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== Visualization on Onyx == | |||
See [[Lab visualization tutorial]] for a basic tutorial on running ParaView on Onyx. | |||
=== Accessing Networked Drives === | |||
As of April 2018, only the NAS is accessible from Onyx. It is generally available as the Z drive, but may need to be mounted the first time. There is a sticky-note on the computer giving instructions on how to do this. This will only need to be done once. | |||
=== Paraview === | |||
To start a parallel session of ParaView, open Command Prompt and run the command: | |||
mpiexec -np N "C:\Program Files\ParaView 5.5.0-RC3-Qt5-MPI-Windows-64bit\bin\pvserver" | |||
where N is the number of cores to use. Onyx has 6 cores (12 with hyper-threading) available to be run, so don't ask for more than 12. Remember that the resources are shared so check how many processors are available before running. | |||
=== VisIt === | |||
To run a parallel session of VisIt, find VisIt in the Start Menu (for non-Windows people, the thing in the bottom left corner) and find VisIt 2.13.1 and choose VisIt Parallel. | |||
== Visualization on Graham == | == Visualization on Graham == | ||
Line 14: | Line 34: | ||
=== VisIt === | === VisIt === | ||
'''Note:''' as of | '''Note:''' as of July 2018: | ||
* you must use VisIt 2.13 | * you must use VisIt 2.13 | ||
* it is unclear how to take advantage of GPU accelerations | * it is unclear how to take advantage of GPU accelerations | ||
* | * parallel VisIt is now available (unofficially) | ||
More information can be gathered at [[VisIt]]. | More information can be gathered at [[VisIt]]. | ||
==== Host | ==== Setting up for Remote VisIt ==== | ||
# Download the host profile from [https://wiki.math.uwaterloo.ca/sheets/FluidsWiki/Visualization/VisIt/host_test.xml here]. | |||
# Put <code>host_file.xml</code> in <code>~/.visit/hosts</code> on your local machine | |||
#* Modify line 42 as appropriate to your user profile | |||
==== Starting a Remote VisIt Session ==== | |||
# Run VisIt 2.13 on your local machine | |||
# Choose <code>Open</code> and under <code>Host</code> choose <code>Graham</code> | |||
#* You will need to wait a minute or so while it connects | |||
# The Directories and Files panels should now show your home directory on Graham | |||
#* Navigate through to locate the files you wish to visualize | |||
# After selecting the files and choosing <code>OK</code>, you will be prompted to request processors | |||
#* This will submit a salloc request to get processors for your VisIt session | |||
#* Choose the <code>slurm</code> profile option (should be default) and request the number of processors / time that is appropriate for your purposes | |||
#* You'll need to wait again until the salloc request is allocated. | |||
#** As with any salloc request, the more you request, the longer you'll have to wait | |||
# Proceed to use VisIt as usual. | |||
#* Saving movies or frames will output the files on your local machine | |||
#* Be aware that the session will die '''without warning''' when you reach the time limit for your session, '''so save often!''' | |||
===== Specifying Start Times ===== | |||
If you want/need to request a large number of processors for your VisIt session, you may find that you need to wait a while. | |||
This can be troublesome since you won't really know when the session will start (although you can [[Graham Tips#Check Job Status and Nodes Usage|check the status on the job on Graham]]). | |||
You can, however, specify a requested start time for a session. | |||
For example, if you want to run a large visualization job, you could submit the request on Tuesday to have the job start Wednesday morning. That way when you get in on Wednesday you don't have to wait for the connection, since your job will have be gaining priority overnight. | |||
To specify a start time, you can use the <syntaxhighlight lang="bash" inline>--begin=YYYY-MM-DDTHH:MM:SS</syntaxhighlight> flag for salloc (as in [[Graham Tips#Interactive Jobs]]). | |||
Use the following steps to set this flag in VisIt. | |||
# go to <code>Options -> Host profiles</code> | |||
# choose <code>Graham</code> from the list of hosts | |||
# <code>Launch Profiles -> Parallel -> Advanced</code> | |||
# Add the appropriate <syntaxhighlight lang="bash" inline>begin</syntaxhighlight> flag to <code>Launcher Arguments</code> | |||
# Select <code>Apply</code> | |||
===== Increasing available memory ===== | ===== Increasing available memory ===== | ||
The host profile provided defaults to 2G per processor. | |||
<code>Launch Profiles -> Parallel -> Advanced</code> | If you require more memory, you can | ||
<code> | # go to <code>Options -> Host profiles</code> | ||
# choose <code>Graham</code> from the list of hosts | |||
# <code>Launch Profiles -> Parallel -> Advanced</code> | |||
# Set the desired memory per processor via the <code>mem-per-cpu</code> flag (if unset, defaults to 256M) | |||
# Select <code>Apply</code> | |||
# (Optional) to set the new value as the default, use <code>Options -> Save Settings</code> | |||
=== Paraview === | === Paraview === | ||
Line 37: | Line 97: | ||
More information can be gathered at [[ParaView]]. | More information can be gathered at [[ParaView]]. | ||
To submit a paraview job to the slurm scheduler use the following submission script. This will run the python script script.py which must contain all relevant lines of code (read file, create contours/volume plot, adjust color scheme, save screenshot, etc.). No interaction with this job is possible. | |||
<syntaxhighlight lang="bash"> | |||
#!/bin/bash | |||
# bash script for submitting a Paraview job to the sharcnet Graham queue | |||
#SBATCH --ntasks=4 # number of MPI processes | |||
#SBATCH --mem-per-cpu=32G # memory per processor (default in Mb) | |||
#SBATCH --time=00-04:00:00 # time (DD-HH:MM:SS) | |||
#SBATCH --job-name="paraview" # job name | |||
##SBATCH —dependency=afterok:<jobid> # Wait for job to complete | |||
#SBATCH --output=para-%j.log # log file | |||
#SBATCH --error=para-%j.err # error file | |||
#SBATCH --mail-user=ddeepwel@uwaterloo.ca # who to email | |||
#SBATCH --mail-type=FAIL # when to email | |||
#SBATCH --account=ctb-mmstastn # UW Fluids designated resource allocation | |||
module load paraview-offscreen | |||
mpirun pvbatch script.py | |||
</syntaxhighlight> | |||
== Mapped netcdf SPINS file == | == Mapped netcdf SPINS file == | ||
Line 43: | Line 125: | ||
=== ParaView === | === ParaView === | ||
* Read in netcdf file and | * Read in netcdf file (choose "NetCDF files generic and CF conventions") | ||
* Unselect the checkbox for Spherical Coordinates (this seems to only sometimes be necessary) | * Unselect the checkbox for Spherical Coordinates (this seems to only sometimes be necessary) | ||
* Select the Output Type: Structured | |||
* Click Apply | * Click Apply | ||
* In the Pipeline, select the file just opened and apply the calculator filter to it (either select the calculator icon, or under Tools->Common in menu bar) | * In the Pipeline, select the file just opened and apply the calculator filter to it (either select the calculator icon, or under Tools->Common in menu bar) | ||
Line 69: | Line 152: | ||
** Click Apply in the Displace operator attributes window | ** Click Apply in the Displace operator attributes window | ||
* Click Draw in the main menu | * Click Draw in the main menu | ||
== 3D Printing == | |||
Thanks to the marvels of technology, it's not only possibly for you to 3D-print iso-surfaces from your simulations, it's actually fairly straight-forward! | |||
<3d file="https://wiki.math.uwaterloo.ca/fluidswiki/images/d/d8/stl_test.stl" scale="1.2" z="0" width="500" height="300" norotate="true" color="0x1F618D"></3d> | |||
[[File:3D print GravCurr 1.jpg|right|thumb|<big>3D print of lobe-cleft instability forming in a gravity current.</big>]] | |||
=== Create ''.stl'' for the Iso-surface === | |||
For VisIt | |||
* <code>File -> Export Databases</code> | |||
* Choose ''STL'' under <code>Export to</code> | |||
* Under <code>Add variable</code> choose the appropriate variable to export | |||
* Choose <code>Export</code> and select <code>Binary</code> in the pop-up window. | |||
For ParaView | |||
* File -> Save Data -> Choose STL from the filetype | |||
* Choose Binary instead of Ascii | |||
=== Scaling and Thickening === | |||
Iso-surfaces produced with the above method will have zero thickness, which causes problems for printing. | |||
You will also likely need / want to scale the dimensions of your stl image to fit the dimensions of the 3D printer. | |||
The following python script uses [https://www.blender.org Blender] to scale and thicken the image. | |||
You will need to have Blender installed on your machine for this to work. | |||
To run the script, you can call Blender from the command line via: | |||
<syntaxhighlight lang="bash" inline> /Applications/Blender/blender.app/Contents/MacOS/blender --background --python scale_and_thicken.py </syntaxhighlight> | |||
, where ''scale_and_thicken.py'' is the python script included below. | |||
Depending on where you installed it, you may need to change the path to the executable. | |||
* You will also need to modify lines 3 and 4 to specify your filenames. | |||
* You can change the thickness by modifying line 31 (current default is roughly the minimum printable thickness) | |||
* This procedure can produce some very large file sizes. One option to reduce file size is to apply a decimate modifier (lines 34-35). The setting in line 35 specifies the proportion of vertices/faces that should ''remain''. So setting the ratio to 0.1 would reduce the file size by a factor of 10. What level of decimation can be applied before significant loss of quality is heavily context dependent, so play around with it. | |||
* Depending on the nature of the shape, it may be easiest to print it on its side. To rotate the object, uncomment line 38 and specify the appropriate 'up' axis. | |||
'''Note that the produced file has dimensions in mm.''' | |||
==== scale_and_thicken.py ==== | |||
<syntaxhighlight lang="python" line highlight="3,4,31,35,38"> | |||
import bpy | |||
in_path = "/Users/bastorer/Desktop/test.stl" | |||
out_path = "/Users/bastorer/Desktop/out.stl" | |||
# Delete all objects | |||
bpy.ops.object.delete() | |||
# Import object | |||
bpy.ops.import_mesh.stl(filepath = in_path) | |||
obj = bpy.context.visible_objects[0].name | |||
print("Modifying <" + obj + "> object") | |||
# Rescale to fit in box | |||
# with mm dimensions | |||
# 406.4 x 355.6 x 406.4 | |||
dims = bpy.data.objects[obj].dimensions | |||
scale_x = 400. / dims[0] | |||
scale_y = 350. / dims[1] | |||
scale_z = 400. / dims[2] | |||
scale = min(scale_x, scale_y, scale_z) | |||
bpy.data.objects[obj].scale[0] = scale | |||
bpy.data.objects[obj].scale[1] = scale | |||
bpy.data.objects[obj].scale[2] = scale | |||
# Add thickness to the object | |||
bpy.ops.object.modifier_add(type = 'SOLIDIFY') | |||
bpy.context.object.modifiers["Solidify"].thickness = 2./scale | |||
# Decimate to reduce file size | |||
bpy.ops.object.modifier_add(type = 'DECIMATE') | |||
bpy.context.object.modifiers["Decimate"].ratio = 1.0 | |||
# Rotate the object (if desired) | |||
#bpy.data.objects[obj].up_axis = 'Y' | |||
# Export mesh | |||
bpy.ops.export_mesh.stl(filepath = out_path) | |||
</syntaxhighlight> |
Latest revision as of 12:11, 11 October 2018
Visualization on Onyx
See Lab visualization tutorial for a basic tutorial on running ParaView on Onyx.
Accessing Networked Drives
As of April 2018, only the NAS is accessible from Onyx. It is generally available as the Z drive, but may need to be mounted the first time. There is a sticky-note on the computer giving instructions on how to do this. This will only need to be done once.
Paraview
To start a parallel session of ParaView, open Command Prompt and run the command:
mpiexec -np N "C:\Program Files\ParaView 5.5.0-RC3-Qt5-MPI-Windows-64bit\bin\pvserver"
where N is the number of cores to use. Onyx has 6 cores (12 with hyper-threading) available to be run, so don't ask for more than 12. Remember that the resources are shared so check how many processors are available before running.
VisIt
To run a parallel session of VisIt, find VisIt in the Start Menu (for non-Windows people, the thing in the bottom left corner) and find VisIt 2.13.1 and choose VisIt Parallel.
Visualization on Graham
All of what you need to know about running Paraview or VisIt on Graham is presented in Graham Visualization.
The general idea is that you run / interact with VisIt/Paraview on your local machine, while have the computing done on Graham. This provides the advantages of:
- not needing to transfer many and/or large data files to your local machine
- running VisIt/ParaView on many processors with a large amount of available memory.
The link above provides a fairly thorough guide to getting up-and-running, just remember to replace cedar with graham where appropriate.
Keep in mind that the requested processors go through a slurm allocation (salloc), and so the more processors that you request, the longer that you will have to wait before receiving the allocation.
VisIt
Note: as of July 2018:
- you must use VisIt 2.13
- it is unclear how to take advantage of GPU accelerations
- parallel VisIt is now available (unofficially)
More information can be gathered at VisIt.
Setting up for Remote VisIt
- Download the host profile from here.
- Put
host_file.xml
in~/.visit/hosts
on your local machine- Modify line 42 as appropriate to your user profile
Starting a Remote VisIt Session
- Run VisIt 2.13 on your local machine
- Choose
Open
and underHost
chooseGraham
- You will need to wait a minute or so while it connects
- The Directories and Files panels should now show your home directory on Graham
- Navigate through to locate the files you wish to visualize
- After selecting the files and choosing
OK
, you will be prompted to request processors- This will submit a salloc request to get processors for your VisIt session
- Choose the
slurm
profile option (should be default) and request the number of processors / time that is appropriate for your purposes - You'll need to wait again until the salloc request is allocated.
- As with any salloc request, the more you request, the longer you'll have to wait
- Proceed to use VisIt as usual.
- Saving movies or frames will output the files on your local machine
- Be aware that the session will die without warning when you reach the time limit for your session, so save often!
Specifying Start Times
If you want/need to request a large number of processors for your VisIt session, you may find that you need to wait a while. This can be troublesome since you won't really know when the session will start (although you can check the status on the job on Graham).
You can, however, specify a requested start time for a session. For example, if you want to run a large visualization job, you could submit the request on Tuesday to have the job start Wednesday morning. That way when you get in on Wednesday you don't have to wait for the connection, since your job will have be gaining priority overnight.
To specify a start time, you can use the --begin=YYYY-MM-DDTHH:MM:SS
flag for salloc (as in Graham Tips#Interactive Jobs).
Use the following steps to set this flag in VisIt.
- go to
Options -> Host profiles
- choose
Graham
from the list of hosts Launch Profiles -> Parallel -> Advanced
- Add the appropriate
begin
flag toLauncher Arguments
- Select
Apply
Increasing available memory
The host profile provided defaults to 2G per processor. If you require more memory, you can
- go to
Options -> Host profiles
- choose
Graham
from the list of hosts Launch Profiles -> Parallel -> Advanced
- Set the desired memory per processor via the
mem-per-cpu
flag (if unset, defaults to 256M) - Select
Apply
- (Optional) to set the new value as the default, use
Options -> Save Settings
Paraview
Note: as of Jan 2018:
- you must use ParaView 5.3.0 when using CPU-based computation on Graham
- you must use ParaView 5.4.0 when using GPU-based computation on Graham
See the Compute Canada Visualization page for further updates and details.
More information can be gathered at ParaView.
To submit a paraview job to the slurm scheduler use the following submission script. This will run the python script script.py which must contain all relevant lines of code (read file, create contours/volume plot, adjust color scheme, save screenshot, etc.). No interaction with this job is possible.
#!/bin/bash
# bash script for submitting a Paraview job to the sharcnet Graham queue
#SBATCH --ntasks=4 # number of MPI processes
#SBATCH --mem-per-cpu=32G # memory per processor (default in Mb)
#SBATCH --time=00-04:00:00 # time (DD-HH:MM:SS)
#SBATCH --job-name="paraview" # job name
##SBATCH —dependency=afterok:<jobid> # Wait for job to complete
#SBATCH --output=para-%j.log # log file
#SBATCH --error=para-%j.err # error file
#SBATCH --mail-user=ddeepwel@uwaterloo.ca # who to email
#SBATCH --mail-type=FAIL # when to email
#SBATCH --account=ctb-mmstastn # UW Fluids designated resource allocation
module load paraview-offscreen
mpirun pvbatch script.py
Mapped netcdf SPINS file
Netcdf files need their data be represented on a rectilinear grid. Mapped (curvilinear) coordinates are accomplished by writing additional fields to which a visualization software can later designate as the correct grid. In the case of mapped SPINS files converted into a netcdf file (through spins2netcdf) this additional field is called zc (for the z-coordinate or curvilinear z). Below are the steps required to plot a field with the correct mapping.
ParaView
- Read in netcdf file (choose "NetCDF files generic and CF conventions")
- Unselect the checkbox for Spherical Coordinates (this seems to only sometimes be necessary)
- Select the Output Type: Structured
- Click Apply
- In the Pipeline, select the file just opened and apply the calculator filter to it (either select the calculator icon, or under Tools->Common in menu bar)
- In the Calculator Properties page:
- Select Coordinate Result checkbox
- Change Result Array Name to something useful (such as "grid". This is unnecessary, but helpful if multiple operations are done)
- In the text box directly below this, input either
- for 2D: iHat*coordsX+jHat*zc
- for 3D: iHat*coordsX+jHat*coordsY+kHat*zc
- Click Apply
VisIt
- Read in netcdf file and add a plot
- Add the displace operator to the plot (Operators->Transforms->Displace)
- Click the arrow to the left of the plot in the Plot List to show the subitems
- Double click the Displace subitem
- Select Create new expression in the Displacement variable drop down menu
- Give expression the name "grid" and Type "Vector Mesh Variable"
- Input the definition as
- for 2D: "{0*zc,zc - coord(meshN1xN2)[1]}" where meshN1xN2 must be replace with the mesh variable found under Insert Variable->Meshes
- for 3D: "{0*zc,0*zc,zc - coord(meshN1xN2xN3)[2]}" where meshN1xN2xN3 must be replace with the mesh variable found under Insert Variable->Meshes
- Click Apply in the Expressions window
- Select grid in the Displacement variable drop down menu (under Vectors)
- Click Apply in the Displace operator attributes window
- Select Create new expression in the Displacement variable drop down menu
- Click Draw in the main menu
3D Printing
Thanks to the marvels of technology, it's not only possibly for you to 3D-print iso-surfaces from your simulations, it's actually fairly straight-forward!
Create .stl for the Iso-surface
For VisIt
File -> Export Databases
- Choose STL under
Export to
- Under
Add variable
choose the appropriate variable to export - Choose
Export
and selectBinary
in the pop-up window.
For ParaView
- File -> Save Data -> Choose STL from the filetype
- Choose Binary instead of Ascii
Scaling and Thickening
Iso-surfaces produced with the above method will have zero thickness, which causes problems for printing. You will also likely need / want to scale the dimensions of your stl image to fit the dimensions of the 3D printer. The following python script uses Blender to scale and thicken the image.
You will need to have Blender installed on your machine for this to work.
To run the script, you can call Blender from the command line via:
/Applications/Blender/blender.app/Contents/MacOS/blender --background --python scale_and_thicken.py
, where scale_and_thicken.py is the python script included below.
Depending on where you installed it, you may need to change the path to the executable.
- You will also need to modify lines 3 and 4 to specify your filenames.
- You can change the thickness by modifying line 31 (current default is roughly the minimum printable thickness)
- This procedure can produce some very large file sizes. One option to reduce file size is to apply a decimate modifier (lines 34-35). The setting in line 35 specifies the proportion of vertices/faces that should remain. So setting the ratio to 0.1 would reduce the file size by a factor of 10. What level of decimation can be applied before significant loss of quality is heavily context dependent, so play around with it.
- Depending on the nature of the shape, it may be easiest to print it on its side. To rotate the object, uncomment line 38 and specify the appropriate 'up' axis.
Note that the produced file has dimensions in mm.
scale_and_thicken.py
import bpy
in_path = "/Users/bastorer/Desktop/test.stl"
out_path = "/Users/bastorer/Desktop/out.stl"
# Delete all objects
bpy.ops.object.delete()
# Import object
bpy.ops.import_mesh.stl(filepath = in_path)
obj = bpy.context.visible_objects[0].name
print("Modifying <" + obj + "> object")
# Rescale to fit in box
# with mm dimensions
# 406.4 x 355.6 x 406.4
dims = bpy.data.objects[obj].dimensions
scale_x = 400. / dims[0]
scale_y = 350. / dims[1]
scale_z = 400. / dims[2]
scale = min(scale_x, scale_y, scale_z)
bpy.data.objects[obj].scale[0] = scale
bpy.data.objects[obj].scale[1] = scale
bpy.data.objects[obj].scale[2] = scale
# Add thickness to the object
bpy.ops.object.modifier_add(type = 'SOLIDIFY')
bpy.context.object.modifiers["Solidify"].thickness = 2./scale
# Decimate to reduce file size
bpy.ops.object.modifier_add(type = 'DECIMATE')
bpy.context.object.modifiers["Decimate"].ratio = 1.0
# Rotate the object (if desired)
#bpy.data.objects[obj].up_axis = 'Y'
# Export mesh
bpy.ops.export_mesh.stl(filepath = out_path)