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vbjax.neural_mass)": [[0, "vbjax.neural_mass.jr_dfun"]], "k1 (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.k1"]], "k2 (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.k2"]], "k3 (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.k3"]], "kernel_conv_prep() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_conv_prep"]], "kernel_diff() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_diff"]], "kernel_dist_origin() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_dist_origin"]], "kernel_estimate_shtns() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_estimate_shtns"]], "kernel_gaussian() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_gaussian"]], "kernel_laplace() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_laplace"]], "kernel_mexican_hat() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_mexican_hat"]], "kernel_sh_normalized() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.kernel_sh_normalized"]], "make_bold() (in module vbjax.monitor)": [[0, "vbjax.monitor.make_bold"]], "make_conn_latent_mvnorm() (in module vbjax.connectome)": [[0, "vbjax.connectome.make_conn_latent_mvnorm"]], "make_cov() (in module vbjax.monitor)": [[0, "vbjax.monitor.make_cov"]], "make_dde() (in module vbjax.loops)": [[0, "vbjax.loops.make_dde"]], "make_dense_layers() (in module vbjax.layers)": [[0, "vbjax.layers.make_dense_layers"]], "make_fc() (in module vbjax.monitor)": [[0, "vbjax.monitor.make_fc"]], "make_fft() (in module vbjax.monitor)": [[0, "vbjax.monitor.make_fft"]], "make_gain() (in module vbjax.monitor)": [[0, "vbjax.monitor.make_gain"]], "make_grid() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.make_grid"]], "make_grid_shtns() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.make_grid_shtns"]], "make_lm() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.make_lm"]], "make_ode() (in module vbjax.loops)": [[0, "vbjax.loops.make_ode"]], "make_offline() (in module vbjax.monitor)": [[0, "vbjax.monitor.make_offline"]], "make_sdde() (in module vbjax.loops)": [[0, "vbjax.loops.make_sdde"]], "make_sde() (in module vbjax.loops)": [[0, "vbjax.loops.make_sde"]], "make_sg_spmv() (in module vbjax.sparse)": [[0, "vbjax.sparse.make_sg_spmv"]], "make_shtdiff() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.make_shtdiff"]], "make_shtdiff_np() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.make_shtdiff_np"]], "make_spmv() (in module vbjax.sparse)": [[0, "vbjax.sparse.make_spmv"]], "make_timeavg() (in module vbjax.monitor)": [[0, "vbjax.monitor.make_timeavg"]], "module": [[0, "module-vbjax.connectome"], [0, "module-vbjax.layers"], [0, "module-vbjax.loops"], [0, "module-vbjax.monitor"], [0, "module-vbjax.neural_mass"], [0, "module-vbjax.shtlc"], [0, "module-vbjax.sparse"], [0, "module-vbjax.util"]], "mpr_dfun() (in module vbjax.neural_mass)": [[0, "vbjax.neural_mass.mpr_dfun"]], "mu (vbjax.neural_mass.jrtheta attribute)": [[0, "vbjax.neural_mass.JRTheta.mu"]], "nu_0 (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.nu_0"]], "nu_max (vbjax.neural_mass.jrtheta attribute)": [[0, "vbjax.neural_mass.JRTheta.nu_max"]], "r (vbjax.neural_mass.jrtheta attribute)": [[0, "vbjax.neural_mass.JRTheta.r"]], "r (vbjax.neural_mass.mprstate attribute)": [[0, "vbjax.neural_mass.MPRState.r"]], "r_0 (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.r_0"]], "randn_relaxed() (in module vbjax.shtlc)": [[0, "vbjax.shtlc.randn_relaxed"]], "recip_alpha (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.recip_alpha"]], "recip_e0 (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.recip_e0"]], "recip_tau_f (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.recip_tau_f"]], "recip_tau_o (vbjax.neural_mass.boldtheta attribute)": [[0, "vbjax.neural_mass.BOLDTheta.recip_tau_o"]], "recip_tau_s (vbjax.neural_mass.boldtheta attribute)": [[0, 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[[0, "module-vbjax.loops"]], "vbjax.monitor": [[0, "module-vbjax.monitor"]], "vbjax.neural_mass": [[0, "module-vbjax.neural_mass"]], "vbjax.shtlc": [[0, "module-vbjax.shtlc"]], "vbjax.sparse": [[0, "module-vbjax.sparse"]], "vbjax.util": [[0, "module-vbjax.util"]], "x0 (vbjax.neural_mass.bveptheta attribute)": [[0, "vbjax.neural_mass.BVEPTheta.x0"]], "y0 (vbjax.neural_mass.jrstate attribute)": [[0, "vbjax.neural_mass.JRState.y0"]], "y1 (vbjax.neural_mass.jrstate attribute)": [[0, "vbjax.neural_mass.JRState.y1"]], "y2 (vbjax.neural_mass.jrstate attribute)": [[0, "vbjax.neural_mass.JRState.y2"]], "y3 (vbjax.neural_mass.jrstate attribute)": [[0, "vbjax.neural_mass.JRState.y3"]], "y4 (vbjax.neural_mass.jrstate attribute)": [[0, "vbjax.neural_mass.JRState.y4"]], "y5 (vbjax.neural_mass.jrstate attribute)": [[0, "vbjax.neural_mass.JRState.y5"]]}})
\ No newline at end of file
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 1c3afc2..77df5d9 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -9,12 +9,78 @@ Welcome to vbjax's documentation!
Introduction
############
+`vbjax` is a Jax-based package for working with virtual brain style models.
+
+Installation
+############
+
+Installs with `pip install "vbjax"`, but you can use the source,
+
+.. code-block:: bash
+
+ git clone https://github.com/ins-amu/vbjax
+ cd vbjax
+ pip install .[dev]
+
+
+The primary additional dependency of vbjax is
+[JAX](github.com/google/jax), which itself depends only on
+NumPy, SciPy & opt-einsum, so it should be safe to add to your
+existing projects.
+
+gee pee you
+------------
+
+**CUDA**
+
+If you have a CUDA-enabled GPU, you install the requisite dependencies like so
+
+.. code-block:: bash
+
+ pip install --upgrade "jax[cuda11_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
+
+
+**M1/M2** 🍎
+
+On newer Apple machines w/ M1 or M2 GPUs, JAX supports using the GPU experimentally
+by installing just two extra packages:
+
+.. code-block:: bash
+
+ pip install ml-dtypes==0.2.0 jax-metal
+
+
+About a third of vbjax tests fail due to absence of certain operations like n-dim
+scatter/gather & FFTs, and it may not be faster because these CPUs already have
+excellent memory bandwidth & latency hiding.
+
+**CUDA** 🐳
+
+*BUT* because GPU software stack versions make aligning stars look like child's play,
+container images are available and auto-built w/
+[GitHub Actions](.github/workflows/docker-image.yml), so you can use w/ Docker
+
+.. code-block:: bash
+
+ docker run --rm -it ghcr.io/ins-amu/vbjax:main python3 -c 'import vbjax; print(vbjax.__version__)'
+
+
+The images are built on Nvidia runtime images, so `--gpus all` is enough
+for Jax to discover the GPU(s).
+
.. toctree::
:maxdepth: 2
:caption: Contents:
+Tutorial
+########
+.. toctree::
+ :maxdepth: 2
+ :caption: Contents:
+
+ tutorial
Indices and tables
==================
diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst
new file mode 100644
index 0000000..f37f8a9
--- /dev/null
+++ b/docs/source/tutorial.rst
@@ -0,0 +1,6 @@
+
+Tutorial
+***************
+
+This is some test text.
+
diff --git a/docs/tutorial.html b/docs/tutorial.html
new file mode 100644
index 0000000..915939b
--- /dev/null
+++ b/docs/tutorial.html
@@ -0,0 +1,100 @@
+
+
+
+
+
+
+
+
Tutorial — vbjax v0.0.10 documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+Tutorial
+This is some test text.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file