init_fbp_running_preds.py

def fbpTrainPredict(df, forecast_period):
    """
    Uses FB Prophet and fits to a appropriately formatted DF. Makes a prediction N days into 
    the future based on given forecast period. Returns predicted values as a DF.
    """
    # Setting up prophet
    m = Prophet(
        daily_seasonality=True, 
        yearly_seasonality=True, 
        weekly_seasonality=True
    )
    
    # Fitting to the prices
    m.fit(df[['ds', 'y']])
    
    # Future DF
    future = m.make_future_dataframe(periods=forecast_period)
        
    # Predicting values
    forecast = m.predict(future)

    # Returning a set of predicted values
    return forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']]
  
  
def runningFBP(prices, forecast_period, training_days):
    """
    Runs Facebook Prophet to get predictions over a set period 
    of time. Uses FBP to train and predict every N days and gets the 
    price forecasts.
    """
    # DF for the predicted values
    pred_df = pd.DataFrame()

    # Running the model each day
    for i in tqdm(range(training_days, len(prices)+1)):
        
        # Training and Predicting the last day on the forecast
        forecast = fbpTrainPredict(
            prices[i-training_days:i], 
            forecast_period
        ).tail(1)
        
        # Adding the forecast predicted
        pred_df = pred_df.append(forecast, ignore_index=True)
        
    # Prepping for merge by converting date values to be the same type
    pred_df['ds'] = pred_df['ds'].apply(lambda x: str(x)[:10])

    prices['ds'] = prices['ds'].apply(lambda x: str(x)[:10])
    
    # Shifting the forecasts back in order to compare it to the 'current' open values
    pred_df[['yhat', 'yhat_lower', 'yhat_upper']] = pred_df[['yhat', 'yhat_lower', 'yhat_upper']].shift(-forecast_period)
    
    # Merging with the prices DF in order to compare values for positions later
    merge_df = prices[['ds', 'open']].merge(
        pred_df,
        on='ds',
        how='outer'
    ).dropna().set_index('ds')

    return merge_df