update readmi with examples usage

README.md

@@ -12,24 +12,63 @@ optimization
 classes has been refactored based on implementations from ***Fedot.Industrial*** legacy.
  - To score change point detection models functions from ***TSAD*** lib has been used\adopted.
 
-#### Tasks:
-
-...
-
 ## To set up local project dependencies:
 ```commandline
  python3 setup.py build
 ```
 
+## Example API usage:
+
+#### №1 SingularSequenceTransformer
+```Python3
+# init libs
+from models.SubspaceBased import SingularSequenceTransformer
+from data.SythData import SinusoidWaves
+from utils.Reports import SummaryReport
+import matplotlib.pyplot as plt
+
+# init df
+data = SinusoidWaves(length_data=1000,
+ cps_number=20,
+ white_noise_level="min").get()
+
+# extract target array
+target_array = data['x'].values
+
+#define some hyperparameters apriori.
+model = SingularSequenceTransformer(
+ queue_window=10,
+ n_components=2,
+ is_fast_parameter_selection=True,
+ threshold_quantile_coeff=0.95).fit(x_train=list(target_array), y_train=None)
+
+# predict change points at target_array
+cps_pred = model.predict(target_array=target_array)
+
+# save all results at one dataframe
+data['cps_pred'] = cps_pred
+
+# plot results
+data.plot(figsize=(20,5))
+
+# get scores based on initial dataframe and model results
+df_summary_report = SummaryReport().create_report(df=data,
+ column_name_preds="cps_pred",
+ column_name_original="CPs"
+ )
+```
+![Plot results](img.png)
+
 TO DO:
 
-1. Docker images for example files at examples dir.
-2. Hybrid model
-3. Evolution optimization for model hyperparameters.
-4. default notebook examples
-5. FastAPI service for end-to-end use in container.
-6. Advanced change point detection models.
-7. More tests.
+1. Docker images to reproduce examples.
+2. CPD significant checker based on queue distance algorithm and statistical information for each subsequcnes.
+3. Hybrid model based on master thesis.
+4. Some more optimization hyperparameters algorithms.
+5. default notebook examples for each model.
+6. FastAPI service for end-to-end use in container.
+7. Advanced change point detection models based on 
+8. More tests.
 
 [//]: # (Here you find notebooks with Change Point Detection methods in Petroleum Data. Mainly I focus to experiment with Fedot.Industrial library.)