add logo

chenyangkang · Sep 7, 2023 · 0e29a8b · 0e29a8b
1 parent 8a95eeb
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Showing 5 changed files with 16 additions and 8 deletions.
diff --git a/.gitignore b/.gitignore
@@ -2,6 +2,5 @@
 *.csv
 *.txt
 *.pkl
-*.gif
 */__pycache__/*
 __pycache__/*
diff --git a/docs/Untitled-1.psd b/docs/Untitled-1.psd
diff --git a/docs/logo.png b/docs/logo.png
diff --git a/mkdocs.yml b/mkdocs.yml
@@ -1,5 +1,5 @@
-site_name: BirdSTEM
-site_url: https://chenyangkag.github.io/BirdSTEM/
+site_name: stemflow
+site_url: https://chenyangkag.github.io/stemflow/
 theme:
   name: material
 
@@ -36,6 +36,8 @@ theme:
 
   font:
     text: Open Sans
+  logo: logo.png
+  favicon: logo.png
 
 
 

diff --git a/setup.py b/setup.py
@@ -8,21 +8,28 @@
     long_description = "\n" + fh.read()
 
 VERSION = '0.0.3'
-DESCRIPTION = 'AdaSTEM model for daily abundance estimation using eBird citizen science data'
-LONG_DESCRIPTION = 'TBD'
+DESCRIPTION = 'A package for Adaptive Spatio-Temporal Model (AdaSTEM) in python'
+LONG_DESCRIPTION = 'stemflow is a toolkit for Adaptive Spatio-Temporal Model (AdaSTEM) in python. A typical usage is daily abundance estimation using eBird citizen science data. It leverages the "adjacency" information of surrounding target values in space and time, to predict the classes/continues values of target spatial-temporal point. In the demo, we use a two-step hurdle model as "base model", with XGBoostClassifier for occurence modeling and XGBoostRegressor for abundance modeling.'
 
 # Setting up
 setup(
-    name="BirdSTEM",
+    name="stemflow",
     version=VERSION,
     author="Yangkang Chen",
     author_email="chenyangkang24@outlook.com",
     description=DESCRIPTION,
     long_description_content_type="text/markdown",
     long_description=long_description,
     packages=find_packages(),
-    install_requires=[''],
-    keywords=['python', 'ebird', 'spatial-temporal model', 'citizen science', 'spatial temporal exploratory model',
+    install_requires=['numpy>=1.24.3',
+                      'matplotlib>=3.7.1',
+                      'pandas>=2.0.3',
+                      'geopandas>=0.11.1',
+                      'tqdm>=4.65.0',
+                      'h3pandas>=0.2.4',
+                      'scikit-learn>=1.2.2',
+                      'seaborn>=0.11.2'],
+    keywords=['python', 'spatial-temporal model', 'ebird', 'citizen science', 'spatial temporal exploratory model',
               'STEM','AdaSTEM','abundance','phenology'],
     classifiers=[
         "Development Status :: 1 - Planning",