0205, 0.019, 0.019, 0.02, 0.021,
0.0205, 51.196, 51.1955, 51.194, 51.193, 51.194, 51.196), .Dim = c(6L,
2L))), class = c("XY", "POLYGON", "sfg"), precision = 0, bbox = structure(c(xmin = 0.019,
ymin = 51.193, xmax = 0.021, ymax = 51.196), class = "bbox"), crs = structure(list(
input = NA_character_, wkt = NA_character_), class = "crs"), n_empty = 0L)), class =
c("sfc_POLYGON",
"sfc"), precision = 0, bbox = structure(c(xmin = 0.0075, ymin = 51.193,
xmax = 0.021, ymax = 51.21), class = "bbox"), crs = structure(list(
input = NA_character_, wkt = NA_character_), class = "crs"), n_empty = 0L)), row.names = c(NA,
-2L), sf_column = "geometry", agr = structure(c(shape = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"), class = c("sf",
"tbl_df", "tbl", "data.frame"))
Related
I want to convert my dataframe from wide to long but based on the character vector in one column (based on residents number from the following dput.)
From the following dput, the outcome should have a total of three rows showing all the 3 residents. Is there a way to do it? I tried using seperate rows but the output is not what I desire.
Tried using
Building_Details_Trial_50 %>% tidyr::separate_rows(residents)
dput
structure(list(time = "Mar 22", buildingId = "50", region = "Central",
geometry = structure(list(structure(list(structure(c(-447.361154068258,
-447.557850744738, -533.811390293442, -536.961556093902,
-443.736917153567, -447.361154068258, 5919.51770006977, 5906.87385860642,
5908.2156806004, 5958.8966109417, 5959.54382538916, 5919.51770006977
), dim = c(6L, 2L))), class = c("XY", "POLYGON", "sfg"))), class = c("sfc_POLYGON",
"sfc"), precision = 0, bbox = structure(c(xmin = -536.961556093902,
ymin = 5906.87385860642, xmax = -443.736917153567, ymax = 5959.54382538916
), class = "bbox"), crs = structure(list(input = NA_character_,
wkt = NA_character_), class = "crs"), n_empty = 0L),
count = 3L, geom_points = structure(list(structure(c(-490.403818453599,
5933.7360887923), class = c("XY", "POINT", "sfg"))), class = c("sfc_POINT",
"sfc"), precision = 0, bbox = structure(c(xmin = -490.403818453599,
ymin = 5933.7360887923, xmax = -490.403818453599, ymax = 5933.7360887923
), class = "bbox"), crs = structure(list(input = NA_character_,
wkt = NA_character_), class = "crs"), n_empty = 0L),
long = -490.403818453599, lat = 5933.7360887923, residents = list(
c("556", "155", "143"))), row.names = 1L, sf_column = "geometry", agr = structure(c(time = NA_integer_,
buildingId = NA_integer_, region = NA_integer_, count = NA_integer_,
long = NA_integer_, lat = NA_integer_, residents = NA_integer_
), levels = c("constant", "aggregate", "identity"), class = "factor"), class = c("sf",
"tbl_df", "tbl", "data.frame"))
Ideal output
Residents
buildingId
Region
556
50
Central
155
50
Central
143
50
Central
I have a list of 72 datasets loaded in the Global Environment. Each dataset contains a column called uniqueID filled with unique identifiers.
I want to merge each dataset with another dataset based on these unique identifiers (i.e. uniqueID).
I can do the following on a dataset by dataset basis:
dataset1<-merge(dataset1,tomerge,by="uniqueID",all.x=TRUE)
However as I have many datasets I would like to do this using a loop.
Here is what I have tried:
dflist<-Filter(is.data.frame, as.list(.GlobalEnv))
dflist<-function(df,x){df<-merge(df,tomerge,all.x=TRUE)}
Here is an example of dataset1 and tomerge that I am trying to merge:
dput(dataset1[1:2, ])
structure(list(id = c(1, 2), geometry = structure(list(structure(c(12.7709873378252,
-2.34780379794057), class = c("XY", "POINT", "sfg")), structure(c(13.7404727250738,
-3.08397066598979), class = c("XY", "POINT", "sfg"))), class = c("sfc_POINT",
"sfc"), precision = 0, bbox = structure(c(xmin = 12.7709873378252,
ymin = -2.08397066598979, xmax = 13.7404727250738, ymax = -1.34780379794057
), class = "bbox"), crs = structure(list(epsg = NA_integer_,
proj4string = NA_character_), class = "crs"), n_empty = 0L),
uniqueID = c("id_1_v12_3", "id_2_v13_3")), sf_column = "geometry", agr = structure(c(id = NA_integer_,
shapefile = NA_integer_), .Label = c("constant", "aggregate",
"identity"), class = "factor"), row.names = 1:2, class = c("sf",
"data.frame"))
dput(tomerge[1:2, 2:3 ])
structure(list(uniqueID = c("id_1_v12_3", "id_2_v13_2"), todigit = c("y",
"y")), row.names = c(NA, -2L), class = c("tbl_df", "tbl", "data.frame"
)) ```
We can use lapply to loop over the list of data.frame and merge with the 'tomerge' data
dfmergelist <- lapply(dflist, function(x)
merge(x, tomerge, by = "uniqueID", all.x = TRUE))
where
dflist <- Filter(is.data.frame, mget(ls()))
I have a fairly simple problem where I want to create a gif which loops through departure_hour and colors the lines based on link volumes. One caveat is the number of rows between states (i.e. departure_hour) may be different.
Here is the code I am trying:
vol <- ggplot() +
geom_sf(data = test, aes(color=link_volume)) +
scale_color_distiller(palette = "OrRd", direction = 1) +
ggtitle("{frame_time}") +
transition_time(departure_hour) +
ease_aes("linear") +
enter_fade() +
exit_fade()
animate(vol, fps = 10, width = 750, height = 450)
However, when I do this I am getting the error:
Error in tween_state(as.data.frame(full_set$from), as.data.frame(full_set$to),:
identical(classes, col_classes(to)) is not TRUE
First, I do not understand if the error is referring to column classes or color classes? If it is color classes am I correct in assuming that the color scales between each plot may be different and that is the reason for this error?
Second, how do I fix this error? There seems to be just one more question on this issue and it has no solution.
Sample data:
> dput(head(test,5))
structure(list(linkid = c(12698L, 26221L, 36429L, 36430L, 47315L
), departure_hour = c(14, 19, 11, 0, 18), link_volume = c(500L,
1550L, 350L, 100L, 550L), geometry = structure(list(structure(c(1065088.71736072,
1065084.18813218, 1253892.13487564, 1253935.59094818), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(1060907.62521458,
1060984.50834787, 1237578.71728528, 1237818.59111698), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(1063031.34624456,
1062955.36965935, 1241210.04281066, 1241498.76584417), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(1063031.34624456,
1063034.73081084, 1241210.04281066, 1241198.98905491), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(1058112.52771678,
1058131.02887377, 1236388.96345761, 1236342.13157851), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg"))), class = c("sfc_LINESTRING",
"sfc"), precision = 0, bbox = structure(c(xmin = 1058112.52771678,
ymin = 1236342.13157851, xmax = 1065088.71736072, ymax = 1253935.59094818
), class = "bbox"), crs = structure(list(epsg = 5070L, proj4string = "+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=23 +lon_0=-96 +x_0=0 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"), class = "crs"), n_empty = 0L)), sf_column = "geometry", agr = structure(c(linkid = NA_integer_,
departure_hour = NA_integer_, link_volume = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"), row.names = c(NA,
5L), class = c("sf", "data.table", "data.frame"))
I am trying to provide extra information in a table below a plotly map using event_data.
I found this: https://community.plot.ly/t/how-to-return-the-same-event-data-information-for-selected-points-even-after-modifying-the-data/5847. A good example using ggplot by adding the key column to the aes:
ggplot(mtcars, aes(mpg, wt, col = I(col), key = key))
But how can I add a key column to a scattergl plotly map in order for the key popping up in the event_data? Any help would be greatly appreciated.
R Shiny code:
library(plotly)
library(shiny)
ui <- fluidPage(
plotlyOutput("plot"),
verbatimTextOutput("event")
)
server <- function(input, output, session) {
#df sample using dput
df <- structure(list(col_group = structure(1:8, .Label = c("1", "2",
"3", "4", "5", "6", "7", "8"), class = "factor"), color = structure(c(4L,
6L, 7L, 8L, 5L, 3L, 2L, 1L), .Label = c("#1A9850", "#66BD63",
"#A6D96A", "#D73027", "#D9EF8B", "#F46D43", "#FDAE61", "#FEE08B"
), class = "factor"), geometry = structure(list(structure(c(4.52343199617246,
4.52324233358547, 4.52267342343957, 4.52224662532908, 4.52210428346744,
4.52200925015845, 4.52192088448668, 4.52180475361204, 4.52172945325391,
4.52168196905882, 4.5215535740952, 4.52095980475523, 4.52076420632298,
4.52062274547478, 51.9453195440486, 51.9453722803981, 51.945526317454,
51.9456480852256, 51.9456928353329, 51.9457296098645, 51.9457705951341,
51.9458530114811, 51.945914910501, 51.9459312169901, 51.9459510896027,
51.9459966849614, 51.9460077291392, 51.9460066867221), .Dim = c(14L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.4964540696277,
4.49696710232736, 51.9086692611627, 51.9084484303039), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.13635479859532,
4.13644010080625, 51.975098751212, 51.9751715711302), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.47801457239531,
4.47834576882542, 51.9300740588744, 51.9304218318716), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.45974369011875,
4.46029492493512, 4.46033964902157, 51.9290774018138, 51.9284345596986,
51.9283809798498), .Dim = 3:2, class = c("XY", "LINESTRING",
"sfg")), structure(c(4.43886518844695, 4.43891013390463, 4.43910559159559,
4.43913561800293, 51.93455577157, 51.9344932127658, 51.9341891712133,
51.9341444695365), .Dim = c(4L, 2L), class = c("XY", "LINESTRING",
"sfg")), structure(c(4.54844667292407, 4.55002805772657, 51.9658870347267,
51.9661409927825), .Dim = c(2L, 2L), class = c("XY", "LINESTRING",
"sfg")), structure(c(4.47522875290306, 4.47598748813623, 51.9347985281278,
51.9353886781931), .Dim = c(2L, 2L), class = c("XY", "LINESTRING",
"sfg"))), class = c("sfc_LINESTRING", "sfc"), precision = 0, bbox = structure(c(xmin = 4.13635479859532,
ymin = 51.9084484303039, xmax = 4.55002805772657, ymax = 51.9751715711302
), class = "bbox"), crs = structure(list(epsg = 4326L, proj4string = "+proj=longlat +datum=WGS84 +no_defs"), class = "crs"), n_empty = 0L),
key = c("1", "8000", "10000", "12000", "14000", "16000",
"18000", "22000")), row.names = c(1L, 8000L, 10000L, 12000L,
14000L, 16000L, 18000L, 22000L), class = c("sf", "data.frame"
), sf_column = "geometry", agr = structure(c(col_group = NA_integer_,
color = NA_integer_, key = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"))
#plotly
output$plot <- renderPlotly({
plot_geo(df, type = "scattergl", mode = "lines",
color = ~col_group, colors = rev(RColorBrewer::brewer.pal(8, name = "RdYlGn"))
)
})
#event_data
output$event <- renderPrint({
d <- event_data("plotly_click")
if (is.null(d)) "Click events appear here (double-click to clear)" else {
df_select <- df %>% tibble::rownames_to_column() %>% filter(col_group==d$curveNumber-7) %>% filter(row_number()==d$pointNumber+1)
browser()
print(df_select)
}
})
}
shinyApp(ui, server)
Solved using customdata and updated plotly package. Perhaps of use for someone else:
library(plotly)
library(shiny)
ui <- fluidPage(
plotlyOutput("plot"),
verbatimTextOutput("event")
)
server <- function(input, output, session) {
#df sample using dput
df <- structure(list(col_group = structure(1:8, .Label = c("1", "2",
"3", "4", "5", "6", "7", "8"), class = "factor"), color = structure(c(4L,
6L, 7L, 8L, 5L, 3L, 2L, 1L), .Label = c("#1A9850", "#66BD63",
"#A6D96A", "#D73027", "#D9EF8B", "#F46D43", "#FDAE61", "#FEE08B"
), class = "factor"), geometry = structure(list(structure(c(4.52343199617246,
4.52324233358547, 4.52267342343957, 4.52224662532908, 4.52210428346744,
4.52200925015845, 4.52192088448668, 4.52180475361204, 4.52172945325391,
4.52168196905882, 4.5215535740952, 4.52095980475523, 4.52076420632298,
4.52062274547478, 51.9453195440486, 51.9453722803981, 51.945526317454,
51.9456480852256, 51.9456928353329, 51.9457296098645, 51.9457705951341,
51.9458530114811, 51.945914910501, 51.9459312169901, 51.9459510896027,
51.9459966849614, 51.9460077291392, 51.9460066867221), .Dim = c(14L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.4964540696277,
4.49696710232736, 51.9086692611627, 51.9084484303039), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.13635479859532,
4.13644010080625, 51.975098751212, 51.9751715711302), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.47801457239531,
4.47834576882542, 51.9300740588744, 51.9304218318716), .Dim = c(2L,
2L), class = c("XY", "LINESTRING", "sfg")), structure(c(4.45974369011875,
4.46029492493512, 4.46033964902157, 51.9290774018138, 51.9284345596986,
51.9283809798498), .Dim = 3:2, class = c("XY", "LINESTRING",
"sfg")), structure(c(4.43886518844695, 4.43891013390463, 4.43910559159559,
4.43913561800293, 51.93455577157, 51.9344932127658, 51.9341891712133,
51.9341444695365), .Dim = c(4L, 2L), class = c("XY", "LINESTRING",
"sfg")), structure(c(4.54844667292407, 4.55002805772657, 51.9658870347267,
51.9661409927825), .Dim = c(2L, 2L), class = c("XY", "LINESTRING",
"sfg")), structure(c(4.47522875290306, 4.47598748813623, 51.9347985281278,
51.9353886781931), .Dim = c(2L, 2L), class = c("XY", "LINESTRING",
"sfg"))), class = c("sfc_LINESTRING", "sfc"), precision = 0, bbox = structure(c(xmin = 4.13635479859532,
ymin = 51.9084484303039, xmax = 4.55002805772657, ymax = 51.9751715711302
), class = "bbox"), crs = structure(list(epsg = 4326L, proj4string = "+proj=longlat +datum=WGS84 +no_defs"), class = "crs"), n_empty = 0L),
key = c("1", "8000", "10000", "12000", "14000", "16000",
"18000", "22000")), row.names = c(1L, 8000L, 10000L, 12000L,
14000L, 16000L, 18000L, 22000L), class = c("sf", "data.frame"
), sf_column = "geometry", agr = structure(c(col_group = NA_integer_,
color = NA_integer_, key = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"))
#plotly
output$plot <- renderPlotly({
plot_geo(df, type = "scattergl", mode = "lines",
customdata = ~key,
color = ~col_group, colors = rev(RColorBrewer::brewer.pal(8, name = "RdYlGn"))
)
})
#event_data
output$event <- renderPrint({
d <- event_data("plotly_click")
if (is.null(d)) "Click events appear here (double-click to clear)" else {
df_select <- df[df$key %in% d$customdata,]
print(df_select)
}
})
}
shinyApp(ui, server)
I'm working on a plotting function based on rasterVis::levelplot to which the user can pass either just a raster object, or a raster object and an sf polygon object.
The function is rather complex, but a minimum subset showing the problem reads as:
library(sf)
library(raster)
library(rasterVis)
myplot <- function(in_rast, in_poly = NULL) {
rastplot <- rasterVis::levelplot(in_rast, margin = FALSE)
polyplot <- layer(sp::sp.polygons(in_poly))
print(rastplot + polyplot)
}
The problem is that I see some strange (for me) results while testing it. Let's define some dummy data - a 1000x1000 raster and a sf POYGON oject with four polygons which split the raster -:
in_rast <- raster(matrix(nrow = 1000, ncol = 1000))
in_rast <- setValues(in_rast, seq(1:1000000))
my_poly <- structure(list(cell_id = 1:4, geometry = structure(list(structure(list(
structure(c(0, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0.5, 0), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg")), structure(list(
structure(c(0.5, 1, 1, 0.5, 0.5, 0, 0, 0.5, 0.5, 0), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg")), structure(list(
structure(c(0, 0.5, 0.5, 0, 0, 0.5, 0.5, 1, 1, 0.5), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg")), structure(list(
structure(c(0.5, 1, 1, 0.5, 0.5, 0.5, 0.5, 1, 1, 0.5), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg"))), n_empty = 0L, class = c("sfc_POLYGON",
"sfc"), precision = 0, crs = structure(list(epsg = NA_integer_,
proj4string = NA_character_), .Names = c("epsg", "proj4string"
), class = "crs"), bbox = structure(c(0, 0, 1, 1), .Names = c("xmin",
"ymin", "xmax", "ymax")))), .Names = c("cell_id", "geometry"), row.names = c(NA,
4L), class = c("sf", "data.frame"), sf_column = "geometry",
agr = structure(NA_integer_, class = "factor", .Label = c("constant",
"aggregate", "identity"), .Names = "cell_id"))
and test the function. In theory, I think this should work:
my_poly <- as(my_poly, "Spatial") # convert to spatial
myplot(in_rast, in_poly = my_poly)
but I get:
doing this:
in_poly <- my_poly
in_poly <- as(in_poly, "Spatial")
myplot(in_rast, in_poly = in_poly)
still fails, but with a different outcome:
The only way I found to have it working is to give to the polygon object the same name that I use inside the function (i.e., in_poly) from the beginning :
in_poly <- structure(list(cell_id = 1:4, geometry = structure(list(structure(list(
structure(c(0, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0.5, 0), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg")), structure(list(
structure(c(0.5, 1, 1, 0.5, 0.5, 0, 0, 0.5, 0.5, 0), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg")), structure(list(
structure(c(0, 0.5, 0.5, 0, 0, 0.5, 0.5, 1, 1, 0.5), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg")), structure(list(
structure(c(0.5, 1, 1, 0.5, 0.5, 0.5, 0.5, 1, 1, 0.5), .Dim = c(5L,
2L))), class = c("XY", "POLYGON", "sfg"))), n_empty = 0L, class = c("sfc_POLYGON",
"sfc"), precision = 0, crs = structure(list(epsg = NA_integer_,
proj4string = NA_character_), .Names = c("epsg", "proj4string"
), class = "crs"), bbox = structure(c(0, 0, 1, 1), .Names = c("xmin",
"ymin", "xmax", "ymax")))), .Names = c("cell_id", "geometry"), row.names = c(NA,
4L), class = c("sf", "data.frame"), sf_column = "geometry",
agr = structure(NA_integer_, class = "factor", .Label = c("constant",
"aggregate", "identity"), .Names = "cell_id"))
in_poly <- as(in_poly, "Spatial")
myplot(in_rast, in_poly = in_poly)
Can anyone explain what's happening here ? It's clearly (?) a scoping problem, but I really do not understand why the function behaves like this !
Thanks in advance !
The help page of latticeExtra::layer explains that:
the evaluation used in layer is non-standard, and can be confusing at first: you typically refer to variables as if inside the panel function (x, y, etc); you can usually refer to objects which exist in the global environment (workspace), but it is safer to pass them in by name in the data argument to layer.
When using layer inside a function, you can embed your object in a list and pass it in the data argument:
myplot <- function(in_rast, in_poly = NULL) {
rastplot <- levelplot(in_rast, margin = FALSE)
polyplot <- layer(sp.polygons(x),
data = list(x = in_poly))
print(rastplot + polyplot)
}
Now the function produces the desired result:
myplot(in_rast, in_poly = my_poly)