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server.R
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library(shiny)
library(SimSpin)
library(plot3D)
shinyServer(function(input, output, session) {
# sim_analysis() tab ----------------------------------------------------------------------------
df <- reactive({
if (input$example_file == TRUE){
validate(
need(try(SimSpin::sim_data(filename = system.file("extdata", 'SimSpin_example.hdf5', package="SimSpin"),
ptype = input$ptype)), "NPart Error: Some requested particle types are missing from this simulation.")
)
galaxy_file = SimSpin::sim_data(filename = system.file("extdata", 'SimSpin_example.hdf5', package="SimSpin"),
ptype = input$ptype)
if (input$DM_profile == "Hernquist"){
SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = list("profile" = "Hernquist", "DM_mass" = input$DM_mass, "DM_a" = input$DM_a))
} else if (input$DM_profile == "NFW"){
SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = list("profile"="NFW", "DM_vm" = input$DM_vm, "DM_a" = input$DM_a, "DM_rhof" = input$DM_rhof))
} else if (input$DM_profile == "None") {
validate(
need(try(SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = NA)), "DMpart Error: There are no dark matter particles in this model. Describe an analytic potential to calculate the total kinematic profile correctly.")
)
SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = NA)
}
} else if (input$example_file == FALSE){
validate(
need(try(SimSpin::sim_data(filename = input$sim_file$datapath,
ptype = input$ptype)), "NPart Error: Some requested particle types are missing from this simulation.")
)
galaxy_file = SimSpin::sim_data(filename = input$sim_file$datapath,
ptype = input$ptype)
if (input$DM_profile == "Hernquist"){
SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = list("profile" = "Hernquist", "DM_mass" = input$DM_mass, "DM_a" = input$DM_a))
} else if (input$DM_profile == "NFW"){
SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = list("profile"="NFW", "DM_vm" = input$DM_vm, "DM_a" = input$DM_a, "DM_rhof" = input$DM_rhof))
} else if (input$DM_profile == "None") {
validate(
need(try(SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = NA)), "DMpart Error: There are no dark matter particles in this model. Describe an analytic potential to calculate the total kinematic profile correctly.")
)
SimSpin::sim_analysis(simdata = galaxy_file,
bin_type = input$bin_type,
rmax = input$rmax,
rbin = input$rbin,
DM_profile = NA)
}
}
}) # running SimSpin::sim_analysis() outside the output generation to be accessed by each
pal <- reactive({
colorRampPalette(rev(RColorBrewer::brewer.pal(10,'Spectral')))(8)
}) # colours for plots
output$segments_title <- renderUI({
HTML(paste("Simulation segments"))
}) # header for segments
output$simulation_segments <- renderPlot({
if (input$submit_1 == 0){
return()
} # only create plot once "submit_1" button is pressed
isolate({
if (input$rmax >= input$rbin){ # if the max radius is greater than the number of bins
if (input$rmax / input$rbin < 5){ # if the spacing between bins is less than 2kpc
lout = input$rmax / 5
} else {lout = input$rbin}
} else if (input$rbin > input$rmax){
if (input$rmax / input$rbin < 5){
lout = input$rmax / 5
} else {lout = input$rbin}
}
if (input$bin_type == "r" | input$bin_type == "cr"){
magicaxis::magplot(df()$part_data$x, df()$part_data$y, pch=".",
xlim = c(-(input$rmax + 10), input$rmax + 10),
ylim = c(-(input$rmax + 10), input$rmax + 10),
xlab = "x, kpc", ylab = "y, kpc", col="black", asp=1)
plotrix::draw.circle(0,0, seq(input$rmax/input$rbin, input$rmax, length.out = lout), border="red")
} else if (input$bin_type == "z"){
magicaxis::magplot(df()$part_data$x, df()$part_data$z, pch=".",
xlim = c(-(input$rmax + 10), input$rmax + 10),
ylim = c(-(input$rmax + 10), input$rmax + 10),
xlab = "x, kpc", ylab = "z, kpc", col="black", asp=1)
abline(h=0, col="red")
abline(h=seq(input$rmax/input$rbin, input$rmax, length.out = lout), col="red")
}
})
}) # drawing the particle distributions and bin divisions
output$user_specs <- renderUI({
if (input$submit_1 == 0){
return()
}
isolate({
if (input$example_file == TRUE){
validate(
need(try(SimSpin::sim_data(filename = system.file("extdata", 'SimSpin_example.hdf5', package="SimSpin"),
ptype = input$ptype)), "NPart Error: Some requested particle types are missing from this simulation.")
)
galaxy_file = SimSpin::sim_data(filename = system.file("extdata", 'SimSpin_example.hdf5', package="SimSpin"),
ptype = input$ptype)
} else if (input$example_file == FALSE){
validate(
need(try(SimSpin::sim_data(filename = input$sim_file$datapath,
ptype = input$ptype)), "NPart Error: Some requested particle types are missing from this simulation.")
)
galaxy_file = SimSpin::sim_data(filename = input$sim_file$datapath,
ptype = input$ptype)
}
ptypes = names(galaxy_file)
p_dat = tags$b("This analysis contains:")
DM_num = sprintf("%i Dark matter particles", if("PartType0" %in% ptypes){nrow(galaxy_file$PartType0$Part)}else{0})
D_num = sprintf("%i Disc particles", if("PartType2" %in% ptypes){nrow(galaxy_file$PartType2$Part)}else{0})
B_num = sprintf("%i Bulge particles", if("PartType3" %in% ptypes){nrow(galaxy_file$PartType3$Part)}else{0})
u_choice = sprintf("You have chosen to divide this into <b>%i</b> '%s' bin(s) out to a maximum radius of <b>%i</b>.", input$rbin, input$bin_type, input$rmax)
if (input$DM_profile == "Hernquist"){
anpot_num = sprintf("You have supplied an <b><u>Hernquist</u></b> analytic potential with <u>total mass</u> of <b>%.3f</b> and <u>halo scale radius</u> of <b>%.1f</b>.", input$DM_mass, input$DM_a)
HTML(paste("", p_dat, DM_num, D_num, B_num, "", anpot_num, "", u_choice, sep="<br/>"))
} else if (input$DM_profile == "NFW"){
anpot_num = sprintf("You have supplied an <b><u>NFW</u></b> analytic potential with a <u>virial mass</u> of <b>%.3f</b>, <u>halo scale radius</u> of <b>%.1f</b>, and a <u>density at the flattening radius</u> of <b>%.3f</b>", input$DM_vm, input$DM_a, input$DM_rhof)
HTML(paste("", p_dat, DM_num, D_num, B_num, "", anpot_num, "", u_choice, sep="<br/>"))
} else if (input$DM_profile == "None" && df()$head_data$Npart[2] == 0){
anpot_num = sprintf("<b>BEWARE:</b> This simulation does not contain any dark matter particles and you have <emph>NOT</emph> specified an analytic potential. The kinematic velocity distribution will not be correct in this case.")
HTML(paste("", p_dat, DM_num, D_num, B_num, "", anpot_num, "", u_choice, sep="<br/>"))
} else {
HTML(paste("", p_dat, DM_num, D_num, B_num, "", u_choice, sep="<br/>"))
}
})
}) # writing the user specifications being used for kinematic calculation
output$logp_title <- renderUI({
HTML(paste("Density log(ρ) distribution"))
}) # header for density plot
output$logp_dist <- renderPlot({if (input$submit_1 == 0){
return()
} # only create plot once "submit_1" button is pressed
isolate({
if (input$bin_type == "r"){
magicaxis::magplot(df()$profile$r, df()$profile$logp, type="l", lty=1, lwd=3,
xlim = c(0, input$rmax),
xlab = "r, kpc", ylab = expression("log"[10]*"("*paste(rho)*"), 10"^{10}*" M"['\u0298']*"kpc"^{-3}),
col = pal()[1])
} else if (input$bin_type == "cr"){
magicaxis::magplot(df()$profile$cr, df()$profile$logp, type="l", lty=1, lwd=3,
xlim = c(0, input$rmax),
xlab = "cr, kpc", ylab = expression("log"[10]*"("*paste(rho)*"), 10"^{10}*" M"['\u0298']*"kpc"^{-3}),
col = pal()[1])
} else if (input$bin_type == "z"){
magicaxis::magplot(df()$profile$z, df()$profile$logp, type="l", lty=1, lwd=3,
xlim = c(0, input$rmax),
xlab = "z, kpc", ylab = expression("log"[10]*"("*paste(rho)*"), 10"^{10}*" M"['\u0298']*"kpc"^{-3}),
col = pal()[1])
}
})
}) # plot density distribution
output$vrot_title <- renderUI({
HTML(paste("Velocity distribution"))
}) # header for vrot plot
output$vrot_dist <- renderPlot({
if (input$submit_1 == 0){
return()
} # only create plot once "submit_1" button is pressed
isolate({
if (input$bin_type == "r"){
magicaxis::magplot(df()$profile$r, df()$profile$vc, type="l", lty=1, lwd=3,
xlim = c(0, input$rmax),
xlab = "r, kpc", ylab = expression("v"[c]*", km/s"),
col = pal()[6])
} else if (input$bin_type == "cr"){
magicaxis::magplot(df()$profile$cr, df()$profile$vcr, type="p", pch=16, lwd=3,
xlim = c(0, input$rmax),
xlab = "cr, kpc", ylab = expression("v"[cr]*", km/s"),
col = pal()[6])
s_vcr = sqrt(mean(df()$profile$vcr * df()$profile$vcr)-(mean(df()$profile$vcr))^2)
abline(h=c(-s_vcr, s_vcr), col=pal()[8])
} else if (input$bin_type == "z"){
magicaxis::magplot(df()$profile$z, df()$profile$vz, type="p", pch=16, lwd=3,
xlim = c(0, input$rmax),
xlab = "z, kpc", ylab = expression("v"[z]*", km/s"),
col = pal()[6])
s_vz = sqrt(mean(df()$profile$vz * df()$profile$vz, na.rm = T)-(mean(df()$profile$vz, na.rm = T))^2)
abline(h=c(-s_vz, s_vz), col=pal()[8])
}
})
}) # plot velocity distribution
output$vrot_beware <- renderUI({
if (input$submit_1 == 0){
return()
}
isolate({
if (input$DM_profile == "None" && df()$head_data$Npart[2] == 0){
beware_1 = sprintf("<b>BEWARE:</b> This simulation does not contain any dark matter particles and you have <emph>NOT</emph> specified an analytic potential. The kinematic velocity distribution will not be correct in this case.")
HTML(paste("", beware_1, "", sep="<br/>"))
}
})
}) # writing beware if the analytic potential is not specified and no DM particles exist in the simulation
output$kin_title <- renderUI({
HTML(paste("General kinematic properties"))
}) # header for kinematics table
output$kinematics <- renderTable({
if (input$submit_1 == 0){
return()
} # only create plot once "submit_1" button is pressed
isolate({
if (input$bin_type == "r"){
kin_dat = data.frame("r<sub>max</sub> / kpc" = input$rmax,
"M(r<sub>max</sub>) / 10<sup>10</sup>M<sub>☉</sub>" = max(df()$profile$Mass, na.rm = T),
"max(v<sub>c</sub>) / kms<sup>-1</sup>" = max(df()$profile$vc, na.rm = T),
"λ'(r<sub>max</sub>)" = df()$profile$lambda[input$rbin],
"σ<sub>z</sub> / kpc" = df()$sigma_z,
check.names = F)
} else if (input$bin_type == "cr"){
kin_dat = data.frame("r<sub>max</sub> / kpc" = input$rmax,
"M(r<sub>max</sub>) / 10<sup>10</sup>M<sub>☉</sub>" = max(df()$profile$Mass, na.rm = T),
"σ<sub>vcr</sub> / kms<sup>-1</sup>" = sqrt(mean(df()$profile$vcr * df()$profile$vcr, na.rm = T)-(mean(df()$profile$vcr, na.rm = T))^2),
"σ<sub>z</sub> / kpc" = df()$sigma_z,
check.names = F)
} else if (input$bin_type == "z"){
kin_dat = data.frame("r<sub>max</sub> / kpc" = input$rmax,
"M(r<sub>max</sub>) / 10<sup>10</sup>M<sub>☉</sub>" = max(df()$profile$Mass),
"σ<sub>vz</sub> / kms<sup>-1</sup>" = sqrt(mean(df()$profile$vz * df()$profile$vz, na.rm = T)-(mean(df()$profile$vz, na.rm = T))^2),
"σ<sub>z</sub> / kpc" = df()$sigma_z,
check.names = F)
}
})
}, sanitize.colnames.function = function(x) x) # kinematics table
output$kin_beware <- renderUI({
if (input$submit_1 == 0){
return()
}
isolate({
if (input$DM_profile == "None" && df()$head_data$Npart[2] == 0){
beware_2 = sprintf("<b>BEWARE:</b> This simulation does not contain any dark matter particles and you have <emph>NOT</emph> specified an analytic potential. The kinematic velocity distribution will not be correct in this case.")
HTML(paste("", beware_2, "", sep="<br/>"))
}
})
}) # writing beware if the analytic potential is not specified and no DM particles exist in the simulation
# build_datacube() tab --------------------------------------------------------------------------
dc_galfile <- reactive({
if (input$example_file_2 == TRUE){
SimSpin::sim_data(filename = system.file("extdata", 'SimSpin_example.hdf5', package="SimSpin"),
ptype = input$ptype_2,
m2l_disc = input$m2l_disc,
m2l_bulge = input$m2l_bulge)
} else if (input$example_file_2 == FALSE){
SimSpin::sim_data(filename = input$sim_file_2$datapath,
ptype = input$ptype_2,
m2l_disc = input$m2l_disc,
m2l_bulge = input$m2l_bulge)
}
})
dc <- reactive({
if (input$blur == "FALSE"){
if (input$survey == "SAMI"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg,
threshold = 25)
} else if (input$survey == "MaNGA"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg,
threshold = 25)
} else if (input$survey == "CALIFA"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg,
threshold = 25)
} else if (input$survey == "Hector"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg,
threshold = 30)
} else if (input$survey == "Specified"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = input$fov,
ap_shape = input$ap_shape,
central_wvl = input$central_wvl,
lsf_fwhm = input$lsf_fwhm,
pixel_sscale = input$pixel_sscale,
pixel_vscale = input$pixel_vscale,
inc_deg = input$inc_deg,
threshold = input$threshold)
}
} else if (input$blur == "TRUE"){
if (input$survey == "SAMI"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg,
threshold = 25,
blur = list("psf" = input$psf, "fwhm" = input$fwhm))
} else if (input$survey == "MaNGA"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg,
threshold = 25,
blur = list("psf" = input$psf, "fwhm" = input$fwhm))
} else if (input$survey == "CALIFA"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg,
threshold = 25,
blur = list("psf" = input$psf, "fwhm" = input$fwhm))
} else if (input$survey == "Hector"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg,
threshold = 30,
blur = list("psf" = input$psf, "fwhm" = input$fwhm))
} else if (input$survey == "Specified"){
SimSpin::build_datacube(simdata = dc_galfile(),
z = input$z,
fov = input$fov,
ap_shape = input$ap_shape,
central_wvl = input$central_wvl,
lsf_fwhm = input$lsf_fwhm,
pixel_sscale = input$pixel_sscale,
pixel_vscale = input$pixel_vscale,
inc_deg = input$inc_deg,
threshold = input$threshold,
blur = list("psf" = input$psf, "fwhm" = input$fwhm))
}
}
}) # running SimSpin::build_datacube() outside the output generation to be accessed by each
output$bc_title <- renderUI({
HTML(paste("Velocity data cube"))
}) # header for build_datacube() tab
output$datacube <- renderPlot({
if (input$submit_2 == 0){
return()
} # only create plot once "submit_2" button is pressed
isolate({
dc_dim = dim(dc()$datacube)
v_len = floor(dc_dim[3]*0.5)
shuffle_dc = array(data = NA, dim = c(dc_dim[1], dc_dim[3], dc_dim[2]))
test = array(data = 0, dim = c(dc_dim[1], dc_dim[3], dc_dim[2]))
for (n in 1:dc_dim[1]){
shuffle_dc[,,n] = dc()$datacube[,n,]
}
shuffle_dc[shuffle_dc < (max(shuffle_dc) * 0.05)] = NA
plot3D::slice3D(x = seq(dc()$xbin_labels[1], dc()$xbin_labels[dc_dim[1]], length.out = dc_dim[1]),
y = seq(dc()$vbin_labels[floor((dc_dim[3]/2)-(v_len/2))], dc()$vbin_labels[floor((dc_dim[3]/2)+(v_len/2))], length.out = v_len),
z = seq(dc()$xbin_labels[1], dc()$xbin_labels[dc_dim[1]], length.out = dc_dim[1]),
colvar = shuffle_dc[,seq(floor((dc_dim[3]/2)-(v_len/2)), floor((dc_dim[3]/2)+(v_len/2)), length.out = v_len),],
ys = seq(dc()$vbin_labels[floor((dc_dim[3]/2)-(v_len/2))], dc()$vbin_labels[floor((dc_dim[3]/2)+(v_len/2))], length.out = v_len),
zs = NULL, xs = NULL,
phi = 50, theta = 35, colkey = FALSE,
NAcol=rgb(1,1,1,alpha=0.01),
xlab = "x", ylab = "velocity, km/s",
zlab = "y", ticktype = "detailed",
nticks = c(10,10,v_len))
plot3D::slicecont3D(x = seq(dc()$xbin_labels[1], dc()$xbin_labels[dc_dim[1]], length.out = dc_dim[1]),
y = seq(dc()$vbin_labels[floor((dc_dim[3]/2)-(v_len/2))], dc()$vbin_labels[floor((dc_dim[3]/2)+(v_len/2))], length.out = v_len),
z = seq(dc()$xbin_labels[1], dc()$xbin_labels[dc_dim[1]], length.out = dc_dim[1]),
colvar = test[,seq(floor((dc_dim[3]/2)-(v_len/2)), floor((dc_dim[3]/2)+(v_len/2)), length.out = v_len),],
ys = seq(dc()$vbin_labels[floor((dc_dim[3]/2)-(v_len/2))], dc()$vbin_labels[floor((dc_dim[3]/2)+(v_len/2))], length.out = v_len),
zs = NULL, xs = NULL,
colkey = FALSE,
NAcol=rgb(1,1,1,alpha=0.01),
add=TRUE, border="black")
})
}, height=reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*3/5,0)))
# datacube plot
output$build_sum_title <- renderUI({
HTML(paste("Data cube summary"))
}) # header for build_datacube() table
output$build_summary <- renderTable({
if (input$submit_2 == 0){
return()
} # only create plot once "submit_2" button is pressed
isolate({
if (input$blur == "FALSE"){
build_dat = data.frame("Spaxel size / kpc" = abs(dc()$xbin_labels[2] - dc()$xbin_labels[1]),
"Voxel size / kms<sup>-1</sup>" = abs(dc()$vbin_labels[2] - dc()$vbin_labels[1]),
"Semi-major, a / kpc" = dc()$axis_ratio$a,
"Semi-minor, b / kpc" = dc()$axis_ratio$b,
check.names = F)
} else if (input$blur == "TRUE"){
build_dat = data.frame("Spaxel size / kpc" = abs(dc()$xbin_labels[2] - dc()$xbin_labels[1]),
"Voxel size / kms<sup>-1</sup>" = abs(dc()$vbin_labels[2] - dc()$vbin_labels[1]),
"Semi-major, a / kpc" = dc()$axis_ratio$a,
"Semi-minor, b / kpc" = dc()$axis_ratio$b,
"FWHM / ''" = input$fwhm,
check.names = F)
}
})
}, sanitize.colnames.function = function(x) x) # kinematics table
# find_lambda() tab -----------------------------------------------------------------------------
fl_galfile <- reactive({
if (input$example_file_3 == TRUE){
SimSpin::sim_data(filename = system.file("extdata", 'SimSpin_example.hdf5', package="SimSpin"),
ptype = input$ptype_3,
m2l_disc = input$m2l_disc_2,
m2l_bulge = input$m2l_bulge_2)
} else if (input$example_file_3 == FALSE){
SimSpin::sim_data(filename = input$sim_file_3$datapath,
ptype = input$ptype_3,
m2l_disc = input$m2l_disc_2,
m2l_bulge = input$m2l_bulge_2)
}
})
fl <- reactive({
if (input$blur_2 == "FALSE" && input$measure_type == "Fit" && input$survey_2 == "SAMI"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fit", "fac"=input$fac),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fit" && input$survey_2 == "MaNGA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fit", "fac"=input$fac),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fit" && input$survey_2 == "CALIFA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fit", "fac"=input$fac),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fit" && input$survey_2 == "Hector"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fit", "fac"=input$fac),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fit" && input$survey_2 == "Specified"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = input$fov_2,
ap_shape = input$ap_shape_2,
central_wvl = input$central_wvl_2,
lsf_fwhm = input$lsf_fwhm_2,
pixel_sscale = input$pixel_sscale_2,
pixel_vscale = input$pixel_vscale_2,
inc_deg = input$inc_deg_2,
threshold = input$threshold_2,
measure_type = list("type"="fit", "fac"=input$fac),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Specified" && input$survey_2 == "SAMI"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Specified" && input$survey_2 == "MaNGA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Specified" && input$survey_2 == "CALIFA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Specified" && input$survey_2 == "Hector"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Specified" && input$survey_2 == "Specified"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = input$fov_2,
ap_shape = input$ap_shape_2,
central_wvl = input$central_wvl_2,
lsf_fwhm = input$lsf_fwhm_2,
pixel_sscale = input$pixel_sscale_2,
pixel_vscale = input$pixel_vscale_2,
inc_deg = input$inc_deg_2,
threshold = input$threshold_2,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fixed" && input$survey_2 == "SAMI"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fixed" && input$survey_2 == "MaNGA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fixed" && input$survey_2 == "CALIFA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fixed" && input$survey_2 == "Hector"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "FALSE" && input$measure_type == "Fixed" && input$survey_2 == "Specified"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = input$fov_2,
ap_shape = input$ap_shape_2,
central_wvl = input$central_wvl_2,
lsf_fwhm = input$lsf_fwhm_2,
pixel_sscale = input$pixel_sscale_2,
pixel_vscale = input$pixel_vscale_2,
inc_deg = input$inc_deg_2,
threshold = input$threshold_2,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fit" && input$survey_2 == "SAMI"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fit", "fac"=input$fac),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fit" && input$survey_2 == "MaNGA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fit", "fac"=input$fac),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fit" && input$survey_2 == "CALIFA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fit", "fac"=input$fac),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fit" && input$survey_2 == "Hector"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fit", "fac"=input$fac),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fit" && input$survey_2 == "Specified"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = input$fov_2,
ap_shape = input$ap_shape_2,
central_wvl = input$central_wvl_2,
lsf_fwhm = input$lsf_fwhm_2,
pixel_sscale = input$pixel_sscale_2,
pixel_vscale = input$pixel_vscale_2,
inc_deg = input$inc_deg_2,
threshold = input$threshold_2,
measure_type = list("type"="fit", "fac"=input$fac),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Specified" && input$survey_2 == "SAMI"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Specified" && input$survey_2 == "MaNGA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Specified" && input$survey_2 == "CALIFA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Specified" && input$survey_2 == "Hector"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Specified" && input$survey_2 == "Specified"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = input$fov_2,
ap_shape = input$ap_shape_2,
central_wvl = input$central_wvl_2,
lsf_fwhm = input$lsf_fwhm_2,
pixel_sscale = input$pixel_sscale_2,
pixel_vscale = input$pixel_vscale_2,
inc_deg = input$inc_deg_2,
threshold = input$threshold_2,
measure_type = list("type"="specified",
"fract"=input$fract,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fixed" && input$survey_2 == "SAMI"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 15,
ap_shape = "circular",
central_wvl = 4800,
lsf_fwhm = 2.65,
pixel_sscale = 0.5,
pixel_vscale = 1.04,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fixed" && input$survey_2 == "MaNGA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 22,
ap_shape = "hexagonal",
central_wvl = 4950,
lsf_fwhm = 2.8,
pixel_sscale = 0.25,
pixel_vscale = 1.2,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fixed" && input$survey_2 == "CALIFA"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4200,
lsf_fwhm = 5.65,
pixel_sscale = 1,
pixel_vscale = 2,
inc_deg = input$inc_deg_2,
threshold = 25,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fixed" && input$survey_2 == "Hector"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = 30,
ap_shape = "hexagonal",
central_wvl = 4800,
lsf_fwhm = 1.3,
pixel_sscale = 1.6,
pixel_vscale = 0.05,
inc_deg = input$inc_deg_2,
threshold = 30,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
} else if (input$blur_2 == "TRUE" && input$measure_type == "Fixed" && input$survey_2 == "Specified"){
SimSpin::find_lambda(simdata = fl_galfile(),
z = input$z_2,
fov = input$fov_2,
ap_shape = input$ap_shape_2,
central_wvl = input$central_wvl_2,
lsf_fwhm = input$lsf_fwhm_2,
pixel_sscale = input$pixel_sscale_2,
pixel_vscale = input$pixel_vscale_2,
inc_deg = input$inc_deg_2,
threshold = input$threshold_2,
measure_type = list("type"="fixed",
"fac"=input$fac,
"axis_ratio"=data.frame("a"=input$ar_a, "b"=input$ar_b)),
blur = list("psf"=input$psf_2, "fwhm"=input$fwhm_2),
IFU_plot = FALSE)
}
})
output$fl_flux_title <- renderUI({
HTML(paste("Flux map"))
}) # header for flux image
output$fl_flux_plot <- renderPlot({
if (input$submit_3 == 0){
return()
} # only create plot once "submit_3" button is pressed
isolate({
appregion = fl()$appregion
appregion[appregion == 0] = NA
counts_img = fl()$counts_img * appregion
axis_data = fl()$axis_ratio
sbin = dim(counts_img)[1]
sbinsize = fl()$sbinsize
xcen = (sbin/2)
ycen = (sbin/2)
par(mfcol=c(1,1), family="sans", font=2, cex=1.15)
magicaxis::magimage(asinh(counts_img), xaxt="n", yaxt="n", ann=FALSE, col=rev(colorRampPalette(RColorBrewer::brewer.pal(9, "RdYlBu")[1:5])(100)), magmap=FALSE, zlim = range(c(asinh(fl()$counts_img))), family="sans", font=2, cex.lab=2)
fields::image.plot(legend.only = TRUE, zlim = range(c(fl()$counts_img)), col = rev(colorRampPalette(RColorBrewer::brewer.pal(9, "RdYlBu")[1:5])(100)), horizontal = TRUE, family="sans", font=2, legend.lab = expression("flux, 10"^{-16} * "erg s"^{-1} * "cm"^{-2} * "arcsec"^{-2}), cex.lab=2)
plotrix::draw.ellipse(x = xcen, y = ycen, a = axis_data$a_kpc / sbinsize, b = axis_data$b_kpc / sbinsize, angle = axis_data$angle - 90, border="red", lwd = 5, deg=TRUE)
})
}, height=reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*3/5,0)))
# plotting the flux images
output$fl_vel_title <- renderUI({
HTML(paste("Velocity map"))
}) # header for velocity image
output$fl_vel_plot <- renderPlot({
if (input$submit_3 == 0){