Example for stumpy

app/model/stumpy.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+
+
+# In[1]:
+
+
+# this definition exposes all python module imports that should be available in all subsequent commands
+import json
+import numpy as np
+import pandas as pd
+import datetime as dt
+import stumpy
+# ...
+# global constants
+MODEL_DIRECTORY = "/srv/app/model/data/"
+
+
+
+
+
+
+
+
+# In[36]:
+
+
+# this cell is not executed from MLTK and should only be used for staging data into the notebook environment
+def stage(name):
+    with open("data/"+name+".csv", 'r') as f:
+        df = pd.read_csv(f)
+    with open("data/"+name+".json", 'r') as f:
+        param = json.load(f)
+    return df, param
+
+
+
+
+
+
+
+
+# In[38]:
+
+
+# initialize your model
+# available inputs: data and parameters
+# returns the model object which will be used as a reference to call fit, apply and summary subsequently
+def init(df,param):
+    model = {}
+    return model
+
+
+
+
+
+
+
+
+# In[40]:
+
+
+# train your model
+# returns a fit info json object and may modify the model object
+def fit(model,df,param):
+    # model.fit()
+    info = {"message": "model created"}
+    return info
+
+
+
+
+
+
+
+
+# In[42]:
+
+
+# apply your model
+# returns the calculated results
+def apply(model,df,param):
+    m = 24
+    if 'options' in param:
+        if 'params' in param['options']:
+            if 'm' in param['options']['params']:
+                m = int(param['options']['params']['m'])
+    target = param['target_variables'][0]
+    mp = stumpy.stump(df[target], m)    
+    result = pd.DataFrame(mp[:, 0], columns=['matrix_profile'])
+    return pd.concat([df, result], axis=1)
+
+
+
+
+
+
+
+
+# In[33]:
+
+
+# save model to name in expected convention "<algo_name>_<model_name>"
+def save(model,name):
+    with open(MODEL_DIRECTORY + name + ".json", 'w') as file:
+        json.dump(model, file)
+    return model
+
+
+
+
+
+
+# In[34]:
+
+
+# load model from name in expected convention "<algo_name>_<model_name>"
+def load(name):
+    model = {}
+    with open(MODEL_DIRECTORY + name + ".json", 'r') as file:
+        model = json.load(file)
+    return model
+
+
+
+
+
+
+# In[35]:
+
+
+# return a model summary
+def summary(model=None):
+    returns = {"version": {"numpy": np.__version__, "pandas": pd.__version__} }
+    return returns
+
+
+
+
+