diff --git a/.nojekyll b/.nojekyll index 34ab590..b43d3db 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -d98d715f \ No newline at end of file +82792286 \ No newline at end of file diff --git a/index.html b/index.html index bd1f763..13cf2da 100644 --- a/index.html +++ b/index.html @@ -1,8 +1,540 @@ - -
-Wassim Kabalan
+
Weak Gravitaional Lensing
-\[ \boxed{e = \gamma + e_i} \] ➢ With \(\gamma\) representing the shear and \(e_i\) representing the intrinsic ellipticity, distributed as \(\mathcal{N}(0, I)\)
-➢ We use the shear as as probe of dark matter distribution
\[p(\theta | x ) \propto \underbrace{p(x | \theta)}_{\mathrm{likelihood}} \ \underbrace{p(\theta)}_{\mathrm{prior}}\]
(Hikage et al. 2018)
➢ Measure the ellipticity \(e = \gamma + e_i\) of all galaxies
➢ Compute summary statistics based on the 2-point correlation function of the shear field
➢ Compute summary statistics based on the 2-point correlation function of the shear field
➢ Run an MCMC chain to recover the posterior distribution of the cosmological parameters, using an analytical likelihood
➢ Run an MCMC chain to recover the posterior distribution of the cosmological parameters, using an analytical likelihood \[p(\theta | x ) \propto \underbrace{p(x | \theta)}_{\mathrm{likelihood}} \ \underbrace{p(\theta)}_{\mathrm{prior}}\]
Limitations
➢ We need a fast, differentiable and precise cosmological simulations
+
➢ Interpolate particles on a grid to estimate mass density
+➢ Estimate gravitational force on grid points by FFT
+➢ Interpolate forces back on particles
+➢ Update particle velocity and positions, and iterate
+\(\begin{array}{c}{{\nabla^{2}\phi=-4\pi G\rho}}\\\\ {{f(\vec{k})=i\vec{k}k^{-2}\rho(\vec{k})}}\end{array}\)
+
Having a full n body simulation is very expensive, so we use a particle mesh simulation
-The idea is to put particles in a grid and evolve the particles in the grid
-you lose some precision on the small scales, but on the large scale it is pretty accurate.
-Numerical cheme
-Cloud in Cell binning
-
import numpy as np
+
+
+def multiply_and_add(a, b, c):
+ return np.dot(a, b) + c
+
+
+a, b, c = np.random.normal(size=(3, 32, 32))
+result = multiply_and_add(a, b, c)
import jax
+import jax.numpy as jnp
+
+@jax.jit
+def multiply_and_add(a, b, c):
+ return jnp.dot(a, b) + c
+
+
+key = jax.random.PRNGKey(0)
+a, b, c = jax.random.normal(key, (3, 32, 32))
+
+result = multiply_and_add(a, b, c)
+gradient = jax.grad(multiply_and_add)(a, b, c)
JAX : Numpy + Autograd + GPU
+when we have the forces on the grid point we interpolate the forces on the particles
-Rubin observatory will provide us with a 15 TB of data per night for 10 years
-say that we need to make a cube of big part of the volume of the survey.
-Picture of a 3D force vector field
-High end GPUs have a reached 80 GBs A100 next generation H100
+
+ DifferentiableUniverseInitiative/JaxPM
+
mesh_shape = [64, 64, 64]
+box_size = [64., 64., 64.]
+snapshots = jnp.linspace(0.1, 1., 2)
+
+@jax.jit
+def run_simulation(omega_c, sigma8):
+ # Create a small function to generate the matter power spectrum
+ k = jnp.logspace(-4, 1, 128)
+ pk = jc.power.linear_matter_power(
+ jc.Planck15(Omega_c=omega_c, sigma8=sigma8), k)
+ pk_fn = lambda x: jc.scipy.interpolate.interp(x.reshape([-1]), k, pk
+ ).reshape(x.shape)
+
+ # Create initial conditions
+ initial_conditions = linear_field(mesh_shape,
+ box_size,
+ pk_fn,
+ seed=jax.random.PRNGKey(0))
+
+ # Create particles
+ particles = jnp.stack(jnp.meshgrid(*[jnp.arange(s) for s in mesh_shape]),
+ axis=-1).reshape([-1, 3])
+
+ cosmo = jc.Planck15(Omega_c=omega_c, sigma8=sigma8)
+
+ # Initial displacement
+ dx, p, f = lpt(cosmo, initial_conditions, particles, 0.1)
+ field = dx + particles
+
+ # Evolve the simulation forward
+ ode_fn = make_ode_fn(mesh_shape)
+ term = ODETerm(lambda t, state, args: jnp.stack(ode_fn(state, t, args), axis=0))
+ solver = Dopri5()
+
+ stepsize_controller = PIDController(rtol=1e-7, atol=1e-7)
+ res = diffeqsolve(term, solver, t0=0.1, t1=1., dt0=0.01, y0=jnp.stack([dx, p],axis=0),
+ args=(cosmo , kvec),
+ stepsize_controller=stepsize_controller,
+ saveat=SaveAt(ts=snapshots))
+
+ # Return the simulation volume at requested
+ return field, res, initial_conditions
+
+field, res, initial_conditions = run_simulation(0.25, 0.8)
+
+
Is everything solved ?
+JAX
-➢ (Poqueres et al. 2021) : \(64^3\) mesh size, on a 1000 Mpc/h box
+➢ (Li et al. 2022) : \(512^3\) mesh size, using pmwd
+ Initial Conditions with a 512 mesh
Initial Conditions with a 256 mesh
Initial Conditions with a 128 mesh
Initial Conditions with a 64 mesh
Power Spectrum
Power Spectrum
Power Spectrum
Power Spectrum
Final field with a 512 mesh
Initial Conditions with a 256 mesh
Initial Conditions with a 128 mesh
Initial Conditions with a 64 mesh
Final field with a 512 mesh
Initial Conditions with a 256 mesh
Initial Conditions with a 128 mesh
Initial Conditions with a 64 mesh
Scaling
+We need a fast, differentiable and Scalable Particle-Mesh simulation
+example of numpy code and grad
-we can also run multiple devices in a single controlle set up
-80 w=x 80
-Differentiable multi host distributed n body simulation that runs on GPUs
-Related work
-FastPM Poqueres nbody 64^3 pmwd 512^3
+
Single GPU (80GB)
Single Node (8x80GB)
Muti Node ( \(\infty\) )
➢ only operation that requires communication is the FFT
+
+ DifferentiableUniverseInitiative/jaxDecomp
+
built on top of JAXDECOMP
-example code of JAXPM
-Three steps
-Generate the linear field
-then LPT simulation
-then the final nbody simulation (use any differential equation solver like diffrax)
-Finally we put the final grid back to the particles
+➢ only operation that requires communication is the FFT
+
+ DifferentiableUniverseInitiative/jaxDecomp
+
import jax
+import jax.numpy as jnp
+import jaxdecomp
+
+devices = mesh_utils.create_device_mesh((2, 2))
+mesh = jax.sharding.Mesh(devices, axis_names=('x', 'y'))
+sharding = jax.sharding.NamedSharding(mesh, P('x', 'y'))
+
+# Create gaussian field distributed across the mesh
+field = jax.make_array_from_single_device_arrays(
+ shape=mesh_shape,
+ sharding=sharding,
+ arrays=[jax.random.normal(jax.random.PRNGKey(rank), (512, 512, 1024))])
+
+k_field = jaxdecomp.fft.pfft3d(field)
+
JaxDecomp features
+➢ jaxDecomp supports 2D and 1D decompositions
+➢ Works for multi-node FFTs
+➢ is differentiable
+➢ The package is also provided as a standalone library
+We can simply differentiate the entire simulation using jax.grad
-We can also interface it with machine learning frameworks like flax for the dark matter halo painting and galaxy painting
+Unique solutions : no, two particles crossing each other yoy can’t tell which one is which
+ Initial Conditions
LPT Simulation
Final field
Distributed FastPM simulations
+➢ Multi host version of JaxPM using jaxDecomp
+➢ For a \(4096^3\) simulation we used 32 GPUs on 4 nodes
+➢ Runtime for a forward run is 6 seconds
+
Distruibuted Particle-Mesh simulations for cosmological inference
+➢ A shift from analytical likelihoods to full field inference
+➢ The need for fast differentiable simulators
+➢ Particle-Mesh as simulators for full field inference
+➢ Distributed fourrier transforms that work on multi-node HPC
+image of with and without halo exchange
${missingFields[0]}
field.`,
+ message: `The items being returned for this search do not include all the required fields. Please ensure that your index items include the ${missingFields[0]}
field or use index-fields
in your _quarto.yml
file to specify the field names.`,
+ };
+ } else if (missingFields.length > 1) {
+ const missingFieldList = missingFields
+ .map((field) => {
+ return `${field}
`;
+ })
+ .join(", ");
+
+ throw {
+ name: `Error: Search index is missing the following fields: ${missingFieldList}.`,
+ message: `The items being returned for this search do not include all the required fields. Please ensure that your index items includes the following fields: ${missingFieldList}, or use index-fields
in your _quarto.yml
file to specify the field names.`,
+ };
+ }
+ }
+}
+
+let lastQuery = null;
+function showCopyLink(query, options) {
+ const language = options.language;
+ lastQuery = query;
+ // Insert share icon
+ const inputSuffixEl = window.document.body.querySelector(
+ ".aa-Form .aa-InputWrapperSuffix"
+ );
+
+ if (inputSuffixEl) {
+ let copyButtonEl = window.document.body.querySelector(
+ ".aa-Form .aa-InputWrapperSuffix .aa-CopyButton"
+ );
+
+ if (copyButtonEl === null) {
+ copyButtonEl = window.document.createElement("button");
+ copyButtonEl.setAttribute("class", "aa-CopyButton");
+ copyButtonEl.setAttribute("type", "button");
+ copyButtonEl.setAttribute("title", language["search-copy-link-title"]);
+ copyButtonEl.onmousedown = (e) => {
+ e.preventDefault();
+ e.stopPropagation();
+ };
+
+ const linkIcon = "bi-clipboard";
+ const checkIcon = "bi-check2";
+
+ const shareIconEl = window.document.createElement("i");
+ shareIconEl.setAttribute("class", `bi ${linkIcon}`);
+ copyButtonEl.appendChild(shareIconEl);
+ inputSuffixEl.prepend(copyButtonEl);
+
+ const clipboard = new window.ClipboardJS(".aa-CopyButton", {
+ text: function (_trigger) {
+ const copyUrl = new URL(window.location);
+ copyUrl.searchParams.set(kQueryArg, lastQuery);
+ copyUrl.searchParams.set(kResultsArg, "1");
+ return copyUrl.toString();
+ },
+ });
+ clipboard.on("success", function (e) {
+ // Focus the input
+
+ // button target
+ const button = e.trigger;
+ const icon = button.querySelector("i.bi");
+
+ // flash "checked"
+ icon.classList.add(checkIcon);
+ icon.classList.remove(linkIcon);
+ setTimeout(function () {
+ icon.classList.remove(checkIcon);
+ icon.classList.add(linkIcon);
+ }, 1000);
+ });
+ }
+
+ // If there is a query, show the link icon
+ if (copyButtonEl) {
+ if (lastQuery && options["copy-button"]) {
+ copyButtonEl.style.display = "flex";
+ } else {
+ copyButtonEl.style.display = "none";
+ }
+ }
+ }
+}
+
+/* Search Index Handling */
+// create the index
+var fuseIndex = undefined;
+var shownWarning = false;
+
+// fuse index options
+const kFuseIndexOptions = {
+ keys: [
+ { name: "title", weight: 20 },
+ { name: "section", weight: 20 },
+ { name: "text", weight: 10 },
+ ],
+ ignoreLocation: true,
+ threshold: 0.1,
+};
+
+async function readSearchData() {
+ // Initialize the search index on demand
+ if (fuseIndex === undefined) {
+ if (window.location.protocol === "file:" && !shownWarning) {
+ window.alert(
+ "Search requires JavaScript features disabled when running in file://... URLs. In order to use search, please run this document in a web server."
+ );
+ shownWarning = true;
+ return;
+ }
+ const fuse = new window.Fuse([], kFuseIndexOptions);
+
+ // fetch the main search.json
+ const response = await fetch(offsetURL("search.json"));
+ if (response.status == 200) {
+ return response.json().then(function (searchDocs) {
+ searchDocs.forEach(function (searchDoc) {
+ fuse.add(searchDoc);
+ });
+ fuseIndex = fuse;
+ return fuseIndex;
+ });
+ } else {
+ return Promise.reject(
+ new Error(
+ "Unexpected status from search index request: " + response.status
+ )
+ );
+ }
+ }
+
+ return fuseIndex;
+}
+
+function inputElement() {
+ return window.document.body.querySelector(".aa-Form .aa-Input");
+}
+
+function focusSearchInput() {
+ setTimeout(() => {
+ const inputEl = inputElement();
+ if (inputEl) {
+ inputEl.focus();
+ }
+ }, 50);
+}
+
+/* Panels */
+const kItemTypeDoc = "document";
+const kItemTypeMore = "document-more";
+const kItemTypeItem = "document-item";
+const kItemTypeError = "error";
+
+function renderItem(
+ item,
+ createElement,
+ state,
+ setActiveItemId,
+ setContext,
+ refresh,
+ quartoSearchOptions
+) {
+ switch (item.type) {
+ case kItemTypeDoc:
+ return createDocumentCard(
+ createElement,
+ "file-richtext",
+ item.title,
+ item.section,
+ item.text,
+ item.href,
+ item.crumbs,
+ quartoSearchOptions
+ );
+ case kItemTypeMore:
+ return createMoreCard(
+ createElement,
+ item,
+ state,
+ setActiveItemId,
+ setContext,
+ refresh
+ );
+ case kItemTypeItem:
+ return createSectionCard(
+ createElement,
+ item.section,
+ item.text,
+ item.href
+ );
+ case kItemTypeError:
+ return createErrorCard(createElement, item.title, item.text);
+ default:
+ return undefined;
+ }
+}
+
+function createDocumentCard(
+ createElement,
+ icon,
+ title,
+ section,
+ text,
+ href,
+ crumbs,
+ quartoSearchOptions
+) {
+ const iconEl = createElement("i", {
+ class: `bi bi-${icon} search-result-icon`,
+ });
+ const titleEl = createElement("p", { class: "search-result-title" }, title);
+ const titleContents = [iconEl, titleEl];
+ const showParent = quartoSearchOptions["show-item-context"];
+ if (crumbs && showParent) {
+ let crumbsOut = undefined;
+ const crumbClz = ["search-result-crumbs"];
+ if (showParent === "root") {
+ crumbsOut = crumbs.length > 1 ? crumbs[0] : undefined;
+ } else if (showParent === "parent") {
+ crumbsOut = crumbs.length > 1 ? crumbs[crumbs.length - 2] : undefined;
+ } else {
+ crumbsOut = crumbs.length > 1 ? crumbs.join(" > ") : undefined;
+ crumbClz.push("search-result-crumbs-wrap");
+ }
+
+ const crumbEl = createElement(
+ "p",
+ { class: crumbClz.join(" ") },
+ crumbsOut
+ );
+ titleContents.push(crumbEl);
+ }
+
+ const titleContainerEl = createElement(
+ "div",
+ { class: "search-result-title-container" },
+ titleContents
+ );
+
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+ if (section) {
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+ section
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+ textEls.push(sectionEl);
+ }
+ const descEl = createElement("p", {
+ class: "search-result-text",
+ dangerouslySetInnerHTML: {
+ __html: text,
+ },
+ });
+ textEls.push(descEl);
+
+ const textContainerEl = createElement(
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+ );
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+ const containerEl = createElement(
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+ {
+ class: "search-result-container",
+ },
+ [titleContainerEl, textContainerEl]
+ );
+
+ const linkEl = createElement(
+ "a",
+ {
+ href: offsetURL(href),
+ class: "search-result-link",
+ },
+ containerEl
+ );
+
+ const classes = ["search-result-doc", "search-item"];
+ if (!section) {
+ classes.push("document-selectable");
+ }
+
+ return createElement(
+ "div",
+ {
+ class: classes.join(" "),
+ },
+ linkEl
+ );
+}
+
+function createMoreCard(
+ createElement,
+ item,
+ state,
+ setActiveItemId,
+ setContext,
+ refresh
+) {
+ const moreCardEl = createElement(
+ "div",
+ {
+ class: "search-result-more search-item",
+ onClick: (e) => {
+ // Handle expanding the sections by adding the expanded
+ // section to the list of expanded sections
+ toggleExpanded(item, state, setContext, setActiveItemId, refresh);
+ e.stopPropagation();
+ },
+ },
+ item.title
+ );
+
+ return moreCardEl;
+}
+
+function toggleExpanded(item, state, setContext, setActiveItemId, refresh) {
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+ if (expanded.includes(item.target)) {
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+ expanded: expanded.filter((target) => target !== item.target),
+ });
+ } else {
+ setContext({ expanded: [...expanded, item.target] });
+ }
+
+ refresh();
+ setActiveItemId(item.__autocomplete_id);
+}
+
+function createSectionCard(createElement, section, text, href) {
+ const sectionEl = createSection(createElement, section, text, href);
+ return createElement(
+ "div",
+ {
+ class: "search-result-doc-section search-item",
+ },
+ sectionEl
+ );
+}
+
+function createSection(createElement, title, text, href) {
+ const descEl = createElement("p", {
+ class: "search-result-text",
+ dangerouslySetInnerHTML: {
+ __html: text,
+ },
+ });
+
+ const titleEl = createElement("p", { class: "search-result-section" }, title);
+ const linkEl = createElement(
+ "a",
+ {
+ href: offsetURL(href),
+ class: "search-result-link",
+ },
+ [titleEl, descEl]
+ );
+ return linkEl;
+}
+
+function createErrorCard(createElement, title, text) {
+ const descEl = createElement("p", {
+ class: "search-error-text",
+ dangerouslySetInnerHTML: {
+ __html: text,
+ },
+ });
+
+ const titleEl = createElement("p", {
+ class: "search-error-title",
+ dangerouslySetInnerHTML: {
+ __html: ` ${title}`,
+ },
+ });
+ const errorEl = createElement("div", { class: "search-error" }, [
+ titleEl,
+ descEl,
+ ]);
+ return errorEl;
+}
+
+function positionPanel(pos) {
+ const panelEl = window.document.querySelector(
+ "#quarto-search-results .aa-Panel"
+ );
+ const inputEl = window.document.querySelector(
+ "#quarto-search .aa-Autocomplete"
+ );
+
+ if (panelEl && inputEl) {
+ panelEl.style.top = `${Math.round(panelEl.offsetTop)}px`;
+ if (pos === "start") {
+ panelEl.style.left = `${Math.round(inputEl.left)}px`;
+ } else {
+ panelEl.style.right = `${Math.round(inputEl.offsetRight)}px`;
+ }
+ }
+}
+
+/* Highlighting */
+// highlighting functions
+function highlightMatch(query, text) {
+ if (text) {
+ const start = text.toLowerCase().indexOf(query.toLowerCase());
+ if (start !== -1) {
+ const startMark = "";
+ const endMark = "";
+
+ const end = start + query.length;
+ text =
+ text.slice(0, start) +
+ startMark +
+ text.slice(start, end) +
+ endMark +
+ text.slice(end);
+ const startInfo = clipStart(text, start);
+ const endInfo = clipEnd(
+ text,
+ startInfo.position + startMark.length + endMark.length
+ );
+ text =
+ startInfo.prefix +
+ text.slice(startInfo.position, endInfo.position) +
+ endInfo.suffix;
+
+ return text;
+ } else {
+ return text;
+ }
+ } else {
+ return text;
+ }
+}
+
+function clipStart(text, pos) {
+ const clipStart = pos - 50;
+ if (clipStart < 0) {
+ // This will just return the start of the string
+ return {
+ position: 0,
+ prefix: "",
+ };
+ } else {
+ // We're clipping before the start of the string, walk backwards to the first space.
+ const spacePos = findSpace(text, pos, -1);
+ return {
+ position: spacePos.position,
+ prefix: "",
+ };
+ }
+}
+
+function clipEnd(text, pos) {
+ const clipEnd = pos + 200;
+ if (clipEnd > text.length) {
+ return {
+ position: text.length,
+ suffix: "",
+ };
+ } else {
+ const spacePos = findSpace(text, clipEnd, 1);
+ return {
+ position: spacePos.position,
+ suffix: spacePos.clipped ? "…" : "",
+ };
+ }
+}
+
+function findSpace(text, start, step) {
+ let stepPos = start;
+ while (stepPos > -1 && stepPos < text.length) {
+ const char = text[stepPos];
+ if (char === " " || char === "," || char === ":") {
+ return {
+ position: step === 1 ? stepPos : stepPos - step,
+ clipped: stepPos > 1 && stepPos < text.length,
+ };
+ }
+ stepPos = stepPos + step;
+ }
+
+ return {
+ position: stepPos - step,
+ clipped: false,
+ };
+}
+
+// removes highlighting as implemented by the mark tag
+function clearHighlight(searchterm, el) {
+ const childNodes = el.childNodes;
+ for (let i = childNodes.length - 1; i >= 0; i--) {
+ const node = childNodes[i];
+ if (node.nodeType === Node.ELEMENT_NODE) {
+ if (
+ node.tagName === "MARK" &&
+ node.innerText.toLowerCase() === searchterm.toLowerCase()
+ ) {
+ el.replaceChild(document.createTextNode(node.innerText), node);
+ } else {
+ clearHighlight(searchterm, node);
+ }
+ }
+ }
+}
+
+function escapeRegExp(string) {
+ return string.replace(/[.*+?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
+}
+
+// highlight matches
+function highlight(term, el) {
+ const termRegex = new RegExp(term, "ig");
+ const childNodes = el.childNodes;
+
+ // walk back to front avoid mutating elements in front of us
+ for (let i = childNodes.length - 1; i >= 0; i--) {
+ const node = childNodes[i];
+
+ if (node.nodeType === Node.TEXT_NODE) {
+ // Search text nodes for text to highlight
+ const text = node.nodeValue;
+
+ let startIndex = 0;
+ let matchIndex = text.search(termRegex);
+ if (matchIndex > -1) {
+ const markFragment = document.createDocumentFragment();
+ while (matchIndex > -1) {
+ const prefix = text.slice(startIndex, matchIndex);
+ markFragment.appendChild(document.createTextNode(prefix));
+
+ const mark = document.createElement("mark");
+ mark.appendChild(
+ document.createTextNode(
+ text.slice(matchIndex, matchIndex + term.length)
+ )
+ );
+ markFragment.appendChild(mark);
+
+ startIndex = matchIndex + term.length;
+ matchIndex = text.slice(startIndex).search(new RegExp(term, "ig"));
+ if (matchIndex > -1) {
+ matchIndex = startIndex + matchIndex;
+ }
+ }
+ if (startIndex < text.length) {
+ markFragment.appendChild(
+ document.createTextNode(text.slice(startIndex, text.length))
+ );
+ }
+
+ el.replaceChild(markFragment, node);
+ }
+ } else if (node.nodeType === Node.ELEMENT_NODE) {
+ // recurse through elements
+ highlight(term, node);
+ }
+ }
+}
+
+/* Link Handling */
+// get the offset from this page for a given site root relative url
+function offsetURL(url) {
+ var offset = getMeta("quarto:offset");
+ return offset ? offset + url : url;
+}
+
+// read a meta tag value
+function getMeta(metaName) {
+ var metas = window.document.getElementsByTagName("meta");
+ for (let i = 0; i < metas.length; i++) {
+ if (metas[i].getAttribute("name") === metaName) {
+ return metas[i].getAttribute("content");
+ }
+ }
+ return "";
+}
+
+function algoliaSearch(query, limit, algoliaOptions) {
+ const { getAlgoliaResults } = window["@algolia/autocomplete-preset-algolia"];
+
+ const applicationId = algoliaOptions["application-id"];
+ const searchOnlyApiKey = algoliaOptions["search-only-api-key"];
+ const indexName = algoliaOptions["index-name"];
+ const indexFields = algoliaOptions["index-fields"];
+ const searchClient = window.algoliasearch(applicationId, searchOnlyApiKey);
+ const searchParams = algoliaOptions["params"];
+ const searchAnalytics = !!algoliaOptions["analytics-events"];
+
+ return getAlgoliaResults({
+ searchClient,
+ queries: [
+ {
+ indexName: indexName,
+ query,
+ params: {
+ hitsPerPage: limit,
+ clickAnalytics: searchAnalytics,
+ ...searchParams,
+ },
+ },
+ ],
+ transformResponse: (response) => {
+ if (!indexFields) {
+ return response.hits.map((hit) => {
+ return hit.map((item) => {
+ return {
+ ...item,
+ text: highlightMatch(query, item.text),
+ };
+ });
+ });
+ } else {
+ const remappedHits = response.hits.map((hit) => {
+ return hit.map((item) => {
+ const newItem = { ...item };
+ ["href", "section", "title", "text", "crumbs"].forEach(
+ (keyName) => {
+ const mappedName = indexFields[keyName];
+ if (
+ mappedName &&
+ item[mappedName] !== undefined &&
+ mappedName !== keyName
+ ) {
+ newItem[keyName] = item[mappedName];
+ delete newItem[mappedName];
+ }
+ }
+ );
+ newItem.text = highlightMatch(query, newItem.text);
+ return newItem;
+ });
+ });
+ return remappedHits;
+ }
+ },
+ });
+}
+
+let subSearchTerm = undefined;
+let subSearchFuse = undefined;
+const kFuseMaxWait = 125;
+
+async function fuseSearch(query, fuse, fuseOptions) {
+ let index = fuse;
+ // Fuse.js using the Bitap algorithm for text matching which runs in
+ // O(nm) time (no matter the structure of the text). In our case this
+ // means that long search terms mixed with large index gets very slow
+ //
+ // This injects a subIndex that will be used once the terms get long enough
+ // Usually making this subindex is cheap since there will typically be
+ // a subset of results matching the existing query
+ if (subSearchFuse !== undefined && query.startsWith(subSearchTerm)) {
+ // Use the existing subSearchFuse
+ index = subSearchFuse;
+ } else if (subSearchFuse !== undefined) {
+ // The term changed, discard the existing fuse
+ subSearchFuse = undefined;
+ subSearchTerm = undefined;
+ }
+
+ // Search using the active fuse
+ const then = performance.now();
+ const resultsRaw = await index.search(query, fuseOptions);
+ const now = performance.now();
+
+ const results = resultsRaw.map((result) => {
+ const addParam = (url, name, value) => {
+ const anchorParts = url.split("#");
+ const baseUrl = anchorParts[0];
+ const sep = baseUrl.search("\\?") > 0 ? "&" : "?";
+ anchorParts[0] = baseUrl + sep + name + "=" + value;
+ return anchorParts.join("#");
+ };
+
+ return {
+ title: result.item.title,
+ section: result.item.section,
+ href: addParam(result.item.href, kQueryArg, query),
+ text: highlightMatch(query, result.item.text),
+ crumbs: result.item.crumbs,
+ };
+ });
+
+ // If we don't have a subfuse and the query is long enough, go ahead
+ // and create a subfuse to use for subsequent queries
+ if (now - then > kFuseMaxWait && subSearchFuse === undefined) {
+ subSearchTerm = query;
+ subSearchFuse = new window.Fuse([], kFuseIndexOptions);
+ resultsRaw.forEach((rr) => {
+ subSearchFuse.add(rr.item);
+ });
+ }
+ return results;
+}
diff --git a/site_libs/revealjs/dist/theme/quarto.css b/site_libs/revealjs/dist/theme/quarto.css
index 73df8c3..61c9e07 100644
--- a/site_libs/revealjs/dist/theme/quarto.css
+++ b/site_libs/revealjs/dist/theme/quarto.css
@@ -1,8 +1,8 @@
-@import"./fonts/source-sans-pro/source-sans-pro.css";:root{--r-background-color: #000;--r-main-font: Source Sans Pro, Helvetica, sans-serif;--r-main-font-size: 40px;--r-main-color: #fff;--r-block-margin: 12px;--r-heading-margin: 0 0 12px 0;--r-heading-font: Source Sans Pro, Helvetica, sans-serif;--r-heading-color: #fff;--r-heading-line-height: 1.2;--r-heading-letter-spacing: normal;--r-heading-text-transform: none;--r-heading-text-shadow: none;--r-heading-font-weight: 600;--r-heading1-text-shadow: none;--r-heading1-size: 2.5em;--r-heading2-size: 1.6em;--r-heading3-size: 1.3em;--r-heading4-size: 1em;--r-code-font: SFMono-Regular, Menlo, Monaco, Consolas, Liberation Mono, Courier New, monospace;--r-link-color: #42affa;--r-link-color-dark: #068de9;--r-link-color-hover: #74c4fb;--r-selection-background-color: #bee4fd;--r-selection-color: 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auto;padding:5px;font-style:italic;background:rgba(255,255,255,.05);box-shadow:0px 0px 2px rgba(0,0,0,.2)}.reveal blockquote p:first-child,.reveal blockquote p:last-child{display:inline-block}.reveal q{font-style:italic}.reveal pre{display:block;position:relative;width:90%;margin:var(--r-block-margin) auto;text-align:left;font-size:.55em;font-family:var(--r-code-font);line-height:1.2em;word-wrap:break-word;box-shadow:0px 5px 15px rgba(0,0,0,.15)}.reveal code{font-family:var(--r-code-font);text-transform:none;tab-size:2}.reveal pre code{display:block;padding:5px;overflow:auto;max-height:400px;word-wrap:normal}.reveal .code-wrapper{white-space:normal}.reveal .code-wrapper code{white-space:pre}.reveal table{margin:auto;border-collapse:collapse;border-spacing:0}.reveal table th{font-weight:bold}.reveal table th,.reveal table td{text-align:left;padding:.2em .5em .2em .5em;border-bottom:1px solid}.reveal table th[align=center],.reveal table td[align=center]{text-align:center}.reveal table 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+@import"./fonts/source-sans-pro/source-sans-pro.css";:root{--r-background-color: rgb(39, 39, 39);--r-main-font: Source Sans Pro, Helvetica, sans-serif;--r-main-font-size: 40px;--r-main-color: #fff;--r-block-margin: 12px;--r-heading-margin: 0 0 12px 0;--r-heading-font: Source Sans Pro, Helvetica, sans-serif;--r-heading-color: #fff;--r-heading-line-height: 1.2;--r-heading-letter-spacing: normal;--r-heading-text-transform: none;--r-heading-text-shadow: none;--r-heading-font-weight: 600;--r-heading1-text-shadow: none;--r-heading1-size: 2.5em;--r-heading2-size: 1.6em;--r-heading3-size: 1.3em;--r-heading4-size: 1em;--r-code-font: SFMono-Regular, Menlo, Monaco, Consolas, Liberation Mono, Courier New, monospace;--r-link-color: #42affa;--r-link-color-dark: #068de9;--r-link-color-hover: #74c4fb;--r-selection-background-color: #bee4fd;--r-selection-color: rgb(39, 39, 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.widget-subarea{margin-bottom:1em}.cell-output-display:not(.no-overflow-x),.knitsql-table:not(.no-overflow-x){overflow-x:auto}.panel-input{margin-bottom:1em}.panel-input>div,.panel-input>div>div{display:inline-block;vertical-align:top;padding-right:12px}.panel-input>p:last-child{margin-bottom:0}.layout-sidebar{margin-bottom:1em}.layout-sidebar .tab-content{border:none}.tab-content>.page-columns.active{display:grid}div.sourceCode>iframe{width:100%;height:300px;margin-bottom:-0.5em}a{text-underline-offset:3px}div.ansi-escaped-output{font-family:monospace;display:block}/*!
*
* ansi colors from IPython notebook's
*
* we also add `bright-[color]-` synonyms for the `-[color]-intense` classes since
* that seems to be what ansi_up emits
*
-*/.ansi-black-fg{color:#3e424d}.ansi-black-bg{background-color:#3e424d}.ansi-black-intense-black,.ansi-bright-black-fg{color:#282c36}.ansi-black-intense-black,.ansi-bright-black-bg{background-color:#282c36}.ansi-red-fg{color:#e75c58}.ansi-red-bg{background-color:#e75c58}.ansi-red-intense-red,.ansi-bright-red-fg{color:#b22b31}.ansi-red-intense-red,.ansi-bright-red-bg{background-color:#b22b31}.ansi-green-fg{color:#00a250}.ansi-green-bg{background-color:#00a250}.ansi-green-intense-green,.ansi-bright-green-fg{color:#007427}.ansi-green-intense-green,.ansi-bright-green-bg{background-color:#007427}.ansi-yellow-fg{color:#ddb62b}.ansi-yellow-bg{background-color:#ddb62b}.ansi-yellow-intense-yellow,.ansi-bright-yellow-fg{color:#b27d12}.ansi-yellow-intense-yellow,.ansi-bright-yellow-bg{background-color:#b27d12}.ansi-blue-fg{color:#208ffb}.ansi-blue-bg{background-color:#208ffb}.ansi-blue-intense-blue,.ansi-bright-blue-fg{color:#0065ca}.ansi-blue-intense-blue,.ansi-bright-blue-bg{background-color:#0065ca}.ansi-magenta-fg{color:#d160c4}.ansi-magenta-bg{background-color:#d160c4}.ansi-magenta-intense-magenta,.ansi-bright-magenta-fg{color:#a03196}.ansi-magenta-intense-magenta,.ansi-bright-magenta-bg{background-color:#a03196}.ansi-cyan-fg{color:#60c6c8}.ansi-cyan-bg{background-color:#60c6c8}.ansi-cyan-intense-cyan,.ansi-bright-cyan-fg{color:#258f8f}.ansi-cyan-intense-cyan,.ansi-bright-cyan-bg{background-color:#258f8f}.ansi-white-fg{color:#c5c1b4}.ansi-white-bg{background-color:#c5c1b4}.ansi-white-intense-white,.ansi-bright-white-fg{color:#a1a6b2}.ansi-white-intense-white,.ansi-bright-white-bg{background-color:#a1a6b2}.ansi-default-inverse-fg{color:#fff}.ansi-default-inverse-bg{background-color:#000}.ansi-bold{font-weight:bold}.ansi-underline{text-decoration:underline}:root{--quarto-body-bg: #000;--quarto-body-color: #fff;--quarto-text-muted: white;--quarto-border-color: white;--quarto-border-width: 1px;--quarto-border-radius: 4px}table.gt_table{color:var(--quarto-body-color);font-size:1em;width:100%;background-color:rgba(0,0,0,0);border-top-width:inherit;border-bottom-width:inherit;border-color:var(--quarto-border-color)}table.gt_table th.gt_column_spanner_outer{color:var(--quarto-body-color);background-color:rgba(0,0,0,0);border-top-width:inherit;border-bottom-width:inherit;border-color:var(--quarto-border-color)}table.gt_table th.gt_col_heading{color:var(--quarto-body-color);font-weight:bold;background-color:rgba(0,0,0,0)}table.gt_table thead.gt_col_headings{border-bottom:1px solid currentColor;border-top-width:inherit;border-top-color:var(--quarto-border-color)}table.gt_table thead.gt_col_headings:not(:first-child){border-top-width:1px;border-top-color:var(--quarto-border-color)}table.gt_table td.gt_row{border-bottom-width:1px;border-bottom-color:var(--quarto-border-color);border-top-width:0px}table.gt_table tbody.gt_table_body{border-top-width:1px;border-bottom-width:1px;border-bottom-color:var(--quarto-border-color);border-top-color:currentColor}div.columns{display:initial;gap:initial}div.column{display:inline-block;overflow-x:initial;vertical-align:top;width:50%}.code-annotation-tip-content{word-wrap:break-word}.code-annotation-container-hidden{display:none !important}dl.code-annotation-container-grid{display:grid;grid-template-columns:min-content auto}dl.code-annotation-container-grid dt{grid-column:1}dl.code-annotation-container-grid dd{grid-column:2}pre.sourceCode.code-annotation-code{padding-right:0}code.sourceCode .code-annotation-anchor{z-index:100;position:relative;float:right;background-color:rgba(0,0,0,0)}input[type=checkbox]{margin-right:.5ch}:root{--mermaid-bg-color: #000;--mermaid-edge-color: #999;--mermaid-node-fg-color: #fff;--mermaid-fg-color: #fff;--mermaid-fg-color--lighter: white;--mermaid-fg-color--lightest: white;--mermaid-font-family: Source Sans Pro, Helvetica, sans-serif;--mermaid-label-bg-color: #000;--mermaid-label-fg-color: #468;--mermaid-node-bg-color: rgba(68, 102, 136, 0.1);--mermaid-node-fg-color: #fff}@media print{:root{font-size:11pt}#quarto-sidebar,#TOC,.nav-page{display:none}.page-columns .content{grid-column-start:page-start}.fixed-top{position:relative}.panel-caption,.figure-caption,figcaption{color:#666}}.code-copy-button{position:absolute;top:0;right:0;border:0;margin-top:5px;margin-right:5px;background-color:rgba(0,0,0,0);z-index:3}.code-copy-button:focus{outline:none}.code-copy-button-tooltip{font-size:.75em}pre.sourceCode:hover>.code-copy-button>.bi::before{display:inline-block;height:1rem;width:1rem;content:"";vertical-align:-0.125em;background-image:url('data:image/svg+xml,