Julian/JuliaMSI
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Images are now plots, now you can select the pixel of the plot to create a spectra according to those coordenates, gave more clearness to the code by creating functions for some processes

Browse Source
This commit is contained in:
Pixelguy14 2025-01-26 13:48:18 -06:00
parent b660d7defb
commit 7667bc26e9
5 changed files with 401 additions and 277 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

14
README.md
View File

@ -9,12 +9,12 @@ A Graphical User Interface for MSI in Julia: https://github.com/CINVESTAV-LABI/j
unzip the file in your desired location<br>
## Load User Interface
1. Set working directory to Julia_msi_GUI (this repository) in your terminal using:
linux:
1. Set working directory to Julia_msi_GUI (this repository) in your terminal using:<br>
Linux:
```
cd PathToRepository/Julia_msi_GUI-main
```
windows/mac:
Windows/Mac:
```
cd PathToRepository\Julia_msi_GUI-main
```
@ -24,7 +24,7 @@ A Graphical User Interface for MSI in Julia: https://github.com/CINVESTAV-LABI/j
```
3. After the script has finished loading, it should open a page (http://127.0.0.1:1481/) in your browser with the web app running.
Additional notes:
After the first boot initializes the packages in your computer, subsequent uses of the app should not take longer to load.
Recomended system requirements: 4 core processor, 8 GB ram
Minimum system requirements: 2 core processor, 8 GB ram (long loading times)
Additional notes:<br>
After the first boot initializes the packages in your computer, subsequent uses of the app should not take longer to load.<br>
Recomended system requirements: 4 core processor, 8 GB ram<br>
Minimum system requirements: 2 core processor, 8 GB ram (long loading times)<br>

641
app.jl
View File

@ -15,18 +15,18 @@ using NativeFileDialog # Opens the file explorer depending on the OS
using StipplePlotly
@genietools
# ==Code import ==
# == Code import ==
# add your data analysis code here or in the lib folder. Code in lib/ will be
# automatically loaded
rgb_ViridisPalette=reinterpret(ColorTypes.RGB24, ViridisPalette)
# ==Search functions ==
# == Search functions ==
function increment_image(current_image, image_list)
if isempty(image_list)
return nothing
end
current_index=findfirst(isequal(current_image), image_list)
if current_index ==nothing || current_index ==length(image_list) || current_image ===""
if current_index==nothing || current_index==length(image_list) || current_image ===""
return image_list[length(image_list)] # Return the current image if it's the last one or not found
else
return image_list[current_index + 1] # Move to the next image
@ -38,17 +38,215 @@ function decrement_image(current_image, image_list)
return nothing
end
current_index=findfirst(isequal(current_image), image_list)
if current_index ==nothing || current_index ==1 || current_image ===""
if current_index==nothing || current_index==1 || current_image===""
return image_list[1] # Return the current image if it's the first one or not found
else
return image_list[current_index - 1] # Move to the previous image
end
end
# ==Reactive code ==
## Plot Image functions
# loadImgPlot recieves the local directory of the image as a string,
# returns the layout and data for the heatmap plotly plot
# this function loads the image into a plot
function loadImgPlot(interfaceImg::String)
# Load the image
cleaned_img=replace(interfaceImg, r"\?.*" => "")
cleaned_img=lstrip(cleaned_img, '/')
var=joinpath("./public", cleaned_img)
img=load(var)
# Convert to grayscale
img_gray=Gray.(img)
img_array=Array(img_gray)
#println(typeof(img_array))
elevation=Float32.(Array(img_gray))
#println(typeof(elevation))
# Get the X, Y coordinates of the image
height, width = size(img_array)
#println("height: $(height), width: $(width)")
X = collect(1:width)
Y = collect(1:height)
# Create the layout
layout = PlotlyBase.Layout(
xaxis = PlotlyBase.attr(
visible = false,
scaleanchor = "y"
),
yaxis = PlotlyBase.attr(
visible = false
)
)
# Create the trace for the image
trace = PlotlyBase.heatmap(
z = elevation,
x = X,
y = -Y,
name="",
showlegend=false,
colorscale = "Viridis",
showscale = true,
colorbar = attr(
title = attr(
text = "Intensity",
font = attr(
size = 14,
color = "black"
),
side = "right"
),
ticks = "outside",
ticklen = 2,
tickwidth = 0.5,
nticks = 5,
tickformat = ".2g"
)
)
plotdata = [trace]
plotlayout = layout
return plotdata, plotlayout, width, height
end
# loadContourPlot recieves the local directory of the image as a string,
# returns the layout and data for the contour plotly plot
# this function loads the image and applies a gaussian filter
# to smoothen it and loads it into a plot
function loadContourPlot(interfaceImg::String)
# Load the image
cleaned_img=replace(interfaceImg, r"\?.*" => "")
cleaned_img=lstrip(cleaned_img, '/')
var=joinpath("./public", cleaned_img)
img=load(var)
img_gray=Gray.(img)
img_array=Array(img_gray)
elevation=Float32.(Array(img_gray)) ./ 255.0 # Normalize between 0 and 1
# Smooth the image
sigma=3.0
kernel=Kernel.gaussian(sigma)
elevation_smoothed=imfilter(elevation, kernel)
# Create the X, Y meshgrid coordinates
x=1:size(elevation_smoothed, 2)
y=1:size(elevation_smoothed, 1)
X=repeat(reshape(x, 1, length(x)), length(y), 1)
Y=repeat(reshape(y, length(y), 1), 1, length(x))
layout=PlotlyBase.Layout(
title="2D Topographic Map",
xaxis=PlotlyBase.attr(
title="X",
scaleanchor="y"
),
yaxis=PlotlyBase.attr(
title="Y"
),
)
trace=PlotlyBase.contour(
z=elevation_smoothed,
x=X[1, :], # Use the first row
y=-Y[:, 1], # Use the first column
contours_coloring="Viridis",
colorscale="Viridis",
colorbar = attr(
tickformat = ".2g"
)
)
plotdata = [trace]
plotlayout = layout
return plotdata, plotlayout
end
# loadSurfacePlot recieves the local directory of the image as a string,
# returns the layout and data for the surface plotly plot
# this function loads the image and applies a gaussian filter
# to smoothen it and loads it into a 3D plot
function loadSurfacePlot(interfaceImg::String)
# Load the image
cleaned_img=replace(interfaceImg, r"\?.*" => "")
cleaned_img=lstrip(cleaned_img, '/')
var=joinpath("./public", cleaned_img)
img=load(var)
#println("Image type:", typeof(img))
img_gray=Gray.(img) # Convert to grayscale
#println("Grayscale image type:", typeof(img_gray))
img_array=Array(img_gray)
elevation=Float32.(Array(img_gray)) ./ 255.0 # Normalize between 0 and 1
#println("Elevation size:", size(elevation))
# Smooth the image
sigma=3.0
kernel=Kernel.gaussian(sigma)
#println(size(kernel))
elevation_smoothed=imfilter(elevation, kernel)
#println("Smoothed elevation size:", size(elevation_smoothed))
# Transpose the elevation_smoothed array
# Create the X, Y meshgrid coordinates
x=1:size(elevation_smoothed, 2)
y=1:size(elevation_smoothed, 1)
X=repeat(reshape(x, 1, length(x)), length(y), 1)
#println("Size of X:", size(X))
Y=repeat(reshape(y, length(y), 1), 1, length(x))
#println("Size of Y:", size(Y))
# Calculate the number of ticks and aspect ratio for the 3d plot
x_nticks=min(20, length(x))
y_nticks=min(20, length(y))
z_nticks=5
aspect_ratio=attr(x=1, y=length(y) / length(x), z=0.5)
# Define the layout for the 3D plot
layout3D=PlotlyBase.Layout(
title="3D Surface Plot",
scene=attr(
xaxis_nticks=x_nticks,
yaxis_nticks=y_nticks,
zaxis_nticks=z_nticks,
camera=attr(eye=attr(x=0, y=-1, z=0.5)),
aspectratio=aspect_ratio
)
)
if size(elevation_smoothed, 1) < size(elevation_smoothed, 2)
# Transpose the elevation_smoothed array if Y axis is longer than X axis to fix chopping
elevation_smoothed=transpose(elevation_smoothed)
Y=-Y
end
trace3D=PlotlyBase.surface(
x=X[1, :],
y=Y[:, 1],
z=elevation_smoothed,
contours_z=attr(
show=true,
usecolormap=true,
highlightcolor="limegreen",
project_z=true
),
colorscale="Viridis",
colorbar = attr(
tickformat = ".2g"
)
)
plotdata = [trace3D]
plotlayout = layout3D
return plotdata, plotlayout
end
function crossLinesPlot(x, y, maxwidth, maxheight)
# Define the coordinates for the two lines
l1_x = [0, maxwidth]
l1_y = [y, y]
l2_x = [x, x]
l2_y = [0, maxheight]
# Create the line traces
trace1 = PlotlyBase.scatter(x = l1_x, y = l1_y, mode = "lines",line=attr(color="red", width=0.5),name="Line X",showlegend=false)
trace2 = PlotlyBase.scatter(x = l2_x, y = l2_y, mode = "lines",line=attr(color="red", width=0.5),name="Line Y",showlegend=false)
return trace1, trace2
end
# == Reactive code ==
# reactive code to make the UI interactive
@app begin
# ==Reactive variables ==
# == Reactive variables ==
# reactive variables exist in both the Julia backend and the browser with two-way synchronization
# @out variables can only be modified by the backend
# @in variables can be modified by both the backend and the browser
@ -107,8 +305,8 @@ end
@out imgIntT="/.bmp" # image Interface TrIQ
@out colorbar="/.png"
@out colorbarT="/.png"
@out img_width=0
@out img_height=0
@out imgWidth=0
@out imgHeight=0
# Messages to interface variables
@out msg=""
@ -141,6 +339,22 @@ end
@out eTime=time()
## Plots
# Local image to plot
layoutImg = PlotlyBase.Layout(
xaxis = PlotlyBase.attr(
visible = false,
scaleanchor = "y"
),
yaxis = PlotlyBase.attr(
visible = false
)
)
traceImg=PlotlyBase.heatmap(x=[], y=[])
@out plotdataImg = [traceImg]
@out plotlayoutImg = layoutImg
# For triq image
@out plotdataImgT = [traceImg]
@out plotlayoutImgT = layoutImg
# Interface Plot Spectrum
layoutSpectra=PlotlyBase.Layout(
title="SUM Spectrum plot",
@ -216,7 +430,7 @@ end
@out plotdata3d=[trace3D]
@out plotlayout3d=layout3D
# ==Reactive handlers ==
# == Reactive handlers ==
# Reactive handlers watch a variable and execute a block of code when its value changes
# The onbutton handler will set the variable to false after the block is executed
@ -238,6 +452,8 @@ end
btnSpectraDisable=false
SpectraEnabled=true
end
xCoord=0
yCoord=0
end
end
@ -271,11 +487,12 @@ end
img=reverse(permutedims(img, (2, 1)), dims=1)
end
flipped_img=reverse(img, dims=1)
img_width=size(flipped_img, 2)
img_height=size(flipped_img, 1)
imgWidth=size(flipped_img, 2)
imgHeight=size(flipped_img, 1)
save(image_path, flipped_img)
# Use timestamp to refresh image interface container
imgIntT="/TrIQ_$(text_nmass).bmp?t=$(timestamp)"
plotdataImgT, plotlayoutImgT, imgWidth, imgHeight = loadImgPlot(imgIntT)
# Get current image
current_triq="TrIQ_$(text_nmass).bmp"
msgtriq="TrIQ image with the Nmass of $(replace(text_nmass, "_" => "."))"
@ -305,11 +522,12 @@ end
img=reverse(permutedims(img, (2, 1)), dims=1)
end
flipped_img=reverse(img, dims=1)
img_width=size(flipped_img, 2)
img_height=size(flipped_img, 1)
imgWidth=size(flipped_img, 2)
imgHeight=size(flipped_img, 1)
save(image_path, flipped_img)
# Use timestamp to refresh image interface container
imgInt="/MSI_$(text_nmass).bmp?t=$(timestamp)"
plotdataImg, plotlayoutImg, imgWidth, imgHeight = loadImgPlot(imgInt)
# Get current image
current_msi="MSI_$(text_nmass).bmp"
msgimg="Image with the Nmass of $(replace(text_nmass, "_" => "."))"
@ -466,15 +684,22 @@ end
new_msi=decrement_image(current_msi, msi_bmp)
new_col_msi=decrement_image(current_col_msi, col_msi_png)
current_msi=new_msi
current_col_msi=new_col_msi
imgInt="/$(current_msi)?t=$(timestamp)"
colorbar="/$(current_col_msi)?t=$(timestamp)"
if new_msi!=nothing || new_col_msi!=nothing
current_msi=new_msi
current_col_msi=new_col_msi
imgInt="/$(current_msi)?t=$(timestamp)"
colorbar="/$(current_col_msi)?t=$(timestamp)"
text_nmass=replace(current_msi, "MSI_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgimg="Image with the Nmass of $(replace(text_nmass, "_" => "."))"
text_nmass=replace(current_msi, "MSI_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgimg="Image with the Nmass of $(replace(text_nmass, "_" => "."))"
# Process the image in the function
plotdataImg, plotlayoutImg, imgWidth, imgHeight = loadImgPlot(imgInt)
else
traceImg=PlotlyBase.heatmap(x=[], y=[])
plotdataImg = [traceImg]
msgimg = ""
end
end
@onbutton imgPlus begin
# Append a query string to force the image to refresh
@ -485,53 +710,75 @@ end
new_msi=increment_image(current_msi, msi_bmp)
new_col_msi=increment_image(current_col_msi, col_msi_png)
if new_msi!=nothing || new_col_msi!=nothing
current_msi=new_msi
current_col_msi=new_col_msi
imgInt="/$(current_msi)?t=$(timestamp)"
colorbar="/$(current_col_msi)?t=$(timestamp)"
current_msi=new_msi
current_col_msi=new_col_msi
imgInt="/$(current_msi)?t=$(timestamp)"
colorbar="/$(current_col_msi)?t=$(timestamp)"
text_nmass=replace(current_msi, "MSI_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgimg="Image with the Nmass of $(replace(text_nmass, "_" => "."))"
text_nmass=replace(current_msi, "MSI_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgimg="Image with the Nmass of $(replace(text_nmass, "_" => "."))"
# Process the image in the function
plotdataImg, plotlayoutImg, imgWidth, imgHeight = loadImgPlot(imgInt)
else
traceImg=PlotlyBase.heatmap(x=[], y=[])
plotdataImg = [traceImg]
msgimg = ""
end
end
@onbutton imgMinusT begin
# Append a query string to force the image to refresh
timestamp=string(time_ns())
new_msi=decrement_image(current_triq, triq_bmp)
new_col_msi=decrement_image(current_col_triq, col_triq_png)
# Update the array of images with TrIQ filter listed in the public folder
triq_bmp=sort(filter(filename -> startswith(filename, "TrIQ_") && endswith(filename, ".bmp"), readdir("public")),lt=natural)
col_triq_png=sort(filter(filename -> startswith(filename, "colorbar_TrIQ_") && endswith(filename, ".png"), readdir("public")),lt=natural)
current_triq=new_msi
current_col_triq=new_col_msi
imgIntT="/$(current_triq)?t=$(timestamp)"
colorbarT="/$(current_col_triq)?t=$(timestamp)"
new_msi=decrement_image(current_triq, triq_bmp)
new_col_msi=decrement_image(current_col_triq, col_triq_png)
if new_msi!=nothing || new_col_msi!=nothing
current_triq=new_msi
current_col_triq=new_col_msi
imgIntT="/$(current_triq)?t=$(timestamp)"
colorbarT="/$(current_col_triq)?t=$(timestamp)"
text_nmass=replace(current_triq, "TrIQ_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgtriq="TrIQ image with the Nmass of $(replace(text_nmass, "_" => "."))"
text_nmass=replace(current_triq, "TrIQ_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgtriq="TrIQ image with the Nmass of $(replace(text_nmass, "_" => "."))"
# Process the image in the function
plotdataImgT, plotlayoutImgT, imgWidth, imgHeight = loadImgPlot(imgIntT)
else
traceImg=PlotlyBase.heatmap(x=[], y=[])
plotdataImgT = [traceImg]
msgtriq = ""
end
end
@onbutton imgPlusT begin
# Append a query string to force the image to refresh
timestamp=string(time_ns())
new_msi=increment_image(current_triq, triq_bmp)
new_col_msi=increment_image(current_col_triq, col_triq_png)
# Update the array of images with TrIQ filter listed in the public folder
triq_bmp=sort(filter(filename -> startswith(filename, "TrIQ_") && endswith(filename, ".bmp"), readdir("public")),lt=natural)
col_triq_png=sort(filter(filename -> startswith(filename, "colorbar_TrIQ_") && endswith(filename, ".png"), readdir("public")),lt=natural)
current_triq=new_msi
current_col_triq=new_col_msi
imgIntT="/$(current_triq)?t=$(timestamp)"
colorbarT="/$(current_col_triq)?t=$(timestamp)"
text_nmass=replace(current_triq, "TrIQ_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgtriq="TrIQ image with the Nmass of $(replace(text_nmass, "_" => "."))"
new_msi=increment_image(current_triq, triq_bmp)
new_col_msi=increment_image(current_col_triq, col_triq_png)
if new_msi!=nothing || new_col_msi!=nothing
current_triq=new_msi
current_col_triq=new_col_msi
imgIntT="/$(current_triq)?t=$(timestamp)"
colorbarT="/$(current_col_triq)?t=$(timestamp)"
text_nmass=replace(current_triq, "TrIQ_" => "")
text_nmass=replace(text_nmass, ".bmp" => "")
msgtriq="TrIQ image with the Nmass of $(replace(text_nmass, "_" => "."))"
# Process the image in the function
plotdataImgT, plotlayoutImgT, imgWidth, imgHeight = loadImgPlot(imgIntT)
else
traceImg=PlotlyBase.heatmap(x=[], y=[])
plotdataImgT = [traceImg]
msgtriq = ""
end
end
# 3d plot
@ -548,59 +795,7 @@ end
btnStartDisable=true
btnSpectraDisable=true
try
img=load(var)
#println("Image type:", typeof(img))
img_gray=Gray.(img) # Convert to grayscale
#println("Grayscale image type:", typeof(img_gray))
img_array=Array(img_gray)
elevation=Float32.(Array(img_gray)) ./ 255.0 # Normalize between 0 and 1
#println("Elevation size:", size(elevation))
# Smooth the image
sigma=3.0
kernel=Kernel.gaussian(sigma)
#println(size(kernel))
elevation_smoothed=imfilter(elevation, kernel)
#println("Smoothed elevation size:", size(elevation_smoothed))
# Transpose the elevation_smoothed array
# Create the X, Y meshgrid coordinates
x=1:size(elevation_smoothed, 2)
y=1:size(elevation_smoothed, 1)
X=repeat(reshape(x, 1, length(x)), length(y), 1)
#println("Size of X:", size(X))
Y=repeat(reshape(y, length(y), 1), 1, length(x))
#println("Size of Y:", size(Y))
# Calculate the number of ticks and aspect ratio for the 3d plot
x_nticks=min(20, length(x))
y_nticks=min(20, length(y))
z_nticks=5
aspect_ratio=attr(x=1, y=length(y) / length(x), z=0.5)
# Define the layout for the 3D plot
layout3D=PlotlyBase.Layout(
title="3D Surface Plot",
scene=attr(
xaxis_nticks=x_nticks,
yaxis_nticks=y_nticks,
zaxis_nticks=z_nticks,
camera=attr(eye=attr(x=0, y=-1, z=0.5)),
aspectratio=aspect_ratio
)
)
if size(elevation_smoothed, 1) < size(elevation_smoothed, 2)
# Transpose the elevation_smoothed array if Y axis is longer than X axis to fix chopping
elevation_smoothed=transpose(elevation_smoothed)
Y=-Y
end
trace3D=PlotlyBase.surface(x=X[1, :], y=Y[:, 1], z=elevation_smoothed,
contours_z=attr(
show=true,
usecolormap=true,
highlightcolor="limegreen",
project_z=true
), colorscale="Viridis")
plotdata3d=[trace3D] # We add the data from the image to the plot
plotlayout3d=layout3D # we update the style of the plot to fit the image.
plotdata3d, plotlayout3d = loadSurfacePlot(imgInt)
GC.gc() # Trigger garbage collection
if Sys.islinux()
ccall(:malloc_trim, Int32, (Int32,), 0) # Ensure julia returns the freed memory to OS
@ -641,53 +836,7 @@ end
btnStartDisable=true
btnSpectraDisable=true
try
img=load(var)
img_gray=Gray.(img) # Convert to grayscale
img_array=Array(img_gray)
elevation=Float32.(Array(img_gray)) ./ 255.0 # Normalize between 0 and 1
# Smooth the image
sigma=3.0
kernel=Kernel.gaussian(sigma)
elevation_smoothed=imfilter(elevation, kernel)
# Create the X, Y meshgrid coordinates
x=1:size(elevation_smoothed, 2)
y=1:size(elevation_smoothed, 1)
X=repeat(reshape(x, 1, length(x)), length(y), 1)
Y=repeat(reshape(y, length(y), 1), 1, length(x))
# Calculate the number of ticks and aspect ratio for the 3d plot
x_nticks=min(20, length(x))
y_nticks=min(20, length(y))
z_nticks=5
aspect_ratio=attr(x=1, y=length(y) / length(x), z=0.5)
# Define the layout for the 3D plot
layout3D=PlotlyBase.Layout(
title="3D Surface Plot",
scene=attr(
xaxis_nticks=x_nticks,
yaxis_nticks=y_nticks,
zaxis_nticks=z_nticks,
camera=attr(eye=attr(x=0, y=-1, z=0.5)),
aspectratio=aspect_ratio
)
)
if size(elevation_smoothed, 1) < size(elevation_smoothed, 2)
# Transpose the elevation_smoothed array if Y axis is longer than X axis to fix chopping
elevation_smoothed=transpose(elevation_smoothed)
Y=-Y
end
trace3D=PlotlyBase.surface(x=X[1, :], y=Y[:, 1], z=elevation_smoothed,
contours_z=attr(
show=true,
usecolormap=true,
highlightcolor="limegreen",
project_z=true
), colorscale="Viridis")
plotdata3d=[trace3D] # We add the data from the image to the plot
plotlayout3d=layout3D # we update the style of the plot to fit the image.
plotdata3d, plotlayout3d = loadSurfacePlot(imgIntT)
GC.gc() # Trigger garbage collection
if Sys.islinux()
ccall(:malloc_trim, Int32, (Int32,), 0) # Ensure julia returns the freed memory to OS
@ -730,41 +879,7 @@ end
btnSpectraDisable=true
try
img=load(var)
# Convert to grayscale
img_gray=Gray.(img)
img_array=Array(img_gray)
elevation=Float32.(Array(img_gray)) ./ 255.0 # Normalize between 0 and 1
# Smooth the image
sigma=3.0
kernel=Kernel.gaussian(sigma)
elevation_smoothed=imfilter(elevation, kernel)
# Create the X, Y meshgrid coordinates
x=1:size(elevation_smoothed, 2)
y=1:size(elevation_smoothed, 1)
X=repeat(reshape(x, 1, length(x)), length(y), 1)
Y=repeat(reshape(y, length(y), 1), 1, length(x))
layoutContour=PlotlyBase.Layout(
title="2D Topographic Map",
xaxis=PlotlyBase.attr(
title="X",
scaleanchor="y"
),
yaxis=PlotlyBase.attr(
title="Y"
),
)
traceContour=PlotlyBase.contour(
z=elevation_smoothed,
x=X[1, :], # Use the first row
y=-Y[:, 1], # Use the first column
contours_coloring="Viridis",
colorscale="Viridis"
)
plotdataC=[traceContour]
plotlayoutC=layoutContour
plotdataC,plotlayoutC=loadContourPlot(imgInt)
GC.gc() # Trigger garbage collection
if Sys.islinux()
ccall(:malloc_trim, Int32, (Int32,), 0) # Ensure Julia returns the freed memory to OS
@ -806,41 +921,7 @@ end
btnSpectraDisable=true
try
img=load(var)
# Convert to grayscale
img_gray=Gray.(img)
img_array=Array(img_gray)
elevation=Float32.(Array(img_gray)) ./ 255.0 # Normalize between 0 and 1
# Smooth the image
sigma=3.0
kernel=Kernel.gaussian(sigma)
elevation_smoothed=imfilter(elevation, kernel)
# Create the X, Y meshgrid coordinates
x=1:size(elevation_smoothed, 2)
y=1:size(elevation_smoothed, 1)
X=repeat(reshape(x, 1, length(x)), length(y), 1)
Y=repeat(reshape(y, length(y), 1), 1, length(x))
layoutContour=PlotlyBase.Layout(
title="2D Topographic Map",
xaxis=PlotlyBase.attr(
title="X",
scaleanchor="y"
),
yaxis=PlotlyBase.attr(
title="Y"
),
)
traceContour=PlotlyBase.contour(
z=elevation_smoothed,
x=X[1, :], # Use the first row
y=-Y[:, 1], # Use the first column
contours_coloring="Viridis",
colorscale="Viridis"
)
plotdataC=[traceContour]
plotlayoutC=layoutContour
plotdataC,plotlayoutC=loadContourPlot(imgIntT)
GC.gc() # Trigger garbage collection
if Sys.islinux()
ccall(:malloc_trim, Int32, (Int32,), 0) # Ensure Julia returns the freed memory to OS
@ -877,50 +958,90 @@ end
# Event detection for clicking on the spectrum plot
@onchange data_click begin
if !isempty(xSpectraMz)
#println("Clicked data on sum spectrum plot : ", data_click)
spectracoords=reshape(plotdata, 1, length(plotdata))
#println("Spectra: $(ndims(spectracoords))")
# Extract x and y values from data_click
cursor_data=data_click["cursor"]
x_value = cursor_data["x"]
y_value = cursor_data["y"] # Get the x and y values from the click of the cursor
closest_distance = Inf
for val in spectracoords
# Find the index where x is within a range
start_idx = findfirst(x -> x >= x_value - 10, val[:x])
end_idx = findlast(x -> x <= x_value + 10, val[:x])
if selectedTab == "tab2"
if !isempty(xSpectraMz)
#println("Clicked data on sum spectrum plot : ", data_click)
spectracoords=reshape(plotdata, 1, length(plotdata))
#println("Spectra: $(ndims(spectracoords))")
# Extract x and y values from data_click
cursor_data=data_click["cursor"]
x_value = cursor_data["x"]
y_value = cursor_data["y"] # Get the x and y values from the click of the cursor
closest_distance = Inf
# Ensure the index are valid and within range
if start_idx !== nothing && end_idx !== nothing
for i in start_idx:end_idx
spectra_x = val[:x][i]
spectra_y = val[:y][i]
distance = sqrt((spectra_x - x_value)^2 + (spectra_y - y_value)^2) # Calculate distance
if distance < closest_distance
closest_distance = distance
Nmass = round(spectra_x, digits=2)
for val in spectracoords
# Find the index where x is within a range
start_idx = findfirst(x -> x >= x_value - 10, val[:x])
end_idx = findlast(x -> x <= x_value + 10, val[:x])
# Ensure the index are valid and within range
if start_idx !== nothing && end_idx !== nothing
for i in start_idx:end_idx
spectra_x = val[:x][i]
spectra_y = val[:y][i]
distance = sqrt((spectra_x - x_value)^2 + (spectra_y - y_value)^2) # Calculate distance
if distance < closest_distance
closest_distance = distance
Nmass = round(spectra_x, digits=2)
end
end
end
end
layoutSpectra=PlotlyBase.Layout(
title="SUM Spectrum plot",
xaxis=PlotlyBase.attr(
title="<i>m/z</i>",
showgrid=true
),
yaxis=PlotlyBase.attr(
title="Intensity",
showgrid=true
),
autosize=false
)
traceSpectra=PlotlyBase.scatter(x=xSpectraMz, y=ySpectraMz, mode="lines",name="Spectra",showlegend=false)
trace2=PlotlyBase.scatter(x=[Nmass, Nmass],y=[0, maximum(ySpectraMz)],mode="lines",line=attr(color="red", width=0.5),name="<i>m/z</i> selected",showlegend=false)
plotdata=[traceSpectra,trace2] # We add the data from spectra and the red line to the plot
plotlayout=layoutSpectra
end
layoutSpectra=PlotlyBase.Layout(
title="SUM Spectrum plot",
xaxis=PlotlyBase.attr(
title="<i>m/z</i>",
showgrid=true
),
yaxis=PlotlyBase.attr(
title="Intensity",
showgrid=true
),
autosize=false
)
traceSpectra=PlotlyBase.scatter(x=xSpectraMz, y=ySpectraMz, mode="lines",name="Spectra",showlegend=false)
trace2=PlotlyBase.scatter(x=[Nmass, Nmass],y=[0, maximum(ySpectraMz)],mode="lines",line=attr(color="red", width=0.5),name="<i>m/z</i> selected",showlegend=false)
plotdata=[traceSpectra,trace2] # We add the data from spectra and the red line to the plot
plotlayout=layoutSpectra
elseif selectedTab == "tab1"
#println("you have clicked the triq image")
cursor_data=data_click["cursor"]
xCoord = Int32(round(cursor_data["x"]))
if xCoord < 0
xCoord = 0
elseif xCoord > imgWidth
xCoord = imgWidth
end
yCoord = Int32(round(cursor_data["y"]))
if yCoord > 0
yCoord = 0
elseif yCoord < -imgHeight
yCoord = -imgHeight
end # Get the x and y values from the click of the cursor and make sure they don't exceed image proportions
#plotdataImgT, plotlayoutImgT, imgWidth, imgHeight = loadImgPlot(imgIntT)
plotdataImgT = filter(trace -> !(get(trace, :name, "") in ["Line X", "Line Y"]), plotdataImgT)
trace1, trace2 = crossLinesPlot(xCoord, yCoord, imgWidth, -imgHeight)
plotdataImgT=append!(plotdataImgT, [trace1, trace2])
elseif selectedTab == "tab0"
#println("you have clicked the normal image")
cursor_data=data_click["cursor"]
xCoord = Int32(round(cursor_data["x"]))
if xCoord < 0
xCoord = 0
elseif xCoord > imgWidth
xCoord = imgWidth
end
yCoord = Int32(round(cursor_data["y"]))
if yCoord > 0
yCoord = 0
elseif yCoord < -imgHeight
yCoord = -imgHeight
end # Get the x and y values from the click of the cursor and make sure they don't exceed image proportions
#plotdataImg, plotlayoutImg, imgWidth, imgHeight = loadImgPlot(imgInt)
plotdataImg = filter(trace -> !(get(trace, :name, "") in ["Line X", "Line Y"]), plotdataImg)
trace1, trace2 = crossLinesPlot(xCoord, yCoord, imgWidth, -imgHeight)
plotdataImg=append!(plotdataImg, [trace1, trace2])
end
end
@ -934,12 +1055,12 @@ end
ccall(:malloc_trim, Int32, (Int32,), 0) # Ensure julia returns the freed memory to OS
end
end
# ==Pages ==
# == Pages ==
# Register a new route and the page that will be loaded on access
@page("/", "app.jl.html")
end
# ==Advanced features ==
# == Advanced features ==
#=
- The @private macro defines a reactive variable that is not sent to the browser.
This is useful for storing data that is unique to each user session but is not needed

17
app.jl.html
View File

@ -160,7 +160,8 @@
<!-- Image manager -->
<div id="image-container" class="row st-col col-12">
<div class="col-10">
<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgInt" width="80%"></q-img>
<plotly id="plotStyle" :data="plotdataImg" :layout="plotlayoutImg" class="q-pa-none q-ma-none sync_data" @click="data_click"></plotly>
<!--<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgInt" width="80%"></q-img>-->
</div>
<div class="col-2">
<q-img id="colorbar" class="q-ma-none q-pa-none" :src="colorbar"></q-img>
@ -180,7 +181,8 @@
<!-- Triq Image manager -->
<div id="image-container" class="row st-col col-12">
<div class="col-10">
<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgIntT" width="80%"></q-img>
<plotly id="plotStyle" :data="plotdataImgT" :layout="plotlayoutImgT" class="q-pa-none q-ma-none sync_data" @click="data_click"></plotly>
<!--<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgIntT" width="80%"></q-img>-->
</div>
<div class="col-2">
<q-img id="colorbar" class="q-ma-none q-pa-none" :src="colorbarT"></q-img>
@ -192,8 +194,7 @@
<q-tab-panel name="tab2">
<!-- Content for Tab 2 -->
<!--<plotly id="plotStyle" :data="plotdata" :layout="plotlayout" class="q-pa-none q-ma-none"></plotly>-->
<plotly id="plotStyle" :data="plotdata" :layout="plotlayout" @click="data_click"
class="q-pa-none q-ma-none sync_data"></plotly>
<plotly id="plotStyle" :data="plotdata" :layout="plotlayout" class="q-pa-none q-ma-none sync_data" @click="data_click"></plotly>
</q-tab-panel>
<q-tab-panel name="tab3">
@ -246,7 +247,7 @@
<!-- Image manager -->
<div id="image-container" class="row st-col col-12">
<div class="st-col col-10">
<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgInt" width="80%"></q-img>
<plotly id="plotStyle" :data="plotdataImg" :layout="plotlayoutImg" class="q-pa-none q-ma-none"></plotly>
</div>
<div class="st-col col-2">
<q-img id="colorbar" class="q-ma-none q-pa-none" :src="colorbar"></q-img>
@ -265,7 +266,7 @@
<!-- Triq Image manager -->
<div id="image-container" class="row st-col col-12">
<div class="col-10">
<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgIntT" width="80%"></q-img>
<plotly id="plotStyle" :data="plotdataImgT" :layout="plotlayoutImgT" class="q-pa-none q-ma-none"></plotly>
</div>
<div class="col-2">
<q-img id="colorbar" class="q-ma-none q-pa-none" :src="colorbarT"></q-img>
@ -301,7 +302,7 @@
<!-- Image manager -->
<div id="image-container" class="row st-col col-12">
<div class="st-col col-10">
<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgInt" width="80%"></q-img>
<plotly id="plotStyle" :data="plotdataImg" :layout="plotlayoutImg" class="q-pa-none q-ma-none"></plotly>
</div>
<div class="st-col col-2">
<q-img id="colorbar" class="q-ma-none q-pa-none" :src="colorbar"></q-img>
@ -320,7 +321,7 @@
<!-- Triq Image manager -->
<div id="image-container" class="row st-col col-12">
<div class="col-10">
<q-img id="imgInt" class="q-ma-none q-pa-none" :src="imgIntT" width="80%"></q-img>
<plotly id="plotStyle" :data="plotdataImgT" :layout="plotlayoutImgT" class="q-pa-none q-ma-none"></plotly>
</div>
<div class="col-2">
<q-img id="colorbar" class="q-ma-none q-pa-none" :src="colorbarT"></q-img>

4
ongoing_tasks.txt
View File

@ -1,9 +1,8 @@
PENDING
Rmsi & julia coherence with image creation and colorbar
colorbar revamp
colorbar revamp CURRENTLY ONGOING
Create function that makes the imzML from mzML files ?
Possibility to add multiple imzML to process at once ?
Per pixel of image plot creation for spectra
Add comparison image (rotate, transform, translate, transparency) CURRENTLY ONGOING
DONE
@ -25,3 +24,4 @@ DONE
Comparative for two views
Even faster initial boot and subsectuential boot
Multiple spectra plot types
Plot creation for spectra Per pixel of image

2
start_MSI_GUI.jl
View File

@ -37,6 +37,8 @@ Genie.loadapp()
@async run(`xdg-open $url`) # For Linux
elseif Sys.iswindows()
@async run(`start $url`) # For Windows
@async run(`explorer $url`)
@async run(`Start-Process $url`) # For Windows
end
end