Merge branch 'dev'

Author: berombau

.cruft.json

@@ -1,7 +1,7 @@
 {
   "template": "https://github.com/scverse/cookiecutter-scverse",
-  "commit": "586b1652162ff7994b0070a034023d64289ae416",
-  "checkout": "v0.3.1",
+  "commit": "009f1b5205d007026e76b3dd79f57ad946947ceb",
+  "checkout": null,
   "context": {
     "cookiecutter": {
       "project_name": "FlowSOM",

.gitignore

@@ -18,6 +18,7 @@ __pycache__/
 /.pytest_cache/
 /.cache/
 /data/
+/node_modules/
 
 # docs
 /docs/generated/

.pre-commit-config.yaml

@@ -1,3 +1,4 @@
+exclude: "tests/data"
 fail_fast: false
 default_language_version:
   python: python3
@@ -6,29 +7,18 @@ default_stages:
   - push
 minimum_pre_commit_version: 2.16.0
 repos:
-  - repo: https://github.com/psf/black
-    rev: "23.11.0"
-    hooks:
-      - id: black
-  - repo: https://github.com/asottile/blacken-docs
-    rev: 1.16.0
-    hooks:
-      - id: blacken-docs
   - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v3.1.0
+    rev: v4.0.0-alpha.8
     hooks:
       - id: prettier
-        # Newer versions of node don't work on systems that have an older version of GLIBC
-        # (in particular Ubuntu 18.04 and Centos 7)
-        # EOL of Centos 7 is in 2024-06, we can probably get rid of this then.
-        # See https://github.com/scverse/cookiecutter-scverse/issues/143 and
-        # https://github.com/jupyterlab/jupyterlab/issues/12675
-        language_version: "17.9.1"
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.5
+    rev: v0.1.14
     hooks:
       - id: ruff
+        types_or: [python, pyi, jupyter]
         args: [--fix, --exit-non-zero-on-fix]
+      - id: ruff-format
+        types_or: [python, pyi, jupyter]
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.5.0
     hooks:

README.md

@@ -1,6 +1,7 @@
 # FlowSOM
 
 <!-- [![Tests][badge-tests]][link-tests] -->
+
 [![Documentation][badge-docs]][link-docs]
 
 [badge-tests]: https://img.shields.io/github/actions/workflow/status/saeyslab/FlowSOM_Python/test.yaml?branch=main

docs/api.md

@@ -1,35 +1,63 @@
 # API
 
-Import FlowSOM as:
+Import FlowSOM using the alias `fs` for convenience. Functions and classes can then be accessed as `fs.FlowSOM` or `fs.io.read_FCS`:
 
 ```
 import flowsom as fs
 ```
 
 The functionality is organised in subpackages:
-- `io` for reading and writing FCS files
-- `pp` for preprocessing
-- `tl` for tools
-- `pl` for plotting
 
-The central class is `FlowSOM`.
+-   `io` for reading and writing FCS files
+-   `pp` for preprocessing
+-   `tl` for tools
+-   `pl` for plotting
 
-## Reading
+The central class is `FlowSOM`, which can be instantiated as a class and is also the output of the convenience function `flowsom_clustering`:
+
+```{eval-rst}
+.. module:: flowsom
+.. autosummary::
+    :toctree: generated
 
+    flowsom.FlowSOM
+    flowsom.flowsom_clustering
 ```
+
+## Reading
+
+```{eval-rst}
+.. module:: flowsom.io
+.. currentmodule:: flowsom
+
+.. autosummary::
+    :toctree: generated
+
     io.read_FCS
 ```
 
 ## Preprocessing
 
-```
+```{eval-rst}
+.. module:: flowsom.pp
+.. currentmodule:: flowsom
+
+.. autosummary::
+    :toctree: generated
+
     pp.aggregate_flowframes
     pp.normalize_estimate_logicle
 ```
 
 ## Tools
 
-```
+```{eval-rst}
+.. module:: flowsom.tl
+.. currentmodule:: flowsom
+
+.. autosummary::
+    :toctree: generated
+
     tl.ConsensusCluster
     tl.SOM
     tl.map_data_to_codes
@@ -45,7 +73,13 @@ The central class is `FlowSOM`.
 
 ## Plotting
 
-```
+```{eval-rst}
+.. module:: flowsom.pl
+.. currentmodule:: flowsom
+
+.. autosummary::
+    :toctree: generated
+
     pl.FlowSOMmary
     pl.plot_2D_scatters
     pl.plot_labels

docs/contributing.md

@@ -51,7 +51,7 @@ and [prettier][prettier-editors].
 ## Writing tests
 
 ```{note}
-Remember to first install the package with `pip install '-e[dev,test]'`
+Remember to first install the package with `pip install -e '.[dev,test]'`
 ```
 
 This package uses the [pytest][] for automated testing. Please [write tests][scanpy-test-docs] for every function added

docs/notebooks/example.ipynb

@@ -464,7 +464,7 @@
    ],
    "source": [
     "# Visualize data\n",
-    "ax = plt.hist2d(ff_t[:,\"CD4\"].X.flatten(), ff_t[:,\"CD8\"].X.flatten(), bins=200, cmin = 1, cmap = \"jet\")\n",
+    "ax = plt.hist2d(ff_t[:, \"CD4\"].X.flatten(), ff_t[:, \"CD8\"].X.flatten(), bins=200, cmin=1, cmap=\"jet\")\n",
     "plt.show()"
    ]
   },
@@ -520,7 +520,7 @@
     }
    ],
    "source": [
-    "fsom = fs.FlowSOM(ff_t, cols_to_use, xdim = 10, ydim = 10, n_clus = 10)\n",
+    "fsom = fs.FlowSOM(ff_t, cols_to_use, xdim=10, ydim=10, n_clus=10)\n",
     "fsom.mudata"
    ]
   },
@@ -555,7 +555,7 @@
     }
    ],
    "source": [
-    "ff_clustered = fs.flowsom_clustering(ff_t, cols_to_use, xdim = 10, ydim = 10, n_clus = 10)\n",
+    "ff_clustered = fs.flowsom_clustering(ff_t, cols_to_use, xdim=10, ydim=10, n_clus=10)\n",
     "ff_clustered"
    ]
   },
@@ -666,8 +666,8 @@
     }
    ],
    "source": [
-    "p = fs.pl.plot_stars(fsom, background_values = fsom.get_cluster_data().obs.metaclustering)\n",
-    "p"
+    "p = fs.pl.plot_stars(fsom, background_values=fsom.get_cluster_data().obs.metaclustering)\n",
+    "p.show()"
    ]
   },
   {
@@ -706,7 +706,13 @@
     }
    ],
    "source": [
-    "p = fs.pl.plot_stars(fsom, background_values = fsom.get_cluster_data().obs.metaclustering, view = \"grid\", equal_node_size = True, equal_background_size = True)\n",
+    "p = fs.pl.plot_stars(\n",
+    "    fsom,\n",
+    "    background_values=fsom.get_cluster_data().obs.metaclustering,\n",
+    "    view=\"grid\",\n",
+    "    equal_node_size=True,\n",
+    "    equal_background_size=True,\n",
+    ")\n",
     "p"
    ]
   },
@@ -736,12 +742,12 @@
    ],
    "source": [
     "# Read in that data\n",
-    "file = open(\"../../tests/data/gating_result.csv\", \"r\")\n",
+    "file = open(\"../../tests/data/gating_result.csv\")\n",
     "data = csv.reader(file)\n",
     "data = [i[0] for i in data]\n",
     "\n",
     "# Plot\n",
-    "p = fs.pl.plot_pies(fsom, data, background_values = fsom.get_cluster_data().obs.metaclustering)"
+    "p = fs.pl.plot_pies(fsom, data, background_values=fsom.get_cluster_data().obs.metaclustering)"
    ]
   },
   {
@@ -771,7 +777,7 @@
     }
    ],
    "source": [
-    "p = fs.pl.plot_numbers(fsom, level = \"clusters\", text_size = 5)"
+    "p = fs.pl.plot_numbers(fsom, level=\"clusters\", text_size=5)"
    ]
   },
   {
@@ -800,7 +806,7 @@
     }
    ],
    "source": [
-    "p = fs.pl.plot_marker(fsom, marker = np.array([\"CD3\"]))"
+    "p = fs.pl.plot_marker(fsom, marker=np.array([\"CD3\"]))"
    ]
   },
   {
@@ -840,14 +846,14 @@
    ],
    "source": [
     "p = fs.pl.plot_2D_scatters(\n",
-    "        fsom,\n",
-    "        channelpairs=[[\"CD3\", \"CD4\"], [\"CD19\", \"TCRb\"]],\n",
-    "        clusters=[[1, 2], [3]],\n",
-    "        metaclusters=[[4], [5, 6]],\n",
-    "        density=True,\n",
-    "        centers=True,\n",
-    "    )\n",
-    "p"
+    "    fsom,\n",
+    "    channelpairs=[[\"CD3\", \"CD4\"], [\"CD19\", \"TCRb\"]],\n",
+    "    clusters=[[1, 2], [3]],\n",
+    "    metaclusters=[[4], [5, 6]],\n",
+    "    density=True,\n",
+    "    centers=True,\n",
+    ")\n",
+    "p.show()"
    ]
   },
   {
@@ -960,7 +966,12 @@
     }
    ],
    "source": [
-    "features = fs.tl.get_features(fsom, files=[ff_t[1:1000, :], ff_t[1000:2000, :]], level = [\"clusters\", \"metaclusters\"], type = [\"counts\", \"percentages\"])\n",
+    "features = fs.tl.get_features(\n",
+    "    fsom,\n",
+    "    files=[ff_t[1:1000, :], ff_t[1000:2000, :]],\n",
+    "    level=[\"clusters\", \"metaclusters\"],\n",
+    "    type=[\"counts\", \"percentages\"],\n",
+    ")\n",
     "features[\"metacluster_percentages\"]"
    ]
   },
@@ -1075,7 +1086,7 @@
     }
    ],
    "source": [
-    "fs.tl.get_counts(fsom, level = \"clusters\")"
+    "fs.tl.get_counts(fsom, level=\"clusters\")"
    ]
   },
   {
@@ -1244,7 +1255,9 @@
     }
    ],
    "source": [
-    "fs.pp.aggregate_flowframes(filenames = [\"../../tests/data/not_preprocessed.fcs\", \"../../tests/data/not_preprocessed.fcs\"], c_total = 5000)"
+    "fs.pp.aggregate_flowframes(\n",
+    "    filenames=[\"../../tests/data/not_preprocessed.fcs\", \"../../tests/data/not_preprocessed.fcs\"], c_total=5000\n",
+    ")"
    ]
   },
   {
@@ -1301,7 +1314,7 @@
    ],
    "source": [
     "fsom_new = fsom.new_data(ff_t[1:200, :])\n",
-    "fs.pl.plot_stars(fsom_new, background_values = fsom_new.get_cluster_data().obs.metaclustering)"
+    "fs.pl.plot_stars(fsom_new, background_values=fsom_new.get_cluster_data().obs.metaclustering)"
    ]
   },
   {
@@ -1350,7 +1363,7 @@
    ],
    "source": [
     "fsom_subset = fsom.subset(fsom.get_cell_data().obs[\"metaclustering\"] == 4)\n",
-    "fs.pl.plot_stars(fsom_subset, background_values = fsom_subset.get_cluster_data().obs.metaclustering)"
+    "fs.pl.plot_stars(fsom_subset, background_values=fsom_subset.get_cluster_data().obs.metaclustering)"
    ]
   }
  ],

env.yaml

@@ -32,4 +32,4 @@ dependencies:
       - sphinxext-opengraph
       - ipykernel
       - ipython
-      - sphinx-copybutton
+      - sphinx-copybutton