tech: test tests using latest installations

* Bump version: 1.1.1 → 1.1.2-rc.0

* fix: release candidate 1.1.2

* Bump version: 1.1.2-rc.0 → 1.1.2

* promote

---------

Co-authored-by: atarashansky <atarashansky@CZIMACOS3990.hsd1.ma.comcast.net>

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 1.0.0
+current_version = 1.1.2
 commit = True
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(?:-(?P<prerel>rc)\.(?P<prerelversion>\d+))?
 serialize = 

.github/ISSUE_TEMPLATE/tech-issue.md

@@ -0,0 +1,23 @@
+---
+name: Tech Issue
+about: Engineering-specific technical work that is not product-specific. Engineering team "owns" these issues.
+title: ""
+labels: tech
+assignees: ""
+---
+
+## Motivation
+
+Why is this work important to engineers?
+
+## Definition of Done
+
+What should the end result look like? What will have been changed?
+
+## Tasks
+
+Detail the specific tasks that can be used to accomplish the desired changes.
+If detailed steps cannot be provided at this time, please file a [Tech Proposal](https://docs.google.com/document/d/1o2vuvl-kXwRJN1nBoPzJS_MAQgDGYnjmPZWa4qRDi-I/edit#heading=h.7dvzhm7gqc3v) instead.
+
+- [ ]
+- [ ]

.github/workflows/close-stale-prs.yml

@@ -0,0 +1,23 @@
+name: Close inactive pull requests
+on:
+  schedule:
+    - cron: "30 1 * * *"
+
+jobs:
+  close-issues:
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
+    steps:
+      - uses: actions/stale@v5
+        with:
+          days-before-issue-stale: -1 # Do not mark any issues as stale
+          days-before-pr-stale: 14
+          days-before-pr-close: 3
+          stale-pr-message: "This PR has not seen any activity in the past 2 weeks; if no one comments or reviews it in the next 3 days, this PR will be closed."
+          close-pr-message: "This PR was closed because it has been inactive for 17 days, 3 days since being marked as stale. Please re-open if you still need this to be addressed."
+          stale-pr-label: "stale"
+          close-pr-label: "autoclosed"
+          exempt-draft-pr: true
+          repo-token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/compatibility_tests.yml

@@ -16,7 +16,7 @@ jobs:
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v1
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Build docker image
@@ -56,7 +56,7 @@ jobs:
     steps:
     - uses: actions/checkout@v2
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v1
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
     - name: Cache env vars

.github/workflows/lint-pr-commit-message.yml

@@ -0,0 +1,19 @@
+
+name: "Lint PR commit message"
+
+on:
+  pull_request_target:
+    types:
+      - opened
+      - edited
+      - synchronize
+
+jobs:
+  main:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: amannn/action-semantic-pull-request@v3.4.1
+        with:
+          validateSingleCommit: true
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/push_tests.yml

@@ -18,7 +18,7 @@ jobs:
       - run: |
           git fetch --depth=1 origin +${{github.base_ref}}
       - name: Set up Python 3.7
-        uses: actions/setup-python@v1
+        uses: actions/setup-python@v4
         with:
           python-version: 3.7
       - name: Node cache
@@ -46,10 +46,12 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
-      - name: Set up Python 3.7
-        uses: actions/setup-python@v1
+      - name: Set up Python 3.7 (pyenv)  # pyenv needed for mlflow in cli annotate tests
+        uses: gabrielfalcao/pyenv-action@v9
         with:
-          python-version: 3.7
+          default: 3.7
+          command: pip install -U pip  # upgrade pip after installing python
+      - run: pip install virtualenv  # virtualenv needed for mlflow in cli annotate tests
       - name: Python cache
         uses: actions/cache@v1
         with:
@@ -78,7 +80,7 @@ jobs:
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python 3.7
-        uses: actions/setup-python@v1
+        uses: actions/setup-python@v4
         with:
           python-version: 3.7
       - name: Python cache
@@ -102,32 +104,33 @@ jobs:
           cd client && make smoke-test
           ./node_modules/codecov/bin/codecov --yml=../.codecov.yml --root=../ --gcov-root=../ -C -F frontend,javascript,smokeTest
 
-  smoke-tests-annotations:
-    runs-on: ubuntu-latest
-    timeout-minutes: 20
-    steps:
-      - uses: actions/checkout@v2
-      - name: Set up Python 3.7
-        uses: actions/setup-python@v1
-        with:
-          python-version: 3.7
-      - name: Python cache
-        uses: actions/cache@v1
-        with:
-          path: ~/.cache/pip
-          key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements*.txt') }}
-          restore-keys: |
-            ${{ runner.os }}-pip-
-      - name: Node cache
-        uses: actions/cache@v1
-        with:
-          path: ~/.npm
-          key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}
-          restore-keys: |
-            ${{ runner.os }}-node-
-      - name: Install dependencies
-        run: make pydist install-dist
-      - name: Smoke tests (with annotations feature)
-        run: |
-          cd client && make smoke-test-annotations
-          ./node_modules/codecov/bin/codecov --yml=../.codecov.yml --root=../ --gcov-root=../ -C -F frontend,javascript,smokeTestAnnotations
+  # TODO: reinstate: https://github.com/chanzuckerberg/cellxgene/issues/2544
+  # smoke-tests-annotations:
+  #   runs-on: ubuntu-latest
+  #   timeout-minutes: 20
+  #   steps:
+  #     - uses: actions/checkout@v2
+  #     - name: Set up Python 3.7
+  #       uses: actions/setup-python@v4
+  #       with:
+  #         python-version: 3.7
+  #     - name: Python cache
+  #       uses: actions/cache@v1
+  #       with:
+  #         path: ~/.cache/pip
+  #         key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements*.txt') }}
+  #         restore-keys: |
+  #           ${{ runner.os }}-pip-
+  #     - name: Node cache
+  #       uses: actions/cache@v1
+  #       with:
+  #         path: ~/.npm
+  #         key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}
+  #         restore-keys: |
+  #           ${{ runner.os }}-node-
+  #     - name: Install dependencies
+  #       run: make pydist install-dist
+  #     - name: Smoke tests (with annotations feature)
+  #       run: |
+  #         cd client && make smoke-test-annotations
+  #         ./node_modules/codecov/bin/codecov --yml=../.codecov.yml --root=../ --gcov-root=../ -C -F frontend,javascript,smokeTestAnnotations

.gitignore

@@ -54,3 +54,6 @@ client/.eslintcache
 
 # E2E Testing
 ignoreE2E*
+
+# annotate subcmd
+.models_cache

LICENSE.txt

@@ -1,6 +1,6 @@
 The MIT License (MIT)
 
-Copyright (c) 2017-2021 Chan Zuckerberg Initiative
+Copyright (c) 2017-2023 Chan Zuckerberg Initiative
 
 Permission is hereby granted, free of charge, to any person obtaining a copy of
 this software and associated documentation files (the "Software"), to deal in

MANIFEST.in

@@ -3,5 +3,6 @@ recursive-include server/common/web/static *
 
 include server/requirements.txt
 include server/requirements-prepare.txt
+include server/requirements-annotate.txt
 include server/converters/schema/hgnc_complete_set.txt.gz
 include server/converters/schema/schema_definitions/*

README-visium.md

@@ -1,20 +0,0 @@
-# Cellxgene Visium Beta
-
-## How it works
-1. Launch `cellxgene` as normal. 
-1. If the loaded dataset has spatial information available, the image data will be loaded on startup.
-1. On the toolbar, next to the Zoom icon, a `Toggle image` button will now appear. Click on it and the image will be added as an underlay.
-1. You can now use any `cellxgene` functionality and the image will still be present. If you pan and zoom, the image will also be panned and zoomed.
-1. If you want to hide the image, you can click on `Toggle image` again
-
-In order for the image to be displayed with the correct size and alignment, the H5AD needs to have a few requirements. See the following section to learn more.
-
-## h5ad requirements
-1. The spatial embedding layer should be contained in `obsm` and be named `X_spatial`. Other layers can exist, but only this one will have the spatial feature enabled.
-2. A `spatial` dict needs to be defined in the `uns` dictionary.
-3. Inside the `spatial` dict, an `images` dict must be defined. 
-4. The `images` dict must contain a `hires` key, which should reference an image encoded as an RGB matrix (i.e., a three-dimensional matrix of size `height x width x 3` where the final dimension has the RGB values for each pixel)
-5. The `images` dict must contain a `scalefactors` dict. This should in turn contain a `tissue_hires_scalef` key, which should reference a floating point number.
-
-Moreover, in order to have the image correctly aligned with the dots, the following must be true:
-1. `tissue_hires_scalef` should represent the ratio between the embedding layer `X_spatial` and the image matrix. In particular, if you multiply `X_spatial` by `tissue_hires_scalef`, you should obtain an array of points that ovelap the tissue image if you plot them in a plane.

README.md

@@ -7,27 +7,27 @@ _an interactive explorer for single-cell transcriptomics data_
 [![Compatibility Tests](https://github.com/chanzuckerberg/cellxgene/workflows/Compatibility%20Tests/badge.svg)](https://github.com/chanzuckerberg/cellxgene/actions?query=workflow%3A%22Compatibility+Tests%22)
 ![Code Coverage](https://codecov.io/gh/chanzuckerberg/cellxgene/branch/main/graph/badge.svg)
 
-cellxgene Desktop (pronounced "cell-by-gene") is an interactive data explorer for single-cell datasets, such as those coming from the [Human Cell Atlas](https://humancellatlas.org). Leveraging modern web development techniques to enable fast visualizations of at least 1 million cells, we hope to enable biologists and computational researchers to explore their data.
+CZ CELLxGENE Annotate (pronounced "cell-by-gene") is an interactive data explorer for single-cell datasets, such as those coming from the [Human Cell Atlas](https://humancellatlas.org). Leveraging modern web development techniques to enable fast visualizations of at least 1 million cells, we hope to enable biologists and computational researchers to explore their data.
 
-Whether you need to visualize one thousand cells or one million, cellxgene Desktop helps you gain insight into your single-cell data.
+Whether you need to visualize one thousand cells or one million, CELLxGENE Annotate helps you gain insight into your single-cell data.
 
 <img src="https://github.com/chanzuckerberg/cellxgene/raw/main/docs/images/crossfilter.gif" width="350" height="200" hspace="30"><img src="https://github.com/chanzuckerberg/cellxgene/raw/main/docs/images/category-breakdown.gif" width="350" height="200" hspace="30">
 
 # Getting started
 
-### The comprehensive guide to cellxgene Desktop
+### The comprehensive guide to CZ CELLxGENE Annotate
 
-[The cellxgene documentation is your one-stop-shop for information about cellxgene Desktop](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/README.md)! You may be particularly interested in:
+[The CZ CELLxGENE Annotate documentation is your one-stop-shop for information about CELLxGENE Annotate](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/README.md)! You may be particularly interested in:
 
-- Seeing [what cellxgene Desktop can do](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/explore-data/explorer-tutorials.md)
-- Learning more about cellxgene [installation](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/install.md) and [usage](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/quick-start.md#quick-start-1)
-- [Preparing your own data](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/data-reqs.md) for use in cellxgene Desktop
+- Seeing [what Annotate can do](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/explore-data/explorer-tutorials.md)
+- Learning more about Annotate [installation](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/install.md) and [usage](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/quick-start.md#quick-start-1)
+- [Preparing your own data](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/data-reqs.md) for use in Annotate
 - Checking out [our roadmap](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/roadmap.md) for future development
-- [Contributing](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/contribute.md) to cellxgene Desktop
+- [Contributing](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/contribute.md) to Annotate
 
 ### Quick start
 
-To install cellxgene Desktop you need Python 3.6+. We recommend [installing cellxgene Desktop into a conda or virtual environment.](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/install.md)
+To install CELLxGENE Annotate you need Python 3.6+. We recommend [installing Annotate into a conda or virtual environment.](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/install.md)
 
 Install the package.
 
@@ -35,19 +35,19 @@ Install the package.
 pip install cellxgene
 ```
 
-Launch cellxgene Desktop with an example [anndata](https://anndata.readthedocs.io/en/latest/) file
+Launch Annotate with an example [anndata](https://anndata.readthedocs.io/en/latest/) file
 
 ```bash
 cellxgene launch https://cellxgene-example-data.czi.technology/pbmc3k.h5ad
 ```
 
-To explore more datasets already formatted for cellxgene Desktop, check out the [Demo data](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/quick-start.md#example-datasets) or
+To explore more datasets already formatted for Annotate, check out the [Demo data](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/quick-start.md#example-datasets) or
 see [Preparing your data](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/desktop/data-reqs.md) to learn more about formatting your own
-data for cellxgene Desktop.
+data for CELLxGENE Annotate.
 
 ### Supported browsers
 
-cellxgene Desktop currently supports the following browsers:
+CELLxGENE Annotate currently supports the following browsers:
 
 - Google Chrome 61+
 - Edge 15+
@@ -62,11 +62,11 @@ For questions, suggestions, or accolades, [join the `#cellxgene-users` channel o
 
 For any errors, [report bugs on Github](https://github.com/chanzuckerberg/cellxgene/issues).
 
-# Developing with cellxgene Desktop
+# Developing with CZ CELLxGENE Annotate
 
 ### Contributing
 
-We warmly welcome contributions from the community! Please see our [contributing guide](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/contribute.md) and don't hesitate to open an issue or send a pull request to improve cellxgene Desktop. Please see the [dev_docs](https://github.com/chanzuckerberg/cellxgene/tree/main/dev_docs) for pull request suggestions, unit test details, local documentation preview, and other development specifics. 
+We warmly welcome contributions from the community! Please see our [contributing guide](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/contribute.md) and don't hesitate to open an issue or send a pull request to improve CELLxGENE Annotate. Please see the [dev_docs](https://github.com/chanzuckerberg/cellxgene/tree/main/dev_docs) for pull request suggestions, unit test details, local documentation preview, and other development specifics. 
 
 This project adheres to the Contributor Covenant [code of conduct](https://github.com/chanzuckerberg/.github/blob/master/CODE_OF_CONDUCT.md). By participating, you are expected to uphold this code. Please report unacceptable behavior to opensource@chanzuckerberg.com.
 
@@ -77,11 +77,11 @@ As such, we encourage other scientific tool builders in academia or industry to
 this project. All code is freely available for reuse under the [MIT license](https://opensource.org/licenses/MIT).
 
 
-Before extending cellxgene, we encourage you to reach out to us with ideas or questions. It might be possible that an 
+Before extending CELLxGENE Annotate, we encourage you to reach out to us with ideas or questions. It might be possible that an 
 extension could be directly contributed, which would make it available for a wider audience, or that it's on our 
 [roadmap](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/roadmap.md) and under active development. 
 
-See the [cellxgene extensions](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/community-extensions.md) section of our documentation for examples of community use and cellxgene extensions. 
+See the [CELLxGENE extensions](https://github.com/chanzuckerberg/cellxgene-documentation/blob/main/community-extensions.md) section of our documentation for examples of community use and CELLxGENE extensions. 
 
 ### Security
 

client/__tests__/e2e/__snapshots__/e2e.test.js.snap

@@ -2,4 +2,4 @@
 
 exports[`did launch page launched 1`] = `"<span style=\\"max-width: 155px; display: flex; overflow: hidden; justify-content: flex-start; width: 100%; padding: 0px;\\"><span style=\\"overflow: hidden; text-overflow: ellipsis; white-space: nowrap; flex-shrink: 1; min-width: 5px;\\">pbm</span><span style=\\"position: relative; overflow: hidden; white-space: nowrap;\\"><span style=\\"color: transparent;\\">c3k</span><span style=\\"position: absolute; right: 0px; color: inherit;\\">c3k</span></span></span>"`;
 
-exports[`metadata loads categories and values from dataset appear 1`] = `"<div style=\\"display: flex; justify-content: space-between; align-items: baseline;\\"><div style=\\"display: flex; justify-content: flex-start; align-items: flex-start;\\"><label class=\\"bp3-control bp3-checkbox\\" for=\\"category-select-louvain\\"><input id=\\"category-select-louvain\\" data-testclass=\\"category-select\\" data-testid=\\"louvain:category-select\\" type=\\"checkbox\\" checked=\\"\\"><span class=\\"bp3-control-indicator\\"></span></label><span role=\\"menuitem\\" tabindex=\\"0\\" data-testclass=\\"category-expand\\" data-testid=\\"louvain:category-expand\\" style=\\"cursor: pointer;\\"><span aria-haspopup=\\"true\\" class=\\"bp3-popover2-target\\"><span data-testid=\\"louvain:category-label\\" tabindex=\\"-1\\" aria-label=\\"louvain\\" class=\\"\\" style=\\"max-width: 265px;\\"><span style=\\"max-width: 265px; display: flex; overflow: hidden; justify-content: flex-start; width: 100%; padding: 0px;\\"><span style=\\"overflow: hidden; text-overflow: ellipsis; white-space: nowrap; flex-shrink: 1; min-width: 5px;\\">lou</span><span style=\\"position: relative; overflow: hidden; white-space: nowrap;\\"><span style=\\"color: transparent;\\">vain</span><span style=\\"position: absolute; right: 0px; color: inherit;\\">vain</span></span></span></span></span><svg stroke=\\"currentColor\\" fill=\\"currentColor\\" stroke-width=\\"0\\" viewBox=\\"0 0 320 512\\" data-testclass=\\"category-expand-is-not-expanded\\" height=\\"1em\\" width=\\"1em\\" xmlns=\\"http://www.w3.org/2000/svg\\" style=\\"font-size: 10px; margin-left: 5px;\\"><path d=\\"M285.476 272.971L91.132 467.314c-9.373 9.373-24.569 9.373-33.941 0l-22.667-22.667c-9.357-9.357-9.375-24.522-.04-33.901L188.505 256 34.484 101.255c-9.335-9.379-9.317-24.544.04-33.901l22.667-22.667c9.373-9.373 24.569-9.373 33.941 0L285.475 239.03c9.373 9.372 9.373 24.568.001 33.941z\\"></path></svg></span></div><div><span class=\\"bp3-popover-wrapper\\"><span aria-haspopup=\\"true\\" class=\\"bp3-popover-target\\"><a role=\\"button\\" data-testclass=\\"colorby\\" data-testid=\\"colorby-louvain\\" class=\\"bp3-button\\" tabindex=\\"0\\"><span icon=\\"tint\\" class=\\"bp3-icon bp3-icon-tint\\"><svg data-icon=\\"tint\\" width=\\"16\\" height=\\"16\\" viewBox=\\"0 0 16 16\\"><desc>tint</desc><path d=\\"M7.88 1s-4.9 6.28-4.9 8.9c.01 2.82 2.34 5.1 4.99 5.1 2.65-.01 5.03-2.3 5.03-5.13C12.99 7.17 7.88 1 7.88 1z\\" fill-rule=\\"evenodd\\"></path></svg></span></a></span></span></div></div><div style=\\"margin-left: 26px;\\"></div>"`;
+exports[`metadata loads categories and values from dataset appear 1`] = `"<div style=\\"display: flex; justify-content: space-between; align-items: baseline;\\"><div style=\\"display: flex; justify-content: flex-start; align-items: flex-start;\\"><label class=\\"bp3-control bp3-checkbox\\" for=\\"category-select-louvain\\"><input id=\\"category-select-louvain\\" data-testclass=\\"category-select\\" data-testid=\\"louvain:category-select\\" type=\\"checkbox\\" checked=\\"\\"><span class=\\"bp3-control-indicator\\"></span></label><span role=\\"menuitem\\" tabindex=\\"0\\" data-testclass=\\"category-expand\\" data-testid=\\"louvain:category-expand\\" style=\\"cursor: pointer;\\"><span aria-haspopup=\\"true\\" class=\\"bp3-popover2-target\\"><span data-testid=\\"louvain:category-label\\" tabindex=\\"-1\\" aria-label=\\"louvain\\" class=\\"\\" style=\\"max-width: 265px;\\"><span style=\\"max-width: 265px; display: flex; overflow: hidden; justify-content: flex-start; width: 100%; padding: 0px;\\"><span style=\\"overflow: hidden; text-overflow: ellipsis; white-space: nowrap; flex-shrink: 1; min-width: 5px;\\">lou</span><span style=\\"position: relative; overflow: hidden; white-space: nowrap;\\"><span style=\\"color: transparent;\\">vain</span><span style=\\"position: absolute; right: 0px; color: inherit;\\">vain</span></span></span></span></span><svg stroke=\\"currentColor\\" fill=\\"currentColor\\" stroke-width=\\"0\\" viewBox=\\"0 0 320 512\\" data-testclass=\\"category-expand-is-not-expanded\\" height=\\"1em\\" width=\\"1em\\" xmlns=\\"http://www.w3.org/2000/svg\\" style=\\"font-size: 10px; margin-left: 5px;\\"><path d=\\"M285.476 272.971L91.132 467.314c-9.373 9.373-24.569 9.373-33.941 0l-22.667-22.667c-9.357-9.357-9.375-24.522-.04-33.901L188.505 256 34.484 101.255c-9.335-9.379-9.317-24.544.04-33.901l22.667-22.667c9.373-9.373 24.569-9.373 33.941 0L285.475 239.03c9.373 9.372 9.373 24.568.001 33.941z\\"></path></svg></span></div><div><span class=\\"bp3-popover-wrapper\\"><span aria-haspopup=\\"true\\" class=\\"bp3-popover-target\\"><a role=\\"button\\" data-testclass=\\"colorby\\" data-testid=\\"colorby-louvain\\" class=\\"bp3-button\\" tabindex=\\"0\\"><span icon=\\"tint\\" aria-hidden=\\"true\\" tabindex=\\"0\\" class=\\"bp3-icon bp3-icon-tint\\"><svg data-icon=\\"tint\\" width=\\"16\\" height=\\"16\\" viewBox=\\"0 0 16 16\\"><path d=\\"M7.88 1s-4.9 6.28-4.9 8.9c.01 2.82 2.34 5.1 4.99 5.1 2.65-.01 5.03-2.3 5.03-5.13C12.99 7.17 7.88 1 7.88 1z\\" fill-rule=\\"evenodd\\"></path></svg></span></a></span></span></div></div><div style=\\"margin-left: 26px;\\"></div>"`;

client/configuration/webpack/webpack.config.dev.js

@@ -1,8 +1,6 @@
 const path = require("path");
 const webpack = require("webpack");
 const HtmlWebpackPlugin = require("html-webpack-plugin");
-const FaviconsWebpackPlugin = require("favicons-webpack-plugin");
-const ScriptExtHtmlWebpackPlugin = require("script-ext-html-webpack-plugin");
 const MiniCssExtractPlugin = require("mini-css-extract-plugin");
 
 const { merge } = require("webpack-merge");
@@ -11,6 +9,7 @@ const sharedConfig = require("./webpack.config.shared");
 const babelOptions = require("../babel/babel.dev");
 
 const fonts = path.resolve("src/fonts");
+const images = path.resolve("src/images");
 const nodeModules = path.resolve("node_modules");
 
 const devConfig = {
@@ -30,11 +29,11 @@ const devConfig = {
       {
         test: /\.(jpg|png|gif|eot|svg|ttf|woff|woff2|otf)$/i,
         loader: "file-loader",
-        include: [nodeModules, fonts],
+        include: [nodeModules, fonts, images],
         options: {
           name: "static/assets/[name].[ext]",
           // (thuang): This is needed to make sure @font url path is '/static/assets/'
-          publicPath: "/",
+          publicPath: "..",
         },
       },
     ],
@@ -44,21 +43,6 @@ const devConfig = {
       inject: true,
       template: path.resolve("index.html"),
     }),
-    new FaviconsWebpackPlugin({
-      logo: "./favicon.png",
-      prefix: "static/img/",
-      favicons: {
-        icons: {
-          android: false,
-          appleIcon: false,
-          appleStartup: false,
-          coast: false,
-          firefox: false,
-          windows: false,
-          yandex: false,
-        },
-      },
-    }),
     new MiniCssExtractPlugin({
       filename: "static/[name].css",
     }),
@@ -73,9 +57,6 @@ const devConfig = {
         CXG_SERVER_PORT: process.env.CXG_SERVER_PORT || "5005",
       }),
     }),
-    new ScriptExtHtmlWebpackPlugin({
-      async: "obsolete",
-    }),
   ],
   infrastructureLogging: {
     level: "warn",

client/configuration/webpack/webpack.config.prod.js

@@ -3,9 +3,7 @@ const webpack = require("webpack");
 const HtmlWebpackPlugin = require("html-webpack-plugin");
 const { CleanWebpackPlugin } = require("clean-webpack-plugin");
 const TerserJSPlugin = require("terser-webpack-plugin");
-const CleanCss = require("clean-css");
-const OptimizeCSSAssetsPlugin = require("optimize-css-assets-webpack-plugin");
-const FaviconsWebpackPlugin = require("favicons-webpack-plugin");
+const CssMinimizerPlugin = require("css-minimizer-webpack-plugin");
 const MiniCssExtractPlugin = require("mini-css-extract-plugin");
 
 const { merge } = require("webpack-merge");
@@ -16,6 +14,7 @@ const CspHashPlugin = require("./cspHashPlugin");
 const sharedConfig = require("./webpack.config.shared");
 
 const fonts = path.resolve("src/fonts");
+const images = path.resolve("src/images");
 const nodeModules = path.resolve("node_modules");
 
 const prodConfig = {
@@ -29,8 +28,8 @@ const prodConfig = {
     minimize: true,
     minimizer: [
       new TerserJSPlugin({}),
-      new OptimizeCSSAssetsPlugin({
-        cssProcessor: CleanCss,
+      new CssMinimizerPlugin({
+        minify: CssMinimizerPlugin.cleanCssMinify,
       }),
     ],
   },
@@ -45,11 +44,11 @@ const prodConfig = {
       {
         test: /\.(jpg|png|gif|eot|svg|ttf|woff|woff2|otf)$/i,
         loader: "file-loader",
-        include: [nodeModules, fonts],
+        include: [nodeModules, fonts, images],
         options: {
           name: "static/assets/[name]-[contenthash].[ext]",
           // (thuang): This is needed to make sure @font url path is '../static/assets/'
-          publicPath: "static/",
+          publicPath: "..",
         },
       },
     ],
@@ -66,21 +65,6 @@ const prodConfig = {
       protectWebpackAssets: false,
       cleanAfterEveryBuildPatterns: ["main.js", "main.css"],
     }),
-    new FaviconsWebpackPlugin({
-      logo: "./favicon.png",
-      prefix: "static/assets/",
-      favicons: {
-        icons: {
-          android: false,
-          appleIcon: false,
-          appleStartup: false,
-          coast: false,
-          firefox: false,
-          windows: false,
-          yandex: false,
-        },
-      },
-    }),
     new MiniCssExtractPlugin({
       filename: "static/[name]-[contenthash].css",
     }),

client/configuration/webpack/webpack.config.shared.js

@@ -2,8 +2,6 @@ const path = require("path");
 const fs = require("fs");
 const MiniCssExtractPlugin = require("mini-css-extract-plugin");
 const ObsoleteWebpackPlugin = require("obsolete-webpack-plugin");
-// eslint-disable-next-line @blueprintjs/classes-constants -- incorrect match
-const ScriptExtHtmlWebpackPlugin = require("script-ext-html-webpack-plugin");
 
 const src = path.resolve("src");
 const nodeModules = path.resolve("node_modules");
@@ -67,8 +65,5 @@ module.exports = {
       template: obsoleteHTMLTemplate,
       promptOnNonTargetBrowser: false,
     }),
-    new ScriptExtHtmlWebpackPlugin({
-      async: "obsolete",
-    }),
   ],
 };

client/index.html

@@ -3,7 +3,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1" />
-    <title>cell&times;gene</title>
+    <title>CELL&times;GENE | Annotate</title>
     <style>
       html,
       body,

client/index_template.html

@@ -3,7 +3,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1" />
-    <title>cell&times;gene</title>
+    <title>CELL&times;GENE | Annotate</title>
     <style>
       html,
       body,

client/package.json

@@ -1,6 +1,6 @@
 {
   "name": "cellxgene",
-  "version": "1.0.0",
+  "version": "1.1.2",
   "license": "MIT",
   "description": "cellxgene is a web application for the interactive exploration of single cell sequence data.",
   "repository": "https://github.com/chanzuckerberg/cellxgene",
@@ -101,6 +101,7 @@
     "clean-webpack-plugin": "^4.0.0-alpha.0",
     "codecov": "^3.7.1",
     "css-loader": "^5.2.4",
+    "css-minimizer-webpack-plugin": "^4.0.0",
     "eslint": "^7.24.0",
     "eslint-config-airbnb": "^18.2.0",
     "eslint-config-prettier": "^8.2.0",
@@ -114,8 +115,6 @@
     "eslint-plugin-react-hooks": "^4.0.8",
     "expect-puppeteer": "^5.0.0",
     "express": "^4.17.1",
-    "favicons": "^6.2.2",
-    "favicons-webpack-plugin": "^5.0.2",
     "file-loader": "^6.0.0",
     "html-webpack-plugin": "^5.3.1",
     "husky": "^7.0.2",
@@ -134,11 +133,9 @@
     "lodash.zip": "^4.2.0",
     "mini-css-extract-plugin": "^1.5.0",
     "obsolete-webpack-plugin": "^0.5.6",
-    "optimize-css-assets-webpack-plugin": "^5.0.3",
     "prettier": "^2.0.5",
     "puppeteer": "^8.0.0",
     "rimraf": "^3.0.2",
-    "script-ext-html-webpack-plugin": "^2.1.4",
     "serve-favicon": "^2.5.0",
     "terser-webpack-plugin": "^5.1.1",
     "webpack": "^5.34.0",

client/src/actions/index.js

@@ -8,7 +8,6 @@ import {
 import { loadUserColorConfig } from "../util/stateManager/colorHelpers";
 import * as selnActions from "./selection";
 import * as annoActions from "./annotation";
-import * as spatialActions from "./spatial";
 import * as viewActions from "./viewStack";
 import * as embActions from "./embedding";
 import * as genesetActions from "./geneset";
@@ -273,5 +272,4 @@ export default {
   genesetDelete: genesetActions.genesetDelete,
   genesetAddGenes: genesetActions.genesetAddGenes,
   genesetDeleteGenes: genesetActions.genesetDeleteGenes,
-  requestSpatialMetadata: spatialActions.requestSpatialMetadata,
 };

client/src/actions/spatial.js

@@ -1,35 +0,0 @@
-import * as globals from "../globals";
-
-export const requestSpatialMetadata = () => async (dispatch) => {
-  dispatch({ type: "request spatial metadata started" });
-  try {
-    const res = await fetch(
-      `${globals.API.prefix}${globals.API.version}spatial/meta`,
-      {
-        method: "GET",
-        headers: new Headers({
-          Accept: "application/json",
-          "Content-Type": "application/json",
-        }),
-        credentials: "include",
-      }
-    );
-
-    if (!res.ok || res.headers.get("Content-Type") !== "application/json") {
-      return null; // TODO need a dispatch //dispatchDiffExpErrors(dispatch, res);
-    }
-
-    const response = await res.json();
-
-    /* then send the success case action through */
-    return dispatch({
-      type: "request spatial metadata success",
-      data: response,
-    });
-  } catch (error) {
-    return dispatch({
-      type: "request spatial metadata error",
-      error,
-    });
-  }
-};

client/src/annoMatrix/viewCreators.js

@@ -58,10 +58,11 @@ function _maskToList(mask) {
   if (!mask) {
     return null;
   }
-  const list = new Int32Array(mask.length);
+  const [...m] = mask;
+  const list = new Int32Array(m.length);
   let elems = 0;
-  for (let i = 0, l = mask.length; i < l; i += 1) {
-    if (mask[i]) {
+  for (let i = 0, l = m.length; i < l; i += 1) {
+    if (m[i]) {
       list[elems] = i;
       elems += 1;
     }

client/src/annoMatrix/whereCache.js

@@ -91,12 +91,9 @@ export function _whereCacheCreate(field, query, columnLabels) {
 	*/
   if (typeof query !== "object") return null;
 
-  if (query.where) {
-    const {
-      field: queryField,
-      column: queryColumn,
-      value: queryValue,
-    } = query.where;
+  const { where, summarize } = query;
+  if (where) {
+    const { field: queryField, column: queryColumn, value: queryValue } = where;
     return {
       where: {
         [field]: {
@@ -107,13 +104,13 @@ export function _whereCacheCreate(field, query, columnLabels) {
       },
     };
   }
-  if (query.summarize) {
+  if (summarize) {
     const {
       method,
       field: queryField,
       column: queryColumn,
       values: queryValues,
-    } = query.summarize;
+    } = summarize;
     const queryValueHash = _hashStringValues(queryValues);
     return {
       summarize: {

client/src/components/app.js

@@ -23,8 +23,6 @@ class App extends React.Component {
   componentDidMount() {
     const { dispatch } = this.props;
 
-    dispatch(actions.requestSpatialMetadata());
-
     /* listen for url changes, fire one when we start the app up */
     window.addEventListener("popstate", this._onURLChanged);
     this._onURLChanged();
@@ -43,7 +41,7 @@ class App extends React.Component {
     const { loading, error, graphRenderCounter } = this.props;
     return (
       <Container>
-        <Helmet title="cellxgene" />
+        <Helmet title="CELL&times;GENE | Annotate" />
         {loading ? (
           <div
             style={{

client/src/components/embedding/index.js

@@ -16,11 +16,10 @@ import actions from "../../actions";
 import { getDiscreteCellEmbeddingRowIndex } from "../../util/stateManager/viewStackHelpers";
 
 @connect((state) => ({
-  imageUnderlay: state.imageUnderlay,
-  layoutChoice: state.layoutChoice, // TODO: really should clean up naming, s/layout/embedding/g
-  schema: state.annoMatrix?.schema,
-  crossfilter: state.obsCrossfilter,
-}))
+    layoutChoice: state.layoutChoice, // TODO: really should clean up naming, s/layout/embedding/g
+    schema: state.annoMatrix?.schema,
+    crossfilter: state.obsCrossfilter,
+  }))
 class Embedding extends React.PureComponent {
   constructor(props) {
     super(props);
@@ -28,18 +27,8 @@ class Embedding extends React.PureComponent {
   }
 
   handleLayoutChoiceChange = (e) => {
-    const { dispatch, imageUnderlay } = this.props;
+    const { dispatch } = this.props;
     dispatch(actions.layoutChoiceAction(e.currentTarget.value));
-
-    // if we just switched off spatial, if the image is on, turn it off
-    if (
-      imageUnderlay.isActive &&
-      e.target.value !== globals.spatialEmbeddingKeyword
-    ) {
-      dispatch({
-        type: "toggle image underlay",
-      });
-    }
   };
 
   render() {

client/src/components/framework/logo.js

@@ -1,17 +1,15 @@
 import React from "react";
-import * as globals from "../../globals";
+import icon from "../../images/icon.png";
 
 const Logo = (props) => {
   const { size } = props;
   return (
-    <svg width={size} height={size} viewBox="0 0 48 48" fill="none">
-      <rect width="48" height="48" fill="white" />
-      <rect width="48" height="48" fill={globals.logoColor} />
-      <rect x="19" y="19" width="22" height="22" fill="white" />
-      <rect x="24" y="24" width="12" height="12" fill={globals.logoColor} />
-      <rect x="7" y="19" width="7" height="22" fill="white" />
-      <rect x="19" y="7" width="22" height="7" fill="white" />
-    </svg>
+    <img
+      src={icon}
+      height={size}
+      width={size}
+      alt="CELLxGENE Annotate Logo"
+     />
   );
 };
 

client/src/components/graph/drawSpatialImageRegl.js

@@ -1,62 +0,0 @@
-export default function drawSpatialImageRegl(regl) {
-  return regl({
-    frag: `
-        precision mediump float;
-
-        // our texture
-        uniform sampler2D u_image;
-
-        // the texCoords passed in from the vertex shader.
-        varying vec2 v_texCoord;
-
-        void main() {
-            gl_FragColor = texture2D(u_image, v_texCoord);
-        }`,
-
-    vert: `
-        attribute vec2 a_position;
-        attribute vec2 a_texCoord;
-
-        uniform vec2 u_resolution;
-
-        uniform mat3 projView;
-
-        varying vec2 v_texCoord;
-
-        void main() {
-            // convert the rectangle from pixels to 0.0 to 1.0
-            vec3 pos = vec3(a_position, 1.);
-            vec2 zeroToOne = pos.xy / u_resolution;
-
-            // convert from 0->1 to 0->2
-            vec2 zeroToTwo = zeroToOne * 2.0;
-
-            // convert from 0->2 to -1->+1 (clipspace)
-            vec2 clipSpace = zeroToTwo - 1.0;
-
-            vec3 pos2 = projView * vec3(clipSpace, 1.);
-
-            gl_Position = vec4(pos2.xy , 0, 1);
-
-            // pass the texCoord to the fragment shader
-            // The GPU will interpolate this value between points.
-            v_texCoord = a_texCoord;
-        }`,
-
-    attributes: {
-      a_texCoord: [0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0],
-      a_position: regl.prop("rectCoords"),
-    },
-
-    uniforms: {
-      projView: regl.prop("projView"),
-      u_image: regl.prop("spatialImageAsTexture"),
-      color: [1, 0, 0, 1],
-      u_resolution: [regl.prop("imageWidth"), regl.prop("imageHeight")],
-      image_width: regl.prop("imageWidth"),
-      //   translate:
-    },
-
-    count: 6,
-  });
-}

client/src/components/graph/graph.js

@@ -14,7 +14,6 @@ import {
   createColorTable,
   createColorQuery,
 } from "../../util/stateManager/colorHelpers";
-import _drawSpatialImage from "./drawSpatialImageRegl";
 import * as globals from "../../globals";
 
 import GraphOverlayLayer from "./overlays/graphOverlayLayer";
@@ -78,8 +77,6 @@ function createModelTF() {
   colors: state.colors,
   pointDilation: state.pointDilation,
   genesets: state.genesets.genesets,
-  spatial: state.spatial.metadata,
-  imageUnderlay: state.imageUnderlay,
 }))
 class Graph extends React.Component {
   static createReglState(canvas) {
@@ -90,7 +87,6 @@ class Graph extends React.Component {
     const camera = _camera(canvas);
     const regl = _regl(canvas);
     const drawPoints = _drawPoints(regl);
-    const drawSpatialImage = _drawSpatialImage(regl);
 
     // preallocate webgl buffers
     const pointBuffer = regl.buffer();
@@ -104,7 +100,6 @@ class Graph extends React.Component {
       pointBuffer,
       colorBuffer,
       flagBuffer,
-      drawSpatialImage,
     };
   }
 
@@ -237,8 +232,6 @@ class Graph extends React.Component {
       pointBuffer: null,
       colorBuffer: null,
       flagBuffer: null,
-      drawSpatialImage: null,
-      spatial: null,
 
       // component rendering derived state - these must stay synchronized
       // with the reducer state they were generated from.
@@ -324,10 +317,7 @@ class Graph extends React.Component {
     if (e.type !== "wheel") e.preventDefault();
     if (camera.handleEvent(e, projectionTF)) {
       this.renderCanvas();
-      this.setState((state) => ({
-        ...state,
-        updateOverlay: !state.updateOverlay,
-      }));
+      this.setState((state) => ({ ...state, updateOverlay: !state.updateOverlay }));
     }
   };
 
@@ -519,14 +509,6 @@ class Graph extends React.Component {
     return { toolSVG: newToolSVG, tool, container };
   };
 
-  loadTextureFromUrl = (src) =>
-    new Promise((resolve, reject) => {
-      const img = new Image();
-      img.onload = () => resolve(img);
-      img.onerror = reject;
-      img.src = src;
-    });
-
   fetchAsyncProps = async (props) => {
     const {
       annoMatrix,
@@ -535,8 +517,6 @@ class Graph extends React.Component {
       crossfilter,
       pointDilation,
       viewport,
-      spatial,
-      imageUnderlay,
     } = props.watchProps;
     const { modelTF } = this.state;
 
@@ -544,8 +524,7 @@ class Graph extends React.Component {
       annoMatrix,
       layoutChoice,
       colorsProp,
-      pointDilation,
-      imageUnderlay
+      pointDilation
     );
 
     const { currentDimNames } = layoutChoice;
@@ -572,10 +551,6 @@ class Graph extends React.Component {
       pointDilationLabel
     );
 
-    this.spatialImage = await this.loadTextureFromUrl(
-      "/api/v0.2/spatial/image"
-    );
-
     const { width, height } = viewport;
     return {
       positions,
@@ -583,8 +558,6 @@ class Graph extends React.Component {
       flags,
       width,
       height,
-      spatial,
-      imageUnderlay,
     };
   };
 
@@ -748,7 +721,6 @@ class Graph extends React.Component {
       flagBuffer,
       camera,
       projectionTF,
-      drawSpatialImage,
     } = this.state;
     this.renderPoints(
       regl,
@@ -757,14 +729,12 @@ class Graph extends React.Component {
       pointBuffer,
       flagBuffer,
       camera,
-      projectionTF,
-      drawSpatialImage
+      projectionTF
     );
   });
 
   updateReglAndRender(asyncProps, prevAsyncProps) {
-    const { positions, colors, flags, height, width, imageUnderlay } =
-      asyncProps;
+    const { positions, colors, flags, height, width } = asyncProps;
     this.cachedAsyncProps = asyncProps;
     const { pointBuffer, colorBuffer, flagBuffer } = this.state;
     let needToRenderCanvas = false;
@@ -784,9 +754,6 @@ class Graph extends React.Component {
       flagBuffer({ data: flags, dimension: 1 });
       needToRenderCanvas = true;
     }
-    if (imageUnderlay !== prevAsyncProps?.imageUnderlay) {
-      needToRenderCanvas = true;
-    }
     if (needToRenderCanvas) this.renderCanvas();
   }
 
@@ -830,25 +797,20 @@ class Graph extends React.Component {
     pointBuffer,
     flagBuffer,
     camera,
-    projectionTF,
-    drawSpatialImage
+    projectionTF
   ) {
-    const { annoMatrix, spatial, imageUnderlay } = this.props;
+    const { annoMatrix } = this.props;
     if (!this.reglCanvas || !annoMatrix) return;
 
     const { schema } = annoMatrix;
     const cameraTF = camera.view();
     const projView = mat3.multiply(mat3.create(), projectionTF, cameraTF);
     const { width, height } = this.reglCanvas;
-    const imW = spatial.data.imageWidth;
-    const imH = spatial.data.imageHeight;
-
     regl.poll();
     regl.clear({
       depth: 1,
-      color: [0, 0, 0, 0],
+      color: [1, 1, 1, 1],
     });
-
     drawPoints({
       distance: camera.distance(),
       color: colorBuffer,
@@ -859,19 +821,6 @@ class Graph extends React.Component {
       nPoints: schema.dataframe.nObs,
       minViewportDimension: Math.min(width, height),
     });
-    if (imageUnderlay?.isActive) {
-      drawSpatialImage({
-        projView,
-        imageWidth: imW,
-        imageHeight: imH,
-        rectCoords: [0, 0, imW, 0, 0, imH, 0, imH, imW, 0, imW, imH],
-        spatialImageAsTexture: regl.texture({
-          data: this.spatialImage,
-          wrapS: "clamp",
-          wrapT: "clamp",
-        }),
-      });
-    }
     regl._gl.flush();
   }
 
@@ -883,8 +832,6 @@ class Graph extends React.Component {
       layoutChoice,
       pointDilation,
       crossfilter,
-      spatial,
-      imageUnderlay,
     } = this.props;
     const { modelTF, projectionTF, camera, viewport, regl } = this.state;
     const cameraTF = camera?.view()?.slice();
@@ -955,8 +902,6 @@ class Graph extends React.Component {
             pointDilation,
             crossfilter,
             viewport,
-            spatial,
-            imageUnderlay,
           }}
         >
           <Async.Pending initial>
@@ -1006,29 +951,32 @@ const ErrorLoading = ({ displayName, error, width, height }) => {
   );
 };
 
-const StillLoading = ({ displayName, width, height }) => (
+const StillLoading = ({ displayName, width, height }) => 
   /*
   Render a busy/loading indicator
   */
-  <div
-    style={{
-      position: "fixed",
-      fontWeight: 500,
-      top: height / 2,
-      width,
-    }}
-  >
+   (
     <div
       style={{
-        display: "flex",
-        justifyContent: "center",
-        justifyItems: "center",
-        alignItems: "center",
+        position: "fixed",
+        fontWeight: 500,
+        top: height / 2,
+        width,
       }}
     >
-      <Button minimal loading intent="primary" />
-      <span style={{ fontStyle: "italic" }}>Loading {displayName}</span>
+      <div
+        style={{
+          display: "flex",
+          justifyContent: "center",
+          justifyItems: "center",
+          alignItems: "center",
+        }}
+      >
+        <Button minimal loading intent="primary" />
+        <span style={{ fontStyle: "italic" }}>Loading {displayName}</span>
+      </div>
     </div>
-  </div>
-);
+  )
+;
+
 export default Graph;

client/src/components/menubar/index.js

@@ -28,8 +28,6 @@ import { getEmbSubsetView } from "../../util/stateManager/viewStackHelpers";
     subsetPossible,
     subsetResetPossible,
     graphInteractionMode: state.controls.graphInteractionMode,
-    imageUnderlay: state.imageUnderlay,
-    layoutChoice: state.layoutChoice, // TODO: really should clean up naming, s/layout/embedding/g
     clipPercentileMin: Math.round(100 * (annoMatrix?.clipRange?.[0] ?? 0)),
     clipPercentileMax: Math.round(100 * (annoMatrix?.clipRange?.[1] ?? 1)),
     userDefinedGenes: state.controls.userDefinedGenes,
@@ -208,8 +206,6 @@ class MenuBar extends React.PureComponent {
       colorAccessor,
       subsetPossible,
       subsetResetPossible,
-      imageUnderlay,
-      layoutChoice,
     } = this.props;
     const { pendingClipPercentiles } = this.state;
 
@@ -272,29 +268,6 @@ class MenuBar extends React.PureComponent {
             disabled={!isColoredByCategorical}
           />
         </Tooltip>
-        {layoutChoice?.available?.includes(globals.spatialEmbeddingKeyword) && (
-          <ButtonGroup className={styles.menubarButton}>
-            <Tooltip
-              content={"Toggle image"}
-              position="bottom"
-              hoverOpenDelay={globals.tooltipHoverOpenDelay}
-            >
-              <AnchorButton
-                type="button"
-                data-testid="toggle-image-underlay"
-                icon={"media"}
-                intent={imageUnderlay.isActive ? "primary" : "none"}
-                active={imageUnderlay.isActive}
-                onClick={() => {
-                  dispatch({
-                    type: "toggle image underlay",
-                  });
-                }}
-              />
-            </Tooltip>
-          </ButtonGroup>
-        )}
-
         <ButtonGroup className={styles.menubarButton}>
           <Tooltip
             content={selectionTooltip}

client/src/globals.js

@@ -2,9 +2,6 @@ import { Colors } from "@blueprintjs/core";
 import { dispatchNetworkErrorMessageToUser } from "./util/actionHelpers";
 import ENV_DEFAULT from "../../environment.default.json";
 
-// visium embedding word, spatial image underlay
-export const spatialEmbeddingKeyword = "spatial";
-
 /* overflow category values are created  using this string */
 export const overflowCategoryLabel = ": all other labels";
 

client/src/reducers/imageUnderlay.js

@@ -1,14 +0,0 @@
-const imageUnderlay = (state = { isActive: false }, action) => {
-  switch (action.type) {
-    case "toggle image underlay":
-      return {
-        ...state,
-        isActive: !state.isActive,
-      };
-
-    default:
-      return state;
-  }
-};
-
-export default imageUnderlay;

client/src/reducers/index.js

@@ -11,7 +11,6 @@ import continuousSelection from "./continuousSelection";
 import graphSelection from "./graphSelection";
 import colors from "./colors";
 import differential from "./differential";
-import spatial from "./spatial";
 import layoutChoice from "./layoutChoice";
 import controls from "./controls";
 import annotations from "./annotations";
@@ -20,7 +19,6 @@ import genesetsUI from "./genesetsUI";
 import autosave from "./autosave";
 import centroidLabels from "./centroidLabels";
 import pointDialation from "./pointDilation";
-import imageUnderlay from "./imageUnderlay";
 import { gcMiddleware as annoMatrixGC } from "../annoMatrix";
 
 import undoableConfig from "./undoableConfig";
@@ -40,9 +38,7 @@ const Reducer = undoable(
     ["colors", colors],
     ["controls", controls],
     ["differential", differential],
-    ["spatial", spatial],
     ["centroidLabels", centroidLabels],
-    ["imageUnderlay", imageUnderlay],
     ["pointDilation", pointDialation],
     ["autosave", autosave],
   ]),
@@ -55,7 +51,6 @@ const Reducer = undoable(
     "colors",
     "controls",
     "differential",
-    "spatial",
     "layoutChoice",
     "centroidLabels",
     "genesets",

client/src/reducers/spatial.js

@@ -1,34 +0,0 @@
-const Spatial = (
-  state = {
-    loading: null,
-    error: null,
-    metadata: null,
-  },
-  action
-) => {
-  switch (action.type) {
-    case "request spatial metadata started":
-      return {
-        ...state,
-        loading: true,
-        error: null,
-      };
-    case "request spatial metadata success":
-      return {
-        ...state,
-        error: null,
-        loading: false,
-        metadata: action,
-      };
-    case "request spatial metadata error":
-      return {
-        ...state,
-        loading: false,
-        error: action.data,
-      };
-    default:
-      return state;
-  }
-};
-
-export default Spatial;

client/src/reducers/undoableConfig.js

@@ -52,9 +52,6 @@ const skipOnActions = new Set([
   "geneset: disable add new genes mode",
   "geneset: activate rename geneset mode",
   "geneset: disable rename geneset mode",
-
-  /* spatial */
-  "toggle image underlay",
 ]);
 
 /*

client/src/util/stateManager/viewStackHelpers.js

@@ -137,10 +137,13 @@ function _getEmbeddingRowOffsets(baseRowIndex, embeddingDf) {
     - if the embedding contains NaN coordinates, return a rowIndex
       that contains only the rows with discrete valued coordinates.
 
-  Currently assumes that there will be onl two dimensions in the embedding.
+  Currently assumes that there will be only two dimensions in the embedding.
   */
+  // eslint-disable-next-line react/destructuring-assignment -- destructuring fails
   const X = embeddingDf.icol(0).asArray();
+  // eslint-disable-next-line react/destructuring-assignment -- destructuring fails
   const Y = embeddingDf.icol(1).asArray();
+
   const offsets = new Int32Array(X.length);
   let numOffsets = 0;
 

dev_docs/release_process.md

@@ -26,14 +26,14 @@ Steps must be run from the project directory and in a virtual env with all the d
 3. In the release branch, run `make create-release-candidate PART=[major | minor | patch]`. This will bump the version and create a release *candidate* version (e.g. `0.3.0-rc.0`).
 4. Commit changes, push the new branch to origin and open a `DO NOT MERGE` draft PR, which will run tests on your branch. We will use this PR later
 5. Upload the release candidate to Test PyPI by running the command `make release-candidate-to-test-pypi`. (Make sure you are registered for PyPI and Test PyPI and you have write access to the cellxgene PyPI package for both).
-6. Verify the release candidate in a fresh virtual environment by running `make install-release-test` which installs the cellxgene build you just uploaded to Test PyPI. The PM should do this too.
+6. Verify the release candidate in a fresh virtual environment by running `VERSION=<X>.<Y>.<Z>rc.<#> make install-release-test` which installs the cellxgene build you just uploaded to Test PyPI (note that the version value does not include a dash `-`!). The PM should do this too. Note that you may need to run `hash -r` to ensure the cellxgene executable that was just installed is found in your shell path.
 7. If you find errors with the release candidate, fix them in main, rebase, and run `make recreate-release-candidate` to increment the release candidate version (i.e. `0.3.0-rc.0` -> `0.3.0-rc.1`). Then go back to Steps 5 and 6 to re-upload and re-test the new release candidate.
 8. If everything looks good, push the release to Test PyPI without the release candidate tag by running the command `make release-final-to-test-pypi` (i.e. `0.3.0-rc.1` -> `0.3.0`).
     - **NOTE:** Once you push the final release version to Test PyPI, you cannot ever re-upload the build again. If you need to make changes to the build, you will have to "burn" the version number and bump the part again and go back to step 1 with a brand new version number. For example, if you upload `0.3.0` to Test PyPI and realize there's a bug, you will have to create a new version `0.4.0` and there will be no `0.3.0` version of cellxgene. This is why testing the release candidate is very important.
 9. Publish the open draft PR for the release and conduct a PR review.
 10. Merge to the `main` branch.
 11. Publish to PyPI (prod) (assuming you that you have registered for PyPI, and that you have write access to the cellxgene pypi package) by running `make release-final`.
-12. Test the installation in a fresh virtual environment by running `pip install --no-cache-dir cellxgene`.
+12. Test the installation in a fresh virtual environment by running `pip install --no-cache-dir cellxgene`. Note that you may need to run `hash -r` to ensure the cellxgene executable that was just installed is found in your shell path.
 13. Create Github release using the version number and release notes ([instructions](https://help.github.com/articles/creating-releases/)):
      - Draft new release
      - Type version name matching release version number from (1)

scripts/launch_and_open

@@ -0,0 +1,16 @@
+#!/usr/bin/expect -f
+
+# Mac only! (depends upon `open` command)
+
+set h5ad [lindex $argv 0]
+puts "$h5ad"
+
+spawn cellxgene launch $h5ad
+
+set timeout 10
+expect -indices -re "Please go to (http:\/\/localhost:\[0-9\]+)" {
+    set url $expect_out(1,string)
+    exec >@stdout 2>@stderr open $url
+}
+
+interact

server/__init__.py

@@ -2,7 +2,7 @@ import logging
 import sys
 from server.common.utils.utils import import_plugins
 
-__version__ = "1.0.0"
+__version__ = "1.1.2"
 display_version = "cellxgene v" + __version__
 
 try:

server/annotate/annotation_types.py

@@ -0,0 +1,5 @@
+from enum import Enum
+
+
+class AnnotationType(Enum):
+    CELL_TYPE = "cell_type"

server/app/app.py

@@ -190,16 +190,6 @@ class SummarizeVarAPI(Resource):
     def post(self, data_adaptor):
         return common_rest.summarize_var_post(request, data_adaptor)
 
-class SpatialImageAPI(Resource):
-    @rest_get_data_adaptor
-    def get(self, data_adaptor):
-        return common_rest.spatial_image_get(request, data_adaptor)
-
-class SpatialMetaAPI(Resource):
-    @rest_get_data_adaptor
-    def get(self, data_adaptor):
-        return data_adaptor.get_spatial_metadata()
-
 
 def get_api_base_resources(bp_base):
     """Add resources that are accessed from the api url"""
@@ -232,9 +222,6 @@ def get_api_dataroot_resources(bp_dataroot):
     # Computation routes
     add_resource(DiffExpObsAPI, "/diffexp/obs")
     add_resource(LayoutObsAPI, "/layout/obs")
-    # Spatial routes
-    add_resource(SpatialImageAPI, "/spatial/image")
-    add_resource(SpatialMetaAPI, "/spatial/meta")
     return api
 
 

server/cli/annotate.py

@@ -0,0 +1,242 @@
+import functools
+import json
+import os.path
+import shlex
+import shutil
+import subprocess
+from os.path import isfile
+from subprocess import STDOUT, PIPE
+from tempfile import NamedTemporaryFile
+
+import click
+import pandas as pd
+from click import BadParameter
+
+from server.annotate.annotation_types import AnnotationType
+from server.common.utils.data_locator import DataLocator
+from server.common.utils.utils import sort_options
+
+
+def annotate_args(func):
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        return func(*args, **kwargs)
+
+    return wrapper
+
+
+@sort_options
+@click.command(
+    options_metavar="<options>"
+)
+@click.argument(
+    "input_h5ad_file",
+    type=click.Path(exists=True, dir_okay=False, readable=True),
+    nargs=1,
+    metavar="<path to H5AD input file>",
+    required=True,
+)
+@click.option(
+    "-m",
+    "--model-url",
+    # Making this a required "option", rather than an "argument", since we support automatic model selection in the
+    # future, in which case the user would not need to specify this option at all and we can make it optional at
+    # that time.
+    required=True,
+    help="The URL of the model used to prediction annotated labels. May be a local filesystem directory "
+    "or S3 path (s3://)",
+)
+@click.option(
+    "-o",
+    "--output-h5ad-file",
+    default="",
+    help="The output H5AD file that will contain the generated annotation values. If this option is not provided, "
+         "the input file will be overwritten to include the new annotations; in this case you must specify "
+         "--overwrite.",
+    metavar="<filename>",
+)
+@click.option(
+    "--overwrite",
+    default=False,
+    is_flag=True,
+    help="Allow overwriting of the specified H5AD output file, if it exists. For safety, you must specify this "
+         "flag if the specified output file already exists or if the --output-h5ad-file option is not provided.",
+    show_default=True,
+)
+@click.option(
+    "-l",
+    "--counts-layer",
+    help="If specified, raw counts will be read from the AnnData layer of the specified name. If unspecified, "
+    "raw counts will be read from `X` matrix, unless 'raw.X' exists, in which case that will be used.",
+)
+@click.option(
+    "-g",
+    "--gene-column-name",
+    help="The name of the `var` column that contains gene names. The values in this column will be used to match "
+    "genes between the query and reference datasets. If not specified, the gene names are expected to exist "
+    "in `var.index`.",
+)
+# TODO: Useful if we want to support discoverability of models
+# @click.option(
+#     "-r",
+#     "--model-repository",
+#     help="The base URL of the model repository. Maybe a local filesystem directory or S3 path (s3://)"
+# )
+# TODO: Useful if we want to support other, future annotation types, beyond "Cell Type". Currently hidden
+@click.option(
+    "-a",
+    "--annotation-type",
+    type=click.Choice([t.value for t in AnnotationType]),
+    default=AnnotationType.CELL_TYPE.value,
+    show_default=True,
+    hidden=True,  # Remove if we add support for more annotation types
+    help="The type of annotation to perform. This model to be used will be inferred from the annotation type.",
+)
+@click.option(
+    "-c",
+    "--annotation-prefix",
+    type=str,
+    default="cxg",
+    show_default=True,
+    help="An optional prefix used to form the names of: 1) new `obs` annotation columns that will store the predicted "
+    "annotation values and confidence scores, 2) `obsm` embeddings (reference and umap embedding), and "
+    "3) `uns` metadata for the prediction operation",
+)
+@click.option(
+    "-n",
+    "--run-name",
+    type=str,
+    help="An optional run name that will be used as a suffix to form the names of new `obs` annotation columns that "
+    "will store the predicted annotation values and confidence scores. This can be used to allow multiple "
+    "annotation predictions to be run on a single AnnData object.",
+)
+@click.option("--use-model-cache/--no-use-model-cache", default=True)
+@click.option(
+    "--use-gpu/--no-use-gpu",
+    default=True,
+    help="Whether to use a GPU for annotation operations (highly recommended, if available).",
+)
+# TODO: This is a cell type model-specific arg, so not ideal to specify here as a hardcoded option
+@click.option(
+    "--classifier",
+    default="default",
+    help="For cell type annotation, the classifier level to use. The classifier is model-dependent, so refer to "
+    "documentation for the specified model for valid values.",
+)
+# TODO: This is a cell type model-specific arg, so not ideal to specify here as a hardcoded option
+@click.option(
+    "--organism",
+    type=click.Choice(["Homo sapiens", "Mus musculus"], case_sensitive=True),
+    default="Homo sapiens",
+    help="For cell type annotation, the organism of the dataset. Used to normalize gene names to HGLC conventions when "
+    "an annotation model has been trained using data from different organism.",
+)
+@click.option(
+    "--model-cache-dir",
+    default=".models_cache",
+    help="Local directory used to store model files that are retrieved from a remote location. Model files will "
+    "be read from this directory first, if they exist, to avoid repeating large downloads.",
+)
+@click.option(
+    "--mlflow-env-manager",
+    type=click.Choice(["virtualenv", "conda", "local"]),
+    default="virtualenv",
+    help="Annotation model prediction will be installed and executed in the specified type of environment. MacOS users "
+    "on Apple Silicon (arm64, M1, M2, etc.) are recommended to use 'conda' to avoid Python package installation "
+    "errors. If 'conda' is specified then cellxgene must also have been installed within a conda environment",
+)
+@click.help_option("--help", "-h", help="Show this message and exit.")
+def annotate(**cli_args):
+    """
+    Add predicted annotations to an H5AD file. Run `cellxgene annotate --help` for more information.
+    """
+    _validate_options(cli_args)
+
+    print(f"Reading query dataset {cli_args['input_h5ad_file']}...")
+
+    annotation_prefix = "_".join(
+        filter(None, [cli_args.get("annotation_prefix"), cli_args.get("annotation_type"), cli_args.get("run_name")])
+    )
+
+    output_h5ad_file = (
+        cli_args["input_h5ad_file"]
+        if cli_args["overwrite"] and not cli_args["output_h5ad_file"]
+        else cli_args["output_h5ad_file"]
+    )
+
+    model_url = cli_args.get("model_url")
+    local_model_path = _retrieve_model(cli_args.get("model_cache_dir"), model_url, cli_args.get("use_model_cache"))
+
+    print(f"Annotating {cli_args.get('input_h5ad_file')} with {cli_args.get('annotation_type')}...")
+
+    if cli_args["annotation_type"] == AnnotationType.CELL_TYPE.value:
+        predict_args = dict(
+            query_dataset_h5ad_path=cli_args.get("input_h5ad_file"),
+            output_h5ad_path=output_h5ad_file,
+            annotation_prefix=annotation_prefix,
+            counts_layer=cli_args.get("counts_layer"),
+            gene_column_name=cli_args.get("gene_column_name"),
+            classifier=cli_args.get("classifier"),
+            organism=cli_args.get("organism"),
+            use_gpu=cli_args.get("use_gpu"),
+        )
+        # Drop args that have values of `None` as these will cause problems when passing into MLflow predict, since it
+        # ultimately gets converted into 1-row Pandas DataFrame (None is interpreted as a float type column!)
+        predict_args = dict([(k, v) for k, v in predict_args.items() if v is not None])
+
+        # Invoke prediction using MLflow cli, as a separate process.
+        # This fully prepares the Python environment that is needed for executing the model.
+        # The Python environment will be reused after it is setup once.
+        with NamedTemporaryFile(buffering=0) as predict_args_file:
+            # write the mlflow predict arguments to a csv file, which will be passed to mlflow cmd
+            pd.DataFrame([json.dumps(predict_args)]).to_csv(predict_args_file, index=None)
+            predict_args_file.seek(0)
+
+            # run mlflow prediction in subprocess
+            predict_cmd = (
+                f"mlflow models predict "
+                f"--env-manager {cli_args['mlflow_env_manager']} "
+                f"--model-uri {local_model_path} "
+                f"--content-type csv --input-path {predict_args_file.name}"
+            )
+            p = subprocess.Popen(
+                args=shlex.split(predict_cmd), stdin=predict_args_file, text=True, bufsize=0, stdout=PIPE, stderr=STDOUT
+            )
+
+            # display mlflow process output as it runs
+            for line in p.stdout:
+                print(line.rstrip())
+
+            p.wait()
+            if p.returncode == 0:
+                print(f"Wrote annotations to {output_h5ad_file}")
+            else:
+                print("Annotation failed!")
+    else:
+        raise BadParameter(f"unknown annotation type {cli_args['annotation_type']}")
+
+
+def _retrieve_model(model_cache_dir, model_url, use_cache=True):
+    local_cache_model_path = os.path.join(model_cache_dir, os.path.splitext(os.path.basename(model_url))[0])
+    if not os.path.exists(local_cache_model_path) or not use_cache:
+        print(f"Retrieving model from {model_url}")
+        # download from remote source
+        with DataLocator(model_url).local_handle() as model_archive_local_path:
+            # unpack archive to local cache dir
+            shutil.unpack_archive(model_archive_local_path, local_cache_model_path)
+    else:
+        print(f"Using cached model at {local_cache_model_path}")
+
+    return local_cache_model_path
+
+
+def _validate_options(cli_args):
+    output = cli_args["output_h5ad_file"]
+    overwrite = cli_args["overwrite"]
+
+    if isfile(output) and not overwrite:
+        raise click.UsageError(f"Cannot overwrite existing file {output}, try using the flag --overwrite")
+
+
+if __name__ == "__main__":
+    annotate()

server/cli/cli.py

@@ -1,5 +1,6 @@
 import click
 
+from .annotate import annotate
 from .launch import launch
 from .prepare import prepare
 from .upgrade import log_upgrade_check
@@ -31,4 +32,5 @@ def cli(upgrade_check):
 
 
 cli.add_command(launch)
+cli.add_command(annotate)
 cli.add_command(prepare)

server/common/annotations/annotations.py

@@ -57,7 +57,7 @@ class Annotations(metaclass=ABCMeta):
         pass
 
     @abstractmethod
-    def write_gene_sets(self, gs, data_adaptor):
+    def write_gene_sets(self, gs, tid, data_adaptor):
         """Write the gene sets (gs) to a persistent storage such that it can later be read"""
         pass
 

server/common/annotations/local_file_csv.py

@@ -7,6 +7,7 @@ from hashlib import blake2b
 
 import pandas as pd
 from flask import session
+from fsspec import AbstractFileSystem
 
 from server import __version__ as cellxgene_version
 from server.app.session import get_user_id
@@ -62,21 +63,27 @@ class AnnotationsLocalFile(Annotations):
         self.check_user_annotations_enabled()  # raises
 
         fname = self._get_celllabels_filename(data_adaptor)
+        empty_labels = pd.DataFrame()
+        if fname is None:
+            return empty_labels
+
         with self.label_lock:
-            if fname is not None and os.path.exists(fname) and os.path.getsize(fname) > 0:
-                # returned the cached labels if possible, otherwise read them from the file
-                if fname == self.last_label_fname:
-                    return self.last_labels
-                else:
-                    labels = pd.read_csv(
-                        fname, dtype="category", index_col=0, header=0, comment="#", keep_default_na=False
-                    )
-                    # update the cache
-                    self.last_label_fname = fname
-                    self.last_labels = labels
-                    return labels
-            else:
-                return pd.DataFrame()
+            locator = DataLocator(fname)
+            if not locator.exists() or locator.size() == 0:
+                return empty_labels
+
+            # return the cached labels if possible
+            if fname == self.last_label_fname:
+                return self.last_labels
+
+            # otherwise, read labels from file
+            with locator.open() as f:
+                labels = pd.read_csv(f, dtype="category", index_col=0, header=0, comment="#", keep_default_na=False)
+
+            # update the cache
+            self.last_label_fname = fname
+            self.last_labels = labels
+            return labels
 
     def write_labels(self, df, data_adaptor):
         self.check_user_annotations_enabled()  # raises
@@ -95,13 +102,12 @@ class AnnotationsLocalFile(Annotations):
 
             fname = self._get_celllabels_filename(data_adaptor)
             self._backup(fname)
-            if not df.empty:
-                with open(fname, "w", newline="") as f:
+            locator = DataLocator(fname)
+            with locator.open("w") as f:
+                if not df.empty:
                     if header is not None:
                         f.write(header)
                     df.to_csv(f)
-            else:
-                open(fname, "w").close()
 
             # update the cache
             self.last_label_fname = fname
@@ -109,26 +115,32 @@ class AnnotationsLocalFile(Annotations):
 
     def read_gene_sets(self, data_adaptor, context=None):
         fname = self._get_genesets_filename(data_adaptor)
-        gene_sets = {}
-        tid = None
+        empty_gene_sets = {}
+
         with self.gene_sets_lock:
             tid = self.last_geneset_tid  # inside the critical section
-            if fname is not None and os.path.exists(fname) and os.path.getsize(fname) > 0:
-                # return the cached genesets if possible, otherwise read from file and validate them
-                if fname == self.last_geneset_fname:
-                    gene_sets = self.last_geneset
-                else:
-                    # read
-                    gene_sets = read_gene_sets_tidycsv(DataLocator(fname), context)
+            if fname is None:
+                return (empty_gene_sets, tid)
 
-                    # validate
-                    gene_sets = data_adaptor.check_new_gene_sets(gene_sets, context)
+            locator = DataLocator(fname)
+            if not locator.exists() or locator.size() == 0:
+                return (empty_gene_sets, tid)
 
-                    # update cache
-                    self.last_geneset_fname = fname
-                    self.last_geneset = gene_sets
+            # return the cached genesets if possible, otherwise read from file and validate them
+            if fname == self.last_geneset_fname:
+                return (self.last_geneset, tid)
 
-        return (gene_sets, tid)
+            # read
+            gene_sets = read_gene_sets_tidycsv(locator, context)
+
+            # validate
+            gene_sets = data_adaptor.check_new_gene_sets(gene_sets, context)
+
+            # update cache
+            self.last_geneset_fname = fname
+            self.last_geneset = gene_sets
+
+            return (gene_sets, tid)
 
     def write_gene_sets(self, gene_sets, tid, data_adaptor):
         self.check_gene_sets_save_enabled()  # raises
@@ -157,9 +169,9 @@ class AnnotationsLocalFile(Annotations):
 
             fname = self._get_genesets_filename(data_adaptor)
             self._backup(fname)
-            with open(fname, "w", newline="") as f:
-                f.write(header)
-                f.write(self.gene_sets_to_csv(gene_sets))
+            locator = DataLocator(fname)
+            with locator.open("w", newline="") as f:
+                f.write(header + self.gene_sets_to_csv(gene_sets))
 
             # update the cache
             self.last_geneset_fname = fname
@@ -181,7 +193,7 @@ class AnnotationsLocalFile(Annotations):
 
         output_file = self.label_output_file or self.gene_sets_output_file
         if output_file:
-            return os.path.dirname(os.path.abspath(output_file))
+            return os.path.dirname(DataLocator(output_file).abspath())
 
         return os.getcwd()
 
@@ -220,34 +232,37 @@ class AnnotationsLocalFile(Annotations):
             1. fname -> backup_dir/fname-TIME
             2. delete excess files in backup_dir
         """
-        root, ext = os.path.splitext(fname)
-        backup_dir = f"{root}-backups"
+        locator = DataLocator(fname)
+        fs: AbstractFileSystem = locator.fs  # Handle to underlying fsspec file system
 
         # Make sure there is work to do
-        if not os.path.exists(fname):
+        if not locator.exists():
             return
 
+        root, ext = os.path.splitext(locator.abspath())
+        backup_dir = f"{root}-backups"
+
         # Ensure backup_dir exists
-        if not os.path.exists(backup_dir):
-            os.mkdir(backup_dir)
+        fs.mkdirs(backup_dir, exist_ok=True)
 
         # Save current file to backup_dir
         fname_base = os.path.basename(fname)
         fname_base_root, fname_base_ext = os.path.splitext(fname_base)
-        # don't use ISO standard time format, as it contains characters illegal on some filesytems.
+        # don't use ISO standard time format, as it contains characters illegal on some filesystems.
         nowish = datetime.now().strftime("%Y-%m-%dT%H-%M-%S")
         backup_fname = os.path.join(backup_dir, f"{fname_base_root}-{nowish}{fname_base_ext}")
-        if os.path.exists(backup_fname):
-            os.remove(backup_fname)
-        os.rename(fname, backup_fname)
+        if fs.exists(backup_fname):
+            fs.delete(backup_fname)
+        fs.rename(fname, backup_fname)
 
         # prune the backup_dir to max number of backup files, keeping the most recent backups
-        backups = list(filter(lambda s: s.startswith(fname_base_root), os.listdir(backup_dir)))
-        excess_count = len(backups) - max_backups
-        if excess_count > 0:
-            backups.sort()
-            for bu in backups[0:excess_count]:
-                os.remove(os.path.join(backup_dir, bu))
+        backup_path_prefix = DataLocator.strip_protocol(os.path.join(backup_dir, fname_base_root + "-"))
+        backups = list(filter(lambda s: s.startswith(backup_path_prefix), fs.ls(backup_dir)))
+
+        # sorting to drop the oldest
+        excess_backups = list(sorted(backups, reverse=True))[max_backups:]
+        for bu in excess_backups:
+            fs.delete(bu)
 
     def update_parameters(self, parameters, data_adaptor):
         params = {}

server/common/config/dataset_config.py

@@ -4,6 +4,7 @@ from os.path import splitext, isdir
 from server.common.annotations.local_file_csv import AnnotationsLocalFile
 from server.common.config.base_config import BaseConfig
 from server.common.errors import ConfigurationError, AnnotationsError
+from server.common.utils.data_locator import DataLocator
 from server.data_common.matrix_loader import MatrixDataLoader
 
 
@@ -127,11 +128,15 @@ class DatasetConfig(BaseConfig):
             if lf_ext and lf_ext != ".csv":
                 raise ConfigurationError(f"genesets file type must be .csv: {genesets_filename}")
 
-        if dirname is not None and not isdir(dirname):
-            try:
-                os.mkdir(dirname)
-            except OSError:
-                raise ConfigurationError("Unable to create directory specified by --user-generated-data-dir")
+        if dirname is not None:
+            if not DataLocator(dirname).islocal():
+                # remote object stores only support objects but not directories, do nothing
+                pass
+            elif not isdir(dirname):
+                try:
+                    os.mkdir(dirname)
+                except OSError:
+                    raise ConfigurationError("Unable to create directory specified by --user-generated-data-dir")
 
         anno_config = {
             "user-annotations": self.user_annotations__enable,

server/common/rest.py

@@ -4,9 +4,8 @@ import sys
 from http import HTTPStatus
 import zlib
 import json
-import numpy as np
 
-from flask import make_response, jsonify, current_app, abort, send_file
+from flask import make_response, jsonify, current_app, abort
 from werkzeug.urls import url_unquote
 
 from server.common.config.client_config import get_client_config
@@ -294,7 +293,7 @@ def layout_obs_get(request, data_adaptor):
 
     try:
         return make_response(
-            data_adaptor.layout_to_fbs_matrix(fields, data_adaptor.get_spatial()), HTTPStatus.OK, {"Content-Type": "application/octet-stream"}
+            data_adaptor.layout_to_fbs_matrix(fields), HTTPStatus.OK, {"Content-Type": "application/octet-stream"}
         )
     except (KeyError, DatasetAccessError) as e:
         return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True)
@@ -398,40 +397,3 @@ def summarize_var_post(request, data_adaptor):
 
     key = request.args.get("key", default=None)
     return summarize_var_helper(request, data_adaptor, key, request.get_data())
-
-def spatial_image_get(request, data_adaptor):
-    import io
-    import matplotlib.pyplot    
-
-    resolution = "hires"
-    spatial = data_adaptor.get_spatial()
-
-    if len(list(spatial)) == 0:
-        return abort_and_log(HTTPStatus.BAD_REQUEST, "uns does not have spatial information")
-
-    library_id = list(spatial)[0]
-    if len(spatial) > 1:
-        current_app.logger.warning(f"More than one library found under uns.spatial, using library '{library_id}'")
-
-    if "images" not in spatial[library_id]:
-        return abort_and_log(HTTPStatus.BAD_REQUEST, "spatial information does not contain images")
-
-    if resolution not in spatial[library_id]["images"]:
-        return abort_and_log(HTTPStatus.BAD_REQUEST, f"spatial information does not contain requested resolution '{resolution}'")
-
-    response_image = io.BytesIO()
-    img = spatial[library_id]["images"][resolution]
-    matplotlib.pyplot.imsave(response_image, img)
-    response_image.seek(0)
-
-    try:
-        return send_file(response_image, attachment_filename=f"{library_id}-{resolution}.png", mimetype="image/png")
-    except (KeyError, DatasetAccessError) as e:
-        return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True)
-    except PrepareError:
-        return abort_and_log(
-            HTTPStatus.NOT_IMPLEMENTED,
-            f"No spatial image available {request.path}",
-            loglevel=logging.ERROR,
-            include_exc_info=True,
-        ) 

server/common/utils/data_locator.py

@@ -52,8 +52,10 @@ class DataLocator:
             self.fs = fsspec.filesystem(self.protocol)
 
     def __repr__(self):
-        return f"DataLocator(protocol={self.protocol}, cname={self.cname}, "
-        f"path={self.path}, uri_or_path={self.uri_or_path})"
+        return (
+            f"DataLocator(protocol={self.protocol}, cname={self.cname}, "
+            f"path={self.path}, uri_or_path={self.uri_or_path})"
+        )
 
     @staticmethod
     def _get_protocol_and_path(uri_or_path):
@@ -65,6 +67,10 @@ class DataLocator:
                 return protocol, path
         return None, uri_or_path
 
+    @staticmethod
+    def strip_protocol(uri_or_path):
+        return DataLocator._get_protocol_and_path(uri_or_path)[1]
+
     def exists(self):
         return self.fs.exists(self.cname)
 
@@ -72,7 +78,7 @@ class DataLocator:
         return self.fs.size(self.cname)
 
     def lastmodtime(self):
-        """ return datetime object representing last modification time, or None if unavailable """
+        """return datetime object representing last modification time, or None if unavailable"""
         info = self.fs.info(self.cname)
         if self.islocal() and info is not None:
             return datetime.fromtimestamp(info["mtime"])
@@ -92,8 +98,8 @@ class DataLocator:
     def isfile(self):
         return self.fs.isfile(self.cname)
 
-    def open(self, *args):
-        return self.fs.open(self.uri_or_path, *args)
+    def open(self, *args, **kwargs):
+        return self.fs.open(self.uri_or_path, *args, **kwargs)
 
     def islocal(self):
         return self.protocol is None or self.protocol == "file"
@@ -107,10 +113,9 @@ class DataLocator:
         # do our best to create a file with the same.
         ext = os.path.splitext(self.path)
         suffix = None if ext[1] == "" else ext[1]
-        with self.open() as src, tempfile.NamedTemporaryFile(prefix="cellxgene_", suffix=suffix, delete=False) as tmp:
-            tmp.write(src.read())
+        with tempfile.NamedTemporaryFile(prefix="cellxgene_", suffix=suffix, delete=False) as tmp:
+            self.fs.download(self.uri_or_path, tmp.name)
             tmp.close()
-            src.close()
             tmp_path = tmp.name
             return LocalFilePath(tmp_path, delete=True)
 

server/common/utils/utils.py

@@ -98,8 +98,7 @@ def custom_format_warning(msg, *args, **kwargs):
 
 
 def jsonify_strict(data):
-    return json.dumps(data, cls=StrictJSONEncoder, allow_nan=False)
-
+    return StrictJSONEncoder().encode(data)
 
 def import_plugins(plugin_module):
     """

server/data_anndata/anndata_adaptor.py

@@ -174,10 +174,14 @@ class AnndataAdaptor(DataAdaptor):
         except MemoryError:
             raise DatasetAccessError("Out of memory - file is too large for available memory.")
         except Exception:
-            raise DatasetAccessError(
+            import traceback
+            message = (
                 "File not found or is inaccessible. File must be an .h5ad object. "
                 "Please check your input and try again."
-            )
+                )
+            if self.server_config.app__verbose:
+                message += f"\n{traceback.format_exc()}"
+            raise DatasetAccessError(message)
 
     def _validate_and_initialize(self):
         if anndata_version_is_pre_070():
@@ -236,6 +240,14 @@ class AnndataAdaptor(DataAdaptor):
             warnings.warn(
                 f"Anndata data matrix is in {self.data.X.dtype} format not float32. " f"Precision may be truncated."
             )
+        if self.data.X.dtype < np.float32:
+            if self.data.isbacked:
+                raise DatasetAccessError(f"Data matrix in {self.data.X.dtype} format is not supported in backed mode."
+                                         " Please reload without --backed, or convert matrix to float32")
+            warnings.warn(
+                f"Anndata data matrix is in unsupported {self.data.X.dtype} format -- will be cast to float32"
+            )
+            self.data.X = self.data.X.astype(np.float32)
         for ax in Axis:
             curr_axis = getattr(self.data, str(ax))
             for ann in curr_axis:
@@ -274,43 +286,6 @@ class AnndataAdaptor(DataAdaptor):
             df = df[fields]
         return encode_matrix_fbs(df, col_idx=df.columns)
 
-    def get_spatial(self):
-        return self.data.uns["spatial"]
-
-    def get_spatial_metadata(self):
-        spatial = self.get_spatial()
-
-        resolution = "hires"
-
-        if len(list(spatial)) == 0:
-            raise Exception("uns does not have spatial information")
-
-        library_id = list(spatial)[0]
-
-        if "images" not in spatial[library_id]:
-            raise Exception("spatial information does not contain images")
-
-        if resolution not in spatial[library_id]["images"]:
-            raise Exception(f"spatial information does not contain requested resolution '{resolution}'")
-
-        scaleref = spatial[library_id]["scalefactors"][f"tissue_{resolution}_scalef"]
-        (h, w, _) = spatial[library_id]["images"][resolution].shape
-
-        A = self.data.obsm["X_spatial"]
-        min = np.nanmin(A, axis=0)
-        max = np.nanmax(A, axis=0)
-        scale = np.amax(max - min)
-        translate = 0.5 - ((max - min) / scale / 2)
-
-        return {
-            "imageWidth": w,
-            "imageHeight": h,
-            "scaleref": scaleref,
-            "inverseScale": int(scale),
-            "inverseTranslate": translate.tolist(),
-            "inverseMin": min.tolist(),
-        }
-
     def get_embedding_names(self):
         """
         Return pre-computed embeddings.

server/data_common/data_adaptor.py

@@ -340,57 +340,31 @@ class DataAdaptor(metaclass=ABCMeta):
         pass
 
     @staticmethod
-    def normalize_embedding(embedding, spatial = None):
+    def normalize_embedding(embedding):
         """Normalize embedding layout to meet client assumptions.
-        Embedding is an ndarray, shape (n_obs, n)., where n is normally 2.
-        Note: if spatial data is available, the normalization will be done
-        according to the size of the underlying image
+        Embedding is an ndarray, shape (n_obs, n)., where n is normally 2
         """
 
-        if spatial is not None:
+        # scale isotropically
+        try:
+            min = np.nanmin(embedding, axis=0)
+            max = np.nanmax(embedding, axis=0)
+        except RuntimeError:
+            # indicates entire array was NaN, which should propagate
+            min = np.NaN
+            max = np.NaN
 
-            # TODO: sync with the code in spatial_data_get
-            resolution = "hires"
+        scale = np.amax(max - min)
+        normalized_layout = (embedding - min) / scale
 
-            if len(list(spatial)) == 0:
-                raise Exception("uns does not have spatial information")
-
-            library_id = list(spatial)[0]
-
-            if "images" not in spatial[library_id]:
-                raise Exception("spatial information does not contain images")
-
-            if resolution not in spatial[library_id]["images"]:
-                raise Exception(f"spatial information does not contain requested resolution '{resolution}'")
-
-            scaleref = spatial[library_id]["scalefactors"][f"tissue_{resolution}_scalef"]
-            (h, w, _) = spatial[library_id]["images"][resolution].shape
-
-            A = embedding * scaleref
-            A = np.column_stack([A[:, 0] / w, A[:, 1] / h])
-            normalized_layout = A.astype(dtype=np.float32)
-
-        else:
-
-            # scale isotropically
-            try:
-                min = np.nanmin(embedding, axis=0)
-                max = np.nanmax(embedding, axis=0)
-            except RuntimeError:
-                # indicates entire array was NaN, which should propagate
-                min = np.NaN
-                max = np.NaN
-
-            scale = np.amax(max - min)
-            normalized_layout = (embedding - min) / scale
-
-            # translate to center on both axis
-            translate = 0.5 - ((max - min) / scale / 2)
-            normalized_layout = normalized_layout + translate
+        # translate to center on both axis
+        translate = 0.5 - ((max - min) / scale / 2)
+        normalized_layout = normalized_layout + translate
 
+        normalized_layout = normalized_layout.astype(dtype=np.float32)
         return normalized_layout
 
-    def layout_to_fbs_matrix(self, fields, spatial = None):
+    def layout_to_fbs_matrix(self, fields):
         """
         return specified embeddings as a flatbuffer, using the cellxgene matrix fbs encoding.
 
@@ -406,7 +380,7 @@ class DataAdaptor(metaclass=ABCMeta):
         with ServerTiming.time("layout.query"):
             for ename in embeddings:
                 embedding = self.get_embedding_array(ename, 2)
-                normalized_layout = DataAdaptor.normalize_embedding(embedding, ename == "spatial" and spatial)
+                normalized_layout = DataAdaptor.normalize_embedding(embedding)
                 layout_data.append(pd.DataFrame(normalized_layout, columns=[f"{ename}_0", f"{ename}_1"]))
 
         with ServerTiming.time("layout.encode"):

server/requirements-annotate.txt

@@ -0,0 +1,2 @@
+mlflow
+scanpy

server/requirements-dev.txt

@@ -2,9 +2,9 @@ black
 bumpversion>=0.5
 codecov>=2.0.15
 parameterized>=0.7.0
-psycopg2-binary>=2.8.5
 pytest>=3.6.3
 python-jose>=3.2.0
 twine>=1.12.1
 -r requirements.txt
 -r requirements-prepare.txt
+-r requirements-annotate.txt

server/requirements.txt

@@ -3,7 +3,7 @@
 anndata>=0.7.6 # we need to_memory(), added in 0.7.6
 boto3>=1.12.18
 click>=7.1.2
-Flask>=1.0.2
+Flask>=1.0.2,<2.3.0
 Flask-Compress>=1.4.0
 Flask-Cors>=3.0.9  # CVE-2020-25032
 Flask-RESTful>=0.3.6
@@ -14,9 +14,8 @@ flatten-dict>=0.2.0
 fsspec>=0.4.4,<0.8.0
 gunicorn>=20.0.4
 h5py>=3.0.0
-matplotlib>=3.5.0
 numba>=0.51.2
-numpy>=1.17.5
+numpy>=1.17.5,<=1.22
 packaging>=20.0
 pandas>=1.0,!=1.1  # pandas 1.1 breaks tests, https://github.com/pandas-dev/pandas/issues/35446
 PyYAML>=5.4  # CVE-2020-14343

setup.py

@@ -9,9 +9,12 @@ with open("server/requirements.txt") as fh:
 with open("server/requirements-prepare.txt") as fh:
     requirements_prepare = fh.read().splitlines()
 
+with open("server/requirements-annotate.txt") as fh:
+    requirements_annotate = fh.read().splitlines()
+
 setup(
     name="cellxgene",
-    version="1.0.0",
+    version="1.1.2",
     packages=find_packages(),
     url="https://github.com/chanzuckerberg/cellxgene",
     license="MIT",
@@ -40,5 +43,5 @@ setup(
         "Topic :: Scientific/Engineering :: Bio-Informatics",
     ],
     entry_points={"console_scripts": ["cellxgene = server.cli.cli:cli"]},
-    extras_require=dict(prepare=requirements_prepare),
+    extras_require=dict(prepare=requirements_prepare, annotate=requirements_annotate),
 )

test/unit/cli/fixtures/__init__.py

@@ -0,0 +1,5 @@
+from .mlflow_model_fixture import FakeModel
+
+
+def _load_pyfunc(data_path):
+    return FakeModel()

test/unit/cli/fixtures/mlflow_model_fixture.py

@@ -0,0 +1,11 @@
+import mlflow
+
+
+class FakeModel(mlflow.pyfunc.PythonModel):
+    def __init__(self, input_to_output: dict = {}):
+        self.input_to_output = input_to_output
+
+    def predict(self, model_input) -> None:
+        # this stdout output is useful for validating the input in a test, noting that this model will be invoked in a
+        # subprocess, so stdout is one means of communicating information back to the test code
+        print(f"__MODEL_INPUT__={model_input.iloc[0][0]}")

test/unit/cli/test_annotate.py

@@ -0,0 +1,130 @@
+import os
+import shutil
+import unittest
+from tempfile import mkstemp, TemporaryDirectory, NamedTemporaryFile
+
+import mlflow
+from click.testing import CliRunner
+
+from server.cli.annotate import annotate
+from test.unit.cli.fixtures.mlflow_model_fixture import FakeModel
+
+
+def write_model(model) -> str:
+    with TemporaryDirectory() as mlflow_model_dir:
+        fixtures_path = os.path.join(os.path.dirname(__file__), "fixtures")
+        mlflow.pyfunc.save_model(mlflow_model_dir, loader_module="fixtures", code_path=[fixtures_path])
+        return shutil.make_archive(mkstemp()[1], "zip", mlflow_model_dir)
+
+
+class TestCliAnnotate(unittest.TestCase):
+    def test__annotate__loads_and_runs(self):
+        """
+        Invokes the `annotate` subcommand of cellxgene CLI, using a CliRunner() programmatic invocation.
+
+        This tests the happy path case:
+        1) Command line options are parsed;
+        2) An MLflow model zip archive can be read in (from local disk), unpacked, and invoked;
+        3) The correct options are passed to the MLflow model.
+        4) The annotate subcommand exits successfully.
+
+        This does not verify model output or predictions (it's a fake MLflow model, after all); it's up to the real model
+        to output its predictions as it wants, but this is specific to the model and so not tested here.
+
+        The  CliRunner() invokes the subcommand in a subprocess, and the annotate subcommand itself invokes the MLflow
+        model in yet another subprocess. So while this test can help determine if everything is working, it is not a
+        simple matter to debug in the case of a failure. However, the stdout/stderr of the MLflow process is captured
+        by the CliRunner() subprocess, so errors can be inspected in result.stdout when debugging this test. Hope this
+        helps!
+        """
+
+        _, query_dataset_file_path = mkstemp()
+        model_file_path = write_model(FakeModel())
+
+        result = CliRunner().invoke(
+            annotate,
+            [
+                query_dataset_file_path,
+                "--model-url",
+                model_file_path,
+                "--output-h5ad-file",
+                f"{query_dataset_file_path}.output",
+                # avoid having mflow create conda env or virtualenv when in test env;
+                # this avoids making pip remote requests and is also faster
+                "--mlflow-env-manager",
+                "local",
+            ],
+        )
+
+        # to help debugging, show the output from the CliRunner and MLflow stdout
+        if result.exit_code:
+            print(result.stdout)
+
+        self.assertEqual(0, result.exit_code, "runs successfully")
+
+        # The FakeModel will print it inputs to stdout, as "__MODEL_INPUT__={...}", allowing us to assert that it received valid inputs.
+        self.assertIn(
+            "__MODEL_INPUT__={"
+            f'"query_dataset_h5ad_path": "{query_dataset_file_path}", '
+            f'"output_h5ad_path": "{query_dataset_file_path}.output", '
+            '"annotation_prefix": "cxg_cell_type", "classifier": "default", '
+            '"organism": "Homo sapiens", "use_gpu": true}',
+            result.stdout,
+            "inputs passed correctly",
+        )
+        self.assertIn(
+            f"Wrote annotations to {query_dataset_file_path}.output",
+            result.stdout,
+            "success message is correct",
+        )
+
+    def test__annotate__requires_overwrite_option_when_output_file_exists(self):
+
+        with NamedTemporaryFile() as input_h5ad, NamedTemporaryFile() as existing_file:
+            required_options = [input_h5ad.name, "--output-h5ad-file", existing_file.name, "--model-url", "some_url"]
+            result = CliRunner().invoke(
+                annotate,
+                required_options + [],
+            )
+
+            self.assertNotEqual(0, result.exit_code, "aborts with non-success code")
+            self.assertIn(
+                "try using the flag --overwrite",
+                result.stdout,
+                "error message displayed",
+            )
+
+    def test__annotate__overwrite_option_allows_overwrite_of_existing_output_file(self):
+        model_file_path = write_model(FakeModel())
+
+        with NamedTemporaryFile() as existing_file:
+            required_options = [
+                existing_file.name,
+                "--output-h5ad-file",
+                existing_file.name,
+                "--overwrite",
+                "--model-url",
+                model_file_path,
+            ]
+            result = CliRunner().invoke(
+                annotate,
+                required_options + [],
+            )
+
+            print(result.stdout)
+            self.assertNotEqual(1, result.exit_code, "aborts with non-success code")
+            self.assertIn(
+                f"Wrote annotations to {existing_file.name}",
+                result.stdout,
+                "success message is correct on output file overwrite",
+            )
+
+
+# TODO:
+# Test annotate cli args more comprehensively
+# Test server.cli.annotate._validate_options
+# Test model caching feature works
+# Test model loading from s3 works (maybe w/just a real model)
+
+if __name__ == "__main__":
+    unittest.main()

test/unit/common/test_api.py

@@ -290,6 +290,7 @@ class EndPoints(object):
         result_data = result.json()
         self.assertEqual(result_data, pbmc3k_colors)
 
+    @unittest.skip('needs fix: https://github.com/chanzuckerberg/cellxgene/issues/2542')
     def test_static(self):
         endpoint = "static"
         file = "assets/favicon.ico"

test/unit/data_anndata/test_anndata_adaptor.py

@@ -1,5 +1,4 @@
 import json
-import sys
 import time
 import unittest
 
@@ -37,6 +36,7 @@ Test the anndata adaptor using the pbmc3k data set.
         (f"{FIXTURES_ROOT}/pbmc3k-CSC-gz.h5ad", True, "normal"),
         (f"{FIXTURES_ROOT}/pbmc3k-CSR-gz.h5ad", True, "normal"),
         (f"{FIXTURES_ROOT}/pbmc3k_64.h5ad", False, "auto"),  # 64 bit conversion tests
+        (f"{FIXTURES_ROOT}/pbmc3k_16.h5ad", False, "auto"),  # 16 bit conversion tests
     ],
 )
 class AdaptorTest(unittest.TestCase):

test/unit/data_anndata/test_anndata_adaptor_errors.py

@@ -0,0 +1,23 @@
+import unittest
+
+from parameterized import parameterized_class
+
+from server.common.errors import DatasetAccessError
+from test import FIXTURES_ROOT
+from test.unit import app_config
+
+
+@parameterized_class(
+    ("data_locator", "backed", "X_approximate_distribution"),
+    [
+        (f"{FIXTURES_ROOT}/pbmc3k_16.h5ad", True, "auto"),  # 16 bit conversion tests
+    ],
+)
+class AdaptorLoadErrorTest(unittest.TestCase):
+    def test_float16_backed_raises_err(self):
+        with self.assertRaises(DatasetAccessError):
+            config = app_config(
+                self.data_locator,
+                backed=self.backed,
+                extra_dataset_config=dict(X_approximate_distribution=self.X_approximate_distribution),
+            )

test/unit/utils/test_jsonify_strict.py

@@ -54,5 +54,5 @@ class TestJsonifyStrict(unittest.TestCase):
         # the actual test!
         self.assertEqual(
             jsonify_strict(values),
-            '{"floating": [100.0, 101.0, 102.0], "integer": [0, 1, 2, 3, 4, 5, 6, 7]}',
+            '{"integer": [0, 1, 2, 3, 4, 5, 6, 7], "floating": [100.0, 101.0, 102.0]}',
         )