Major renaming

Author: serjisa

.github/workflows/python-publish.yml

@@ -25,7 +25,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v3
       with:
-        python-version: '3.8'
+        python-version: '3.10'
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip

README.md

@@ -1,9 +1,9 @@
-<p align="center"><a href="https://sclitr.readthedocs.io/en/latest/"><img src="docs/source/logo.png" height="150"></a></p>
+<p align="center"><a href="https://clone2vec.readthedocs.io/en/latest/"><img src="docs/source/logo.png" height="150"></a></p>
 
 # clone2vec
 
-![Tests](https://github.com/kharchenkolab/scLiTr/actions/workflows/tests.yml/badge.svg)
-![PyPI](https://img.shields.io/pypi/v/sclitr)
+![Tests](https://github.com/kharchenkolab/clone2vec/actions/workflows/tests.yml/badge.svg)
+![PyPI](https://img.shields.io/pypi/v/clone2vec)
 ![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
 
 clone2vec is a Python package for analysis of lineage tracing coupled with single-cell RNA-Seq.
@@ -21,13 +21,13 @@ will be used as embedding for further analysis.
 
 ## Benchmarking illustrations
 
-See [Technical Note](https://github.com/kharchenkolab/scLiTr/blob/main/docs/Technical_note.pdf) for more details.
+See [Technical Note](https://github.com/kharchenkolab/clone2vec/blob/main/docs/Technical_note.pdf) for more details.
 
 ## Installation
 
 clone2vec might be installed via `pip` (takes 1-2 minutes on Google Colab):
 ```bash
-pip install sclitr
+pip install clone2vec
 ```
 or the latest development version can be installed from GitHub using:
 ```bash
@@ -45,5 +45,5 @@ on the following systems:
 
 ## Documentation and tutorials
 
-Please visit [documentation web-site](https://sclitr.readthedocs.io/en/latest/) to check out API description and a few
+Please visit [documentation web-site](https://clone2vec.readthedocs.io/en/latest/) to check out API description and a few
 tutorials with analysis.

sclitr/__init__.py clone2vec/__init__.pysclitr/__init__.py renamed to clone2vec/__init__.py

@@ -124,7 +124,7 @@ def _prepare_pools(
                 validation_key = adata.uns["gs"]["obs_key"]
                 validation_value = adata.uns["gs"]["keys"]["validation"]
             except:
-                raise ValueError("gs_key not found in adata.uns. Please run sl.tl.gs() or set validation_key and validation_value.")
+                raise ValueError("gs_key not found in adata.uns. Please run c2v.tl.gs() or set validation_key and validation_value.")
         else:
             validation_key = adata.uns[gs_key]["obs_key"]
             validation_value = adata.uns[gs_key]["keys"]["validation"]
@@ -298,7 +298,7 @@ def catboost(
     obsm_key : str
         Key in `adata.obsm` to use for the response variable.
     gs_key : str | None, optional
-        Key in `adata.obs` with `sl.tl.gs()` parameters. Default is None.
+        Key in `adata.obs` with `c2v.tl.gs()` parameters. Default is None.
     validation_key : str | None, optional
         Key in `adata.obs` to use for the train/validation split. If None, reconstructed from
         the adata.uns[gs_key]. Default is None.

sclitr/associations.py clone2vec/associations.pysclitr/associations.py renamed to clone2vec/associations.py

@@ -768,7 +768,7 @@ def clone2vec_Poi(
 
     start = logg.info("fitting clone2vec_Poi embeddings")
     if obsp_key not in clones.obsp:
-        raise KeyError(f"Graph '{obsp_key}' not found in clones.obsp. Did you run `sl.tl.clonal_nn(adata, clones)` before?")
+        raise KeyError(f"Graph '{obsp_key}' not found in clones.obsp. Did you run `c2v.tl.clonal_nn(adata, clones)` before?")
 
     start_time = time.time()
 

sclitr/catboost.py clone2vec/catboost.pysclitr/catboost.py renamed to clone2vec/catboost.py

@@ -2076,7 +2076,7 @@ def predictors_comparison(
         try:
             df = shapdata.varm["signed_mean_shap"]
         except KeyError:
-            raise KeyError("varm['signed_mean_shap'] not found. Please run sl.utils.correct_shap() first with flags `normalize=False` and `correct_sign=True`.")
+            raise KeyError("varm['signed_mean_shap'] not found. Please run c2v.utils.correct_shap() first with flags `normalize=False` and `correct_sign=True`.")
     else:
         logg.warning(f"We expect sign-corrected and not normalized by maximum value SHAPs in varm['{varm_key}'].")
         df = shapdata.varm[varm_key]
@@ -2445,7 +2445,7 @@ def catboost_perfomance(
     from .associations import _fast_corr
 
     if "catboost_info" not in shapdata.uns.keys():
-        raise ValueError("catboost_info not found in shapdata.uns. Please, run `sl.tl.catboost()` first.")
+        raise ValueError("catboost_info not found in shapdata.uns. Please, run `c2v.tl.catboost()` first.")
 
     obsm_key = shapdata.uns["catboost_info"]["obsm_key"]
     fates_used = shapdata.uns["catboost_info"]["fates_used"]