I've been trying to figure out the code to plot lines like these based on me copy and pasting a series of numbers into the code each day. I was trying to use an array but I'm not sure that's what I need to do. Any help would be greatly appreciated!
Example
//#version=5
indicator("Input Levels", overlay = true)
lev1 = input.float(3990, title = "Val 1", inline = "1")
col1 = input.color(color.black, title = "", inline = "1")
lev2 = input.float(3890, title = "Val 2", inline = "2")
col2 = input.color(color.green, title = "", inline = "2")
lev3 = input.float(3995, title = "Val 3", inline = "3")
col3 = input.color(color.black, title = "", inline = "3")
lev4 = input.float(3870, title = "Val 4", inline = "4")
col4 = input.color(color.red, title = "", inline = "4")
lev5 = input.float(3826, title = "Val 5", inline = "5")
col5 = input.color(color.black, title = "", inline = "5")
var float[] level_vals = array.from(lev1, lev2, lev3, lev4, lev5)
var color[] color_vals = array.from(col1, col2, col3, col4, col5)
var line[] level_lines = array.new_line()
size = array.size(level_vals)
if barstate.isfirst
for i = 0 to size - 1
array.push(level_lines, line.new(x1 = na, y1 = na, x2 = na, y2 = na, style = line.style_dashed, color = color.black, extend = extend.both))
if barstate.islast
for i = 0 to size - 1
line_i = array.get(level_lines, i)
val_i = array.get(level_vals, i)
color_i = array.get(color_vals, i)
line.set_xy1(line_i, x = bar_index - 1, y = val_i)
line.set_xy2(line_i, x = bar_index, y = val_i)
line.set_color(line_i, color = color_i)
You can save the numbers in an array, then run a for loop in the array and plot dashed line at them. Example below
//#version=5
indicator(title="Plot numbers")
var numbers=array.from(3992.5,3990.25,3989,3987.25,3985,3983.25,3981,3977.25,3971.25,3966.5)
if barstate.isfirst
for i = 0 to array.size(numbers) - 1
line.new(bar_index, array.get(numbers,i),bar_index, array.get(numbers,i), style = line.style_dashed, color = color.black, extend = extend.both)
Related
I have a long entry buy condition where
Candle time frame is 15 minutes
Alert candle high is below lower band of bollinger bands.
entry when next candle crossover the alert candle high
This script gives entry oh high breakout + 0.01 but it does not give entry in the exact breakout candle and gives entry when price comes next time on expected entry price i.e. alert candle high + 0.01.
Requesting solution to get entry in breakout candle itself and at expected breakout price.
//#version=5
strategy("Bands Reversion", overlay=true, calc_on_every_tick=true)
//// Indicator Bollinger Bands
source = close
length = input.int(20, minval=1)
mult = input.float(1.5, minval=0.001, maxval=50)
direction = input.int(0, title = "Strategy Direction", minval=-1, maxval=1)
strategy.risk.allow_entry_in(direction == 0 ? strategy.direction.all : (direction < 0 ? strategy.direction.short : strategy.direction.long))
basis = ta.sma(source, length)
dev = mult * ta.stdev(source, length)
upper = basis + dev
lower = basis - dev
plot(basis, color = color.red)
plot(upper)
plot(lower)
/// Trade entry time and squareoff time
TradeTime = input(title="Trade Timings",defval="0930-1130")
SqoffTime = input(title="Squareoff Timings",defval="1530-1545")
Barsinsession(TradeTime) => time(timeframe.period,TradeTime) != 0
Insession = Barsinsession(TradeTime) ? 1 : 0
endofsession = Insession == 0 and Insession[1] == 1
Sqsession = Barsinsession(SqoffTime) ? 1 : 0
SqTime = Sqsession == 1 and Sqsession[1] == 0
//// Input control and conditions
buy_condition = high[1] < lower[1] and ta.crossover(high, high[1]) and Insession
short_condition = low[1] > upper[1] and ta.crossunder(low, low[1]) and Insession
buy_alert_high = ta.valuewhen(buy_condition, high[1],0)
buy_alert_low = ta.valuewhen(buy_condition, low[1],0)
short_alert_low = ta.valuewhen(short_condition, low[1],0)
short_alert_high = ta.valuewhen(short_condition, high[1],0)
buy_alert_high1 = ta.valuewhen(buy_condition, high,0)
plot(buy_alert_high, style = plot.style_circles)
plot(buy_alert_low, style = plot.style_circles, offset = -2)
plot(short_alert_low, style = plot.style_circles)
plot(short_alert_high, style = plot.style_circles)
sell = ta.crossunder(close, low) or SqTime //// or SqTime if for intraday exit
cover = ta.crossover(close,high) or SqTime //// or SqTime if for intraday exit
plotshape(buy_condition, style = shape.triangleup, location = location.belowbar, color = color.green, text = "BUY")
plotshape(short_condition, style = shape.triangledown, location = location.abovebar, color = color.red, text = "SHORT")
long_price = ta.valuewhen(buy_condition, (buy_alert_high + 0.01),0 )
longstop = buy_alert_low - 0.01
longtgt = basis
short_price = ta.valuewhen(short_condition,short_alert_low - 0.01,0) ////short_alert_low - (0.01 * 100 * syminfo.mintick) //// ta.valuewhen(short_condition,short_alert_low - 0.01,0)
shortstop = short_alert_high + 0.01
shorttgt = basis
strategy.entry("long",direction = strategy.long, when = buy_condition, limit = long_price, comment ="BUY")
strategy.close("long", when = sell, comment = "SELL")
strategy.exit("long", from_entry = "long", stop = longstop, limit = longtgt, comment = "TG/SL_EXIT")
strategy.entry("short",direction = strategy.short, when = short_condition,limit = short_price, comment ="SHORT")
strategy.close("short", when = cover, comment = "COVER")
strategy.exit("short", from_entry = "short", stop = shortstop, limit = shorttgt, comment = "TG/SL_EXIT")
plot(strategy.position_size > 0 ? longstop : na, style = plot.style_linebr, color = color.red)
plot(strategy.position_size > 0 ? longtgt : na, style = plot.style_linebr, color = color.green)
plot(strategy.position_size < 0 ? shortstop : na, style = plot.style_linebr, color = color.red)
plot(strategy.position_size < 0 ? shorttgt : na, style = plot.style_linebr, color = color.green)
On checking for condition gap(high-low) > 0.1%(which is met multiple times), the label only gets
rendered ONCE (instead of on relevant bars within 25 bar lookback).
Plz provide a solution.
CODE :
Historical Bars
//#version=5
indicator("PriceMomemtum",overlay = true,max_bars_back = 25)
gap = (math.abs(high - low)/low ) * 100
//var gap = (math.abs(high - low)/low ) * 100
if gap > 0.1
var lbl = label.new(x = bar_index,y = na , text = na ,text_font_family = font.family_default ,xloc = xloc.bar_index,yloc =yloc.abovebar,style = label.style_arrowdown ,textcolor = color.white,size =size.small,textalign = text.align_left,tooltip = na)
label.set_text(lbl,str.tostring(gap,"#.00")+"%")
label.set_xy(lbl,bar_index,high )
Realtime Bars
//#version=5
indicator("PriceMomemtum",overlay = true,max_bars_back = 25)
if barstate.isrealtime
gap = (math.abs(high - low)/low ) * 100
//var gap = (math.abs(high - low)/low ) * 100
if gap > 0.1
var lbl = label.new(x = bar_index,y = na , text = na ,text_font_family = font.family_default ,xloc = xloc.bar_index,yloc =yloc.abovebar,style = label.style_arrowdown ,textcolor = color.white,size =size.small,textalign = text.align_left,tooltip = na)
label.set_text(lbl,str.tostring(gap,"#.00")+"%")
label.set_xy(lbl,bar_index,high )
alert(str.tostring(time(syminfo.timezone)) + "(PriceMomentum)", alert.freq_once_per_bar)
Have you tried defining "lbl" variable without "var"?
result
I have two symbolic expressions a and b, each consists of polynomials with basic arithmetic and small, positive, integer powers.
simplify(a - b) doesn't go up to 0, and my only alternative is to subs some random numbers into the variables and compare.
I would have expected something like expanding the expressions until there are no parentheses. Then, add all fractions into a single fraction.
I converted the data into a function which can be called as:
x = sym('x', [1 8], 'real')';
err = func( x ) % should be simplified to zeros
x0 = rand( size(x) )
double( subs(err, x, x0) )
simplify(err)
The function
function err_Dpsi_Dpsi2 = func(in1)
%FUNC
% ERR_DPSI_DPSI2 = FUNC(IN1)
% This function was generated by the Symbolic Math Toolbox version 8.4.
% 29-Dec-2020 20:03:34
x1 = in1(1,:);
x2 = in1(2,:);
x3 = in1(3,:);
x4 = in1(4,:);
x5 = in1(5,:);
x6 = in1(6,:);
x7 = in1(7,:);
x8 = in1(8,:);
t2 = x1.*x6;
t3 = x2.*x5;
t4 = x1.*x7;
t5 = x3.*x5;
t6 = x2.*x7;
t7 = x3.*x6;
t8 = -x2;
t9 = -x3;
t10 = -x6;
t11 = -x7;
t15 = x1./2.0;
t16 = x2./2.0;
t17 = x1./4.0;
t18 = x3./2.0;
t19 = x2./4.0;
t20 = x3./4.0;
t21 = x5./2.0;
t22 = x6./2.0;
t23 = x5./4.0;
t24 = x7./2.0;
t25 = x6./4.0;
t26 = x7./4.0;
t43 = x2.*7.072e+3;
t44 = x3.*7.072e+3;
t45 = x4.*7.071e+3;
t46 = x6.*7.072e+3;
t47 = x7.*7.072e+3;
t48 = x8.*7.071e+3;
t60 = x2.*x8.*-7.071e+3;
t62 = x4.*x7.*-7.071e+3;
t69 = x1.*9.999907193999999e-1;
t70 = x5.*9.999907193999999e-1;
t71 = x1.*1.0000660704;
t72 = x5.*1.0000660704;
t74 = x2.*1.0001321408;
t75 = x3.*1.0001321408;
t76 = x6.*1.0001321408;
t77 = x7.*1.0001321408;
t78 = x1.*1.0000660704;
t79 = x2.*5.000660704e-1;
t80 = x2.*1.0001321408;
t81 = x3.*5.000660704e-1;
t82 = x3.*1.0001321408;
t83 = x5.*1.0000660704;
t84 = x6.*5.000660704e-1;
t85 = x6.*1.0001321408;
t86 = x7.*5.000660704e-1;
t87 = x7.*1.0001321408;
t102 = x1.*9.999907194000001e-1;
t103 = x5.*9.999907194000001e-1;
t104 = x4.*4.999953597e-1;
t105 = x8.*4.999953597e-1;
t108 = x2.*1.000132149530596;
t109 = x3.*1.000132149530596;
t110 = x6.*1.000132149530596;
t111 = x7.*1.000132149530596;
t112 = x2.*1.000056789186827;
t113 = x3.*1.000056789186827;
t114 = x6.*1.000056789186827;
t115 = x7.*1.000056789186827;
t124 = x4.*1.000056789186827;
t125 = x8.*1.000056789186827;
t126 = x4.*9.999814388861295e-1;
t127 = x8.*9.999814388861295e-1;
t128 = x2.*1.000132149530596;
t129 = x3.*1.000132149530596;
t130 = x6.*1.000132149530596;
t131 = x7.*1.000132149530596;
t139 = x4.*2.500307147434136e-1;
t140 = x8.*2.500307147434136e-1;
t141 = x2.*1.000056789186827;
t142 = x3.*1.000056789186827;
t144 = x4.*1.000056789186827;
t145 = x6.*1.000056789186827;
t146 = x7.*1.000056789186827;
t148 = x8.*1.000056789186827;
t157 = x2.*x8.*(-2.500307147434136e-1);
t158 = x4.*x7.*(-2.500307147434136e-1);
t159 = x4.*9.999814388861297e-1;
t160 = x8.*9.999814388861297e-1;
t12 = -t3;
t13 = -t4;
t14 = -t7;
t27 = t2./4.0;
t28 = t3./4.0;
t29 = t4./4.0;
t30 = t5./4.0;
t31 = t6./4.0;
t32 = t7./4.0;
t33 = t8+x1;
t34 = t9+x1;
t35 = t10+x5;
t36 = t11+x5;
t37 = -t16;
t38 = -t18;
t39 = -t20;
t40 = -t22;
t41 = -t24;
t42 = -t26;
t52 = t6.*7.072e+3;
t53 = t48.*x2;
t54 = t7.*7.072e+3;
t55 = t45.*x6;
t56 = t48.*x3;
t57 = t45.*x7;
t58 = -t45;
t59 = -t48;
t88 = -t74;
t89 = -t75;
t90 = -t76;
t91 = -t77;
t92 = -t80;
t93 = -t79;
t94 = -t82;
t95 = -t81;
t96 = -t85;
t97 = -t84;
t98 = -t87;
t99 = -t86;
t116 = -t108;
t117 = -t109;
t118 = -t110;
t119 = -t111;
t120 = -t112;
t121 = -t113;
t122 = -t114;
t123 = -t115;
t132 = -t128;
t133 = -t129;
t134 = -t130;
t135 = -t131;
t136 = t6.*2.500660747652978e-1;
t137 = t7.*2.500660747652978e-1;
t143 = -t139;
t147 = -t140;
t149 = t140.*x2;
t150 = t139.*x6;
t151 = t140.*x3;
t152 = t139.*x7;
t153 = -t141;
t154 = -t142;
t155 = -t145;
t156 = -t146;
t49 = -t28;
t50 = -t29;
t51 = -t32;
t61 = -t54;
t63 = t43+t58;
t64 = t44+t58;
t65 = t46+t59;
t66 = t47+t59;
t67 = t2+t5+t6+t12+t13+t14;
t138 = -t137;
t161 = t15+t38+t93+t104;
t162 = t15+t37+t95+t104;
t163 = t21+t41+t97+t105;
t164 = t21+t40+t99+t105;
t169 = t71+t89+t116+t124;
t170 = t71+t88+t117+t124;
t171 = t72+t91+t118+t125;
t172 = t72+t90+t119+t125;
t173 = t78+t92+t133+t144;
t174 = t78+t94+t132+t144;
t175 = t83+t96+t135+t148;
t176 = t83+t98+t134+t148;
t177 = t69+t120+t121+t126;
t178 = t70+t122+t123+t127;
t179 = t102+t153+t154+t159;
t180 = t103+t155+t156+t160;
t68 = 1.0./t67;
t73 = t27+t30+t31+t49+t50+t51;
t106 = t52+t55+t56+t60+t61+t62;
t165 = t161.^2;
t166 = t162.^2;
t167 = t163.^2;
t168 = t164.^2;
t182 = t136+t138+t150+t151+t157+t158;
t100 = 1.0./t73;
t107 = 1.0./t106;
t181 = t165+t166+t167+t168;
t183 = 1.0./t182;
t101 = t100.^2;
t184 = t183.^2;
err_Dpsi_Dpsi2 = [t181.*(t35.*t68.*t100-t36.*t68.*t100)+t101.*t181.*(t25+t42),-t100.*t169+t100.*t174+t169.*t183-t174.*t183-t101.*t181.*(t23+t42)+t181.*t184.*(t140-x7.*2.500660747652978e-1)+t36.*t68.*t100.*t181+t66.*t107.*t181.*t183.*1.0,-t100.*t170+t100.*t173+t170.*t183-t173.*t183-t181.*t184.*(t140-x6.*2.500660747652978e-1)+t101.*t181.*(t23-t25)-t35.*t68.*t100.*t181-t65.*t107.*t181.*t183.*1.0,t100.*t177-t100.*t179-t177.*t183+t179.*t183+t181.*(t65.*t107.*t183.*9.998585972850678e-1-t66.*t107.*t183.*9.998585972850678e-1)-t181.*t184.*(x6.*2.500307147434136e-1-x7.*2.500307147434136e-1),-t181.*(t33.*t68.*t100-t34.*t68.*t100)-t101.*t181.*(t19+t39),-t100.*t171+t100.*t176+t171.*t183-t176.*t183+t101.*t181.*(t17+t39)-t181.*t184.*(t139-x3.*2.500660747652978e-1)-t34.*t68.*t100.*t181-t64.*t107.*t181.*t183.*1.0,-t100.*t172+t100.*t175+t172.*t183-t175.*t183+t181.*t184.*(t139-x2.*2.500660747652978e-1)-t101.*t181.*(t17-t19)+t33.*t68.*t100.*t181+t63.*t107.*t181.*t183.*1.0,t100.*t178-t100.*t180-t178.*t183+t180.*t183-t181.*(t63.*t107.*t183.*9.998585972850678e-1-t64.*t107.*t183.*9.998585972850678e-1)+t181.*t184.*(x2.*2.500307147434136e-1-x3.*2.500307147434136e-1)];
I found what I was looking for
num = numden( err ) % convert to rational polynomial, and we care only about the numerator
collect( num ) % cancel terms--not needed, numden does some version of simplify
My example, though, wasn't good. For some reason, there are precision issues. I thought that symbolic used exact arithmetic, but I didn't look into that. However, if I use variables instead of finite precision coefficients, then it outputs zeros.
I'm trying to improve the look of Rayshader by overlaying more recent (higher detail) satellite imagery (that I'm getting from the {leaflet} packages) but the overlay doesn't match with the 3D rendering.
Ideally I'm looking for a open-source solution that can get global satellite imagery. Bonus points if you find finer detail data for my area of interest - Hawaii.
One method using {geoviz} and {rayshader} uses the slippy_overlay() function to create a number of overlay images from either Mapbox (satellite, mapbox-streets-v8, mapbox-terrain-v2, mapbox-traffic-v1, terrain-rgb, mapbox-incidents-v1) or Stamen. Although I found mapbox-terrain-v2 the best it still lacks the detail I would like. Since it requires setting up an API for mapbox I just use stamen/watercolor below:
library(geoviz)
library(rayshader)
### Maui
lat = 20.785700
lon = -156.259204
square_km = 22
max_tiles = 10
dem <- mapzen_dem(lat, lon, square_km, max_tiles)
elev_matrix = matrix(
raster::extract(dem, raster::extent(dem), buffer=1000),
nrow = ncol(dem),
ncol = nrow(dem)
)
ambmat <- ambient_shade(elev_matrix, zscale = 30)
raymat <- ray_shade(elev_matrix, zscale = 30, lambert = TRUE)
watermap <- detect_water(elev_matrix)
overlay_img <-
slippy_overlay(dem,
image_source = "stamen",
image_type = "watercolor",
png_opacity = 0.3,
max_tiles = max_tiles)
elev_matrix %>%
sphere_shade(sunangle = 270, texture = "imhof4") %>%
add_water(detect_water(elev_matrix), color="imhof4") %>%
add_shadow(ray_shade(elev_matrix,zscale=3,maxsearch = 300),0.5) %>%
add_shadow(ambmat,0.5) %>%
add_overlay(overlay_img) %>%
plot_3d(elev_matrix,
solid = T,
water = T,
waterdepth = 0,
wateralpha = 0.5,
watercolor = "lightblue",
waterlinecolor = "white",
waterlinealpha = 0.5,
zscale= raster_zscale(dem) / 3,
fov=0,theta=135,zoom=0.75,phi=45, windowsize = c(1000,800))
I'm trying to adapt Will Bishop's workflow for getting overlays with the leaflet package but the result is very odd. Will's approach is a bit different as it fetches elevation data from USGS, which doesn't have baythmetric elevation which is must for me - so I used geoviz
library(leaflet)
# define bounding box with longitude/latitude coordinates
bbox <- list(
p1 = list(long = -156.8037, lat = 20.29737),
p2 = list(long = -155.7351, lat = 21.29577)
)
leaflet() %>%
addTiles() %>%
addRectangles(
lng1 = bbox$p1$long, lat1 = bbox$p1$lat,
lng2 = bbox$p2$long, lat2 = bbox$p2$lat,
fillColor = "transparent"
) %>%
fitBounds(
lng1 = bbox$p1$long, lat1 = bbox$p1$lat,
lng2 = bbox$p2$long, lat2 = bbox$p2$lat,
)
What's the area of my hillshade from geoviz?
dim(dem)
780 780 1
Okay so the overlay image needs to be 780 x 780 so I modify the helper functions to download the overlay with the World_Imagery base map:
define_image_size <- function(bbox, major_dim = 780) {
# calculate aspect ration (width/height) from lat/long bounding box
aspect_ratio <- abs((bbox$p1$long - bbox$p2$long) / (bbox$p1$lat - bbox$p2$lat))
# define dimensions
img_width <- ifelse(aspect_ratio > 1, major_dim, major_dim*aspect_ratio) %>% round()
img_height <- ifelse(aspect_ratio < 1, major_dim, major_dim/aspect_ratio) %>% round()
size_str <- paste(img_width, img_height, sep = ",")
list(height = img_height, width = img_width, size = size_str)
}
get_arcgis_map_image <- function(bbox, map_type = "World_Imagery", file = NULL,
width = 780, height = 780, sr_bbox = 4326) {
require(httr)
require(glue)
require(jsonlite)
url <- parse_url("https://utility.arcgisonline.com/arcgis/rest/services/Utilities/PrintingTools/GPServer/Export%20Web%20Map%20Task/execute")
# define JSON query parameter
web_map_param <- list(
baseMap = list(
baseMapLayers = list(
list(url = jsonlite::unbox(glue("https://services.arcgisonline.com/ArcGIS/rest/services/{map_type}/MapServer",
map_type = map_type)))
)
),
exportOptions = list(
outputSize = c(width, height)
),
mapOptions = list(
extent = list(
spatialReference = list(wkid = jsonlite::unbox(sr_bbox)),
xmax = jsonlite::unbox(max(bbox$p1$long, bbox$p2$long)),
xmin = jsonlite::unbox(min(bbox$p1$long, bbox$p2$long)),
ymax = jsonlite::unbox(max(bbox$p1$lat, bbox$p2$lat)),
ymin = jsonlite::unbox(min(bbox$p1$lat, bbox$p2$lat))
)
)
)
res <- GET(
url,
query = list(
f = "json",
Format = "PNG32",
Layout_Template = "MAP_ONLY",
Web_Map_as_JSON = jsonlite::toJSON(web_map_param))
)
if (status_code(res) == 200) {
body <- content(res, type = "application/json")
message(jsonlite::toJSON(body, auto_unbox = TRUE, pretty = TRUE))
if (is.null(file))
file <- tempfile("overlay_img", fileext = ".png")
img_res <- GET(body$results[[1]]$value$url)
img_bin <- content(img_res, "raw")
writeBin(img_bin, file)
message(paste("image saved to file:", file))
} else {
message(res)
}
invisible(file)
}
Now download the file, then load it
image_size <- define_image_size(bbox, major_dim = 780)
# fetch overlay image
overlay_file <- "maui_overlay.png"
get_arcgis_map_image(bbox, map_type = "World_Imagery", file = overlay_file,
# width = image_size$width, height = image_size$height,
sr_bbox = 4326)
overlay_img <- png::readPNG("maui_overlay.png")
Okay let's make the plot
elev_matrix %>%
sphere_shade(sunangle = 270, texture = "imhof4") %>%
add_water(detect_water(elev_matrix), color="imhof4") %>%
add_shadow(ray_shade(elev_matrix,zscale=3,maxsearch = 300),0.5) %>%
add_shadow(ambmat,0.5) %>%
add_overlay(overlay_img, alphacolor = 1) %>%
plot_3d(elev_matrix,
solid = T,
water = T,
waterdepth = 0,
wateralpha = 0.5,
watercolor = "lightblue",
waterlinecolor = "white",
waterlinealpha = 0.5,
zscale= raster_zscale(dem) / 3,
fov=0,theta=135,zoom=0.75,phi=45, windowsize = c(1000,800))
As you can see the overlay image is rotated to the hillshade.
Now I'm also realizing that fetching satellite with a bounding box method isn't ideal when you're trying to show bathymatrix data. It would be ideal to subset this overlay somehow programmatically but I'll probably just end up using inkscape once I've figured out how to rotate the overlay.
I tried to use the {magick}'s image_rotate() function to no avail:
library(magick)
maui <- magick::image_read("maui_overlay.png")
image_rotate(maui, 30) # -> maui_30
# image_write(maui_30, path = "maui_overlay_30.png", format = "png")
But magick has changed the dimensions:
# A tibble: 1 x 7
format width height colorspace matte filesize density
<chr> <int> <int> <chr> <lgl> <int> <chr>
1 PNG 1068 1068 sRGB TRUE 0 38x38
And will give an error with rayshader:
overlay_img <- png::readPNG("maui_overlay_30.png")
elev_matrix %>%
sphere_shade(sunangle = 270, texture = "imhof4") %>%
add_water(detect_water(elev_matrix), color="imhof4") %>%
add_shadow(ray_shade(elev_matrix,zscale=3,maxsearch = 300),0.5) %>%
add_shadow(ambmat,0.5) %>%
add_overlay(overlay_img, alphacolor = 1) %>%
plot_3d(elev_matrix,
solid = T,
water = T,
waterdepth = 0,
wateralpha = 0.5,
watercolor = "lightblue",
waterlinecolor = "white",
waterlinealpha = 0.5,
zscale= raster_zscale(dem) / 3,
fov=0,theta=135,zoom=0.75,phi=45, windowsize = c(1000,800))
Error in add_overlay(., overlay_img, alpha = 0.8) : argument 3 matches multiple formal arguments
The answer couldn't have been simpler... it needed to be transposed overlay_img = aperm(overlay_img, c(2,1,3)).
I have a nested cell of cells like the one below:
CellArray={1,1,1,{1,1,1,{1,1,{1,{1 1 1 1 1 1 1 1}, 1,1},1,1},1,1,1},1,1,1,{1,1,1,1}};
I need to randomly pick a location in CellArray. All members' locations of CellArray must have same chances to be chosen in the random selection process. Thanks.
You can capture the output of the celldisp function. Then use regex to extrcat indices:
s=evalc('celldisp(CellArray,'''')');
m = regexp(s, '\{[^\=]*\}', 'match');
Thanks to #excaza that suggested a clearer use of regexp
Result:
m =
{
[1,1] = {1}
[1,2] = {2}
[1,3] = {3}
[1,4] = {4}{1}
[1,5] = {4}{2}
[1,6] = {4}{3}
[1,7] = {4}{4}{1}
[1,8] = {4}{4}{2}
[1,9] = {4}{4}{3}{1}
[1,10] = {4}{4}{3}{2}{1}
[1,11] = {4}{4}{3}{2}{2}
[1,12] = {4}{4}{3}{2}{3}
[1,13] = {4}{4}{3}{2}{4}
[1,14] = {4}{4}{3}{2}{5}
[1,15] = {4}{4}{3}{2}{6}
[1,16] = {4}{4}{3}{2}{7}
[1,17] = {4}{4}{3}{2}{8}
[1,18] = {4}{4}{3}{3}
[1,19] = {4}{4}{3}{4}
[1,20] = {4}{4}{4}
[1,21] = {4}{4}{5}
[1,22] = {4}{5}
[1,23] = {4}{6}
[1,24] = {4}{7}
[1,25] = {5}
[1,26] = {6}
[1,27] = {7}
[1,28] = {8}{1}
[1,29] = {8}{2}
[1,30] = {8}{3}
[1,31] = {8}{4}
}
Use randi to select an index:
m{randi(numel(m))}