Merge pull request #232 from slimgroup/geom-3d

Field data improvements

.github/workflows/ci-examples.yml

@@ -26,7 +26,7 @@ jobs:
 
     steps:
       - name: Checkout JUDI
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - id: set-matrix
         run: echo "matrix=$(ls examples/scripts/*.jl examples/machine-learning/*.jl | xargs -n 1 | jq -R -s -c 'split("\n")[:-1]')" >> $GITHUB_OUTPUT
@@ -52,7 +52,7 @@ jobs:
 
     steps:
       - name: Checkout JUDI
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - name: Setup julia
         uses: julia-actions/setup-julia@v1

.github/workflows/ci-judi.yml

@@ -33,10 +33,10 @@ jobs:
 
     steps:
       - name: Checkout JUDI
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - name: Cache julia install
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         env:
           cache-name: cache-julia-pkgs
         with:

.github/workflows/ci-op.yml

@@ -19,9 +19,9 @@ jobs:
     name: ${{ matrix.op }} on Julia ${{ matrix.version }} - ${{ matrix.os }}
     runs-on: ${{ matrix.os }}
     env:
-      DEVITO_ARCH: gcc-9
+      DEVITO_ARCH: gcc-11
       DEVITO_LANGUAGE: "openmp"
-      DEVITO_LOGGING: "ERROR"
+      DEVITO_LOGGING: "INFO"
       OMP_NUM_THREADS: ${{ matrix.omp }}
       GROUP: ${{ matrix.op }}
 
@@ -62,14 +62,10 @@ jobs:
 
     steps:
       - name: Checkout JUDI
-        uses: actions/checkout@v3
-
-      - name: Install GCC 9
-        if : runner.os == 'macOS'
-        run : brew install gcc@9
+        uses: actions/checkout@v4
 
       - name: Cache julia install
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         env:
           cache-name: cache-julia-pkgs
         with:

.github/workflows/deploy_doc.yaml

@@ -19,7 +19,7 @@ jobs:
 
     steps:
       - name: Checkout master
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - uses: julia-actions/setup-julia@latest
 

.github/workflows/docker-publish.yml

@@ -25,7 +25,7 @@ jobs:
         run: echo ${{ github.event_name }}
 
       - name: Checkout JUDI
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - name: Set up QEMU
         uses: docker/[email protected]

.github/workflows/flake8.yml

@@ -20,10 +20,10 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v1
+    - uses: actions/checkout@v4
 
     - name: Set up Python 3.9
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: 3.9
 

Project.toml

@@ -32,14 +32,23 @@ SegyIO = "0.7.7 - 0.8.3, >= 0.8.5"
 TimerOutputs = "0.5"
 julia = "1.6"
 
+[extensions]
+FluxJUDIExt = "Flux"
+JLD2JUDIExt = "JLD2"
+ZygoteJUDIExt = "Zygote"
+
 [extras]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
-ArgParse = "c7e460c6-2fb9-53a9-8c5b-16f535851c63"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 
 [targets]
-test = ["Aqua", "ArgParse", "JLD2", "Printf", "Test", "TimerOutputs", "Flux"]
+test = ["Aqua", "JLD2", "Printf", "Test", "TimerOutputs", "Flux"]
+
+[weakdeps]
+Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
+JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"

deps/build.jl

@@ -5,9 +5,16 @@ struct DevitoException <: Exception
     msg::String
 end
 
-pk = pyimport("pkg_resources")
 python = PyCall.pyprogramname
 
+try
+    pk = pyimport("pkg_resources")
+catch e
+    Cmd([python, "-m", "pip", "install", "--user", "setuptools"])
+    run(cmd)
+    pk = pyimport("pkg_resources")
+end
+
 ################## Devito ##################
 # pip command
 cmd = Cmd([python, "-m", "pip", "install", "-U", "--user", "devito[extras,tests]>=4.4"])

docker/Dockerfile.base

@@ -9,6 +9,7 @@ ENV DEBIAN_FRONTEND noninteractive
 
 # Install nvidia HPC sdk
 RUN apt-get update -y && \
+    apt-get install -y -q python3 python3-dev python3-pip && \
     apt-get install -y -q wget git apt-utils vim curl jq && \
     apt-get install -y -q liblapack-dev libblas-dev libibverbs-dev && \
     wget -q -P /app/ https://developer.download.nvidia.com/hpc-sdk/21.5/nvhpc-21-5_21.5_amd64.deb \ 
@@ -85,3 +86,4 @@ WORKDIR /app/judi/notebooks
 EXPOSE 8888
 
 CMD /root/.local/bin/jupyter-notebook --ip="*" --no-browser --allow-root
+

docs/src/preconditioners.md

@@ -1,6 +1,6 @@
 # Seismic Preconditioners
 
-JUDI provides a selected number of preconditioners known to be beneficial to FWI and RTM. We welcome additional preconditionners from the community. Additionnaly, any JOLI operator can be used as a preconditiner in conbination with JUDI operator thanks to the fundamental interface between JUDI and JOLI.
+JUDI provides a selected number of preconditioners known to be beneficial to FWI and RTM. We welcome additional preconditioners from the community. Additionnaly, any JOLI operator can be used as a preconditiner in conbination with JUDI operator thanks to the fundamental interface between JUDI and JOLI.
 
 ```@contents
 Pages = ["preconditioners.md"]
@@ -74,7 +74,7 @@ m_mute = I'*vec(m)
 
 ## Data preconditioners
 
-These preconditioners are design to act on the shot records (data). These preconditioners are indexable by source number so that working with a subset of shot is trivial to implement.
+These preconditioners are design to act on the shot records (data). These preconditioners are indexable by source number so that working with a subset of shot is trivial to implement. Additionally, all [DataPreconditionner](@ref) are compatible with out-of-core JUDI objects such as `judiVector{SeisCon}` so that the preconditioner is only applied to single shot data at propagation time.
 
 
 ### Data topmute
@@ -100,4 +100,34 @@ A `TimeDifferential{K}` is a linear operator that implements a time derivative (
 
 ```@docs
 TimeDifferential
-```
+```
+
+## Inversion wrappers
+
+For large scale and practical cases, the inversions wrappers [fwi_objective](@ref) and [lsrtm_objective](@ref) are used to minimize the number of PDE solves. Those wrapper support the use of preconditioner as well for better results.
+
+**Usage:**
+
+For fwi, you can use the `data_precon` keyword argument to be applied to the residual (the preconditioner is applied to both the field and synthetic data to ensure better misfit):
+
+```julia
+fwi_objective(model, q, dobs; data_precon=precon)
+```
+
+where `precon` can be:
+
+- A single [DataPreconditionner](@ref)
+- A list/tuple of [DataPreconditionner](@ref)
+- A product of [DataPreconditionner](@ref)
+
+Similarly, for LSRTM, you can use the `model_precon` keyword argument to be applied to the perturbation `dm` and the `data_precon` keyword argument to be applied to the residual:
+
+```julia
+lsrtm_objective(model, q, dobs, dm; model_precon=dPrec, data_precon=dmPrec)
+```
+
+where `dPrec` and `dmPrec` can be:
+
+- A single preconditioner ([DataPreconditionner](@ref) for `data_precon` and [ModelPreconditionner](@ref) for `model_precon`)
+- A list/tuple of preconditioners ([DataPreconditionner](@ref) for `data_precon` and ModelPreconditionner](@ref) for `model_precon`)
+- A product of preconditioners ([DataPreconditionner](@ref) for `data_precon` and ModelPreconditionner](@ref) for `model_precon`)