Aug 24

docs/QuickStart.md

@@ -1,11 +1,50 @@
 # Quick Start
 
-## Installation
+<!-- ## Installation
 ```
 pip install birdstem
 ```
 
 ## test on sample data
 ```
 import birdstem as bs
-```
+``` -->
+
+
+## Fit an AdaSTEM model
+```py
+from BirdSTEM.model.AdaSTEM import AdaSTEM, AdaSTEMHurdle
+from BirdSTEM.model.Hurdle import Hurdle
+from xgboost import XGBClassifier, XGBRegressor
+
+SAVE_DIR = './'
+
+base_model = Hurdle(classifier=XGBClassifier(tree_method='hist',random_state=42, verbosity = 0, n_jobs=1),
+                    regressor=XGBRegressor(tree_method='hist',random_state=42, verbosity = 0, n_jobs=1))
+
+
+model = AdaSTEMHurdle(base_model=base_model,
+                        ensemble_fold = 10,
+                        min_ensemble_required= 7,
+                        grid_len_lon_upper_threshold=50,
+                            grid_len_lon_lower_threshold=10,
+                            grid_len_lat_upper_threshold=50,
+                            grid_len_lat_lower_threshold=10,
+                            points_lower_threshold = 50,
+                            temporal_start = 0, temporal_end=1400, temporal_step=100, temporal_bin_interval = 100,
+                            stixel_training_size_threshold = 50, ## important, should be consistent with points_lower_threshold
+                            save_gridding_plot = True,
+                            save_tmp = True,
+                            save_dir=SAVE_DIR,
+                            sample_weights_for_classifier=True)
+
+## fit
+model.fit(X_train,y_train)
+
+## predict
+pred_mean, pred_std = model.predict(X_test)
+pred_mean = np.where(pred_mean>0, pred_mean, 0)
+eval_metrics = AdaSTEM.eval_STEM_res('hurdle',y_test, pred_mean)
+print(eval_metrics)
+
+```

docs/index.md

@@ -1,17 +1,52 @@
-# Welcome to MkDocs
+# Welcome to BirdSTEM
 
-For full documentation visit [mkdocs.org](https://www.mkdocs.org).
+<!-- For full documentation visit [mkdocs.org](https://www.mkdocs.org). -->
 
 ## Commands
 
-* `mkdocs new [dir-name]` - Create a new project.
-* `mkdocs serve` - Start the live-reloading docs server.
-* `mkdocs build` - Build the documentation site.
-* `mkdocs -h` - Print help message and exit.
+## Installation
 
-## Project layout
+## Fit an AdaSTEM model
+```py
+from BirdSTEM.model.AdaSTEM import AdaSTEM, AdaSTEMHurdle
+from BirdSTEM.model.Hurdle import Hurdle
+from xgboost import XGBClassifier, XGBRegressor
+
+SAVE_DIR = './'
+
+base_model = Hurdle(classifier=XGBClassifier(tree_method='hist',random_state=42, verbosity = 0, n_jobs=1),
+                    regressor=XGBRegressor(tree_method='hist',random_state=42, verbosity = 0, n_jobs=1))
+
+
+model = AdaSTEMHurdle(base_model=base_model,
+                        ensemble_fold = 10,
+                        min_ensemble_required= 7,
+                        grid_len_lon_upper_threshold=50,
+                            grid_len_lon_lower_threshold=10,
+                            grid_len_lat_upper_threshold=50,
+                            grid_len_lat_lower_threshold=10,
+                            points_lower_threshold = 50,
+                            temporal_start = 0, temporal_end=1400, temporal_step=100, temporal_bin_interval = 100,
+                            stixel_training_size_threshold = 50, ## important, should be consistent with points_lower_threshold
+                            save_gridding_plot = True,
+                            save_tmp = True,
+                            save_dir=SAVE_DIR,
+                            sample_weights_for_classifier=True)
+
+## fit
+model.fit(X_train,y_train)
+
+## predict
+pred_mean, pred_std = model.predict(X_test)
+pred_mean = np.where(pred_mean>0, pred_mean, 0)
+eval_metrics = AdaSTEM.eval_STEM_res('hurdle',y_test, pred_mean)
+print(eval_metrics)
+
+```
+
+<!-- ## Project layout
 
     mkdocs.yml    # The configuration file.
     docs/
         index.md  # The documentation homepage.
-        ...       # Other markdown pages, images and other files.
+        ...       # Other markdown pages, images and other files. -->