GetEvaluation.hs

{-# LANGUAGE DeriveDataTypeable #-}
{-# LANGUAGE DeriveGeneric      #-}
{-# LANGUAGE OverloadedStrings  #-}
{-# LANGUAGE RecordWildCards    #-}
{-# LANGUAGE TypeFamilies       #-}

{-# OPTIONS_GHC -fno-warn-unused-imports #-}
{-# OPTIONS_GHC -fno-warn-unused-binds   #-}
{-# OPTIONS_GHC -fno-warn-unused-matches #-}

-- Derived from AWS service descriptions, licensed under Apache 2.0.

-- |
-- Module      : Network.AWS.MachineLearning.GetEvaluation
-- Copyright   : (c) 2013-2016 Brendan Hay
-- License     : Mozilla Public License, v. 2.0.
-- Maintainer  : Brendan Hay <brendan.g.hay@gmail.com>
-- Stability   : auto-generated
-- Portability : non-portable (GHC extensions)
--
-- Returns an @Evaluation@ that includes metadata as well as the current status of the @Evaluation@ .
--
--
module Network.AWS.MachineLearning.GetEvaluation
    (
    -- * Creating a Request
      getEvaluation
    , GetEvaluation
    -- * Request Lenses
    , geEvaluationId

    -- * Destructuring the Response
    , getEvaluationResponse
    , GetEvaluationResponse
    -- * Response Lenses
    , gersStatus
    , gersPerformanceMetrics
    , gersLastUpdatedAt
    , gersCreatedAt
    , gersComputeTime
    , gersInputDataLocationS3
    , gersMLModelId
    , gersStartedAt
    , gersFinishedAt
    , gersCreatedByIAMUser
    , gersName
    , gersLogURI
    , gersEvaluationId
    , gersMessage
    , gersEvaluationDataSourceId
    , gersResponseStatus
    ) where

import           Network.AWS.Lens
import           Network.AWS.MachineLearning.Types
import           Network.AWS.MachineLearning.Types.Product
import           Network.AWS.Prelude
import           Network.AWS.Request
import           Network.AWS.Response

-- | /See:/ 'getEvaluation' smart constructor.
newtype GetEvaluation = GetEvaluation'
    { _geEvaluationId :: Text
    } deriving (Eq,Read,Show,Data,Typeable,Generic)

-- | Creates a value of 'GetEvaluation' with the minimum fields required to make a request.
--
-- Use one of the following lenses to modify other fields as desired:
--
-- * 'geEvaluationId' - The ID of the @Evaluation@ to retrieve. The evaluation of each @MLModel@ is recorded and cataloged. The ID provides the means to access the information.
getEvaluation
    :: Text -- ^ 'geEvaluationId'
    -> GetEvaluation
getEvaluation pEvaluationId_ =
    GetEvaluation'
    { _geEvaluationId = pEvaluationId_
    }

-- | The ID of the @Evaluation@ to retrieve. The evaluation of each @MLModel@ is recorded and cataloged. The ID provides the means to access the information.
geEvaluationId :: Lens' GetEvaluation Text
geEvaluationId = lens _geEvaluationId (\ s a -> s{_geEvaluationId = a});

instance AWSRequest GetEvaluation where
        type Rs GetEvaluation = GetEvaluationResponse
        request = postJSON machineLearning
        response
          = receiveJSON
              (\ s h x ->
                 GetEvaluationResponse' <$>
                   (x .?> "Status") <*> (x .?> "PerformanceMetrics") <*>
                     (x .?> "LastUpdatedAt")
                     <*> (x .?> "CreatedAt")
                     <*> (x .?> "ComputeTime")
                     <*> (x .?> "InputDataLocationS3")
                     <*> (x .?> "MLModelId")
                     <*> (x .?> "StartedAt")
                     <*> (x .?> "FinishedAt")
                     <*> (x .?> "CreatedByIamUser")
                     <*> (x .?> "Name")
                     <*> (x .?> "LogUri")
                     <*> (x .?> "EvaluationId")
                     <*> (x .?> "Message")
                     <*> (x .?> "EvaluationDataSourceId")
                     <*> (pure (fromEnum s)))

instance Hashable GetEvaluation

instance NFData GetEvaluation

instance ToHeaders GetEvaluation where
        toHeaders
          = const
              (mconcat
                 ["X-Amz-Target" =#
                    ("AmazonML_20141212.GetEvaluation" :: ByteString),
                  "Content-Type" =#
                    ("application/x-amz-json-1.1" :: ByteString)])

instance ToJSON GetEvaluation where
        toJSON GetEvaluation'{..}
          = object
              (catMaybes
                 [Just ("EvaluationId" .= _geEvaluationId)])

instance ToPath GetEvaluation where
        toPath = const "/"

instance ToQuery GetEvaluation where
        toQuery = const mempty

-- | Represents the output of a @GetEvaluation@ operation and describes an @Evaluation@ .
--
--
--
-- /See:/ 'getEvaluationResponse' smart constructor.
data GetEvaluationResponse = GetEvaluationResponse'
    { _gersStatus                 :: !(Maybe EntityStatus)
    , _gersPerformanceMetrics     :: !(Maybe PerformanceMetrics)
    , _gersLastUpdatedAt          :: !(Maybe POSIX)
    , _gersCreatedAt              :: !(Maybe POSIX)
    , _gersComputeTime            :: !(Maybe Integer)
    , _gersInputDataLocationS3    :: !(Maybe Text)
    , _gersMLModelId              :: !(Maybe Text)
    , _gersStartedAt              :: !(Maybe POSIX)
    , _gersFinishedAt             :: !(Maybe POSIX)
    , _gersCreatedByIAMUser       :: !(Maybe Text)
    , _gersName                   :: !(Maybe Text)
    , _gersLogURI                 :: !(Maybe Text)
    , _gersEvaluationId           :: !(Maybe Text)
    , _gersMessage                :: !(Maybe Text)
    , _gersEvaluationDataSourceId :: !(Maybe Text)
    , _gersResponseStatus         :: !Int
    } deriving (Eq,Read,Show,Data,Typeable,Generic)

-- | Creates a value of 'GetEvaluationResponse' with the minimum fields required to make a request.
--
-- Use one of the following lenses to modify other fields as desired:
--
-- * 'gersStatus' - The status of the evaluation. This element can have one of the following values:     * @PENDING@ - Amazon Machine Language (Amazon ML) submitted a request to evaluate an @MLModel@ .    * @INPROGRESS@ - The evaluation is underway.    * @FAILED@ - The request to evaluate an @MLModel@ did not run to completion. It is not usable.    * @COMPLETED@ - The evaluation process completed successfully.    * @DELETED@ - The @Evaluation@ is marked as deleted. It is not usable.
--
-- * 'gersPerformanceMetrics' - Measurements of how well the @MLModel@ performed using observations referenced by the @DataSource@ . One of the following metric is returned based on the type of the @MLModel@ :      * BinaryAUC: A binary @MLModel@ uses the Area Under the Curve (AUC) technique to measure performance.      * RegressionRMSE: A regression @MLModel@ uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.     * MulticlassAvgFScore: A multiclass @MLModel@ uses the F1 score technique to measure performance.  For more information about performance metrics, please see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide> .
--
-- * 'gersLastUpdatedAt' - The time of the most recent edit to the @Evaluation@ . The time is expressed in epoch time.
--
-- * 'gersCreatedAt' - The time that the @Evaluation@ was created. The time is expressed in epoch time.
--
-- * 'gersComputeTime' - The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the @Evaluation@ , normalized and scaled on computation resources. @ComputeTime@ is only available if the @Evaluation@ is in the @COMPLETED@ state.
--
-- * 'gersInputDataLocationS3' - The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
--
-- * 'gersMLModelId' - The ID of the @MLModel@ that was the focus of the evaluation.
--
-- * 'gersStartedAt' - The epoch time when Amazon Machine Learning marked the @Evaluation@ as @INPROGRESS@ . @StartedAt@ isn't available if the @Evaluation@ is in the @PENDING@ state.
--
-- * 'gersFinishedAt' - The epoch time when Amazon Machine Learning marked the @Evaluation@ as @COMPLETED@ or @FAILED@ . @FinishedAt@ is only available when the @Evaluation@ is in the @COMPLETED@ or @FAILED@ state.
--
-- * 'gersCreatedByIAMUser' - The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.
--
-- * 'gersName' - A user-supplied name or description of the @Evaluation@ .
--
-- * 'gersLogURI' - A link to the file that contains logs of the @CreateEvaluation@ operation.
--
-- * 'gersEvaluationId' - The evaluation ID which is same as the @EvaluationId@ in the request.
--
-- * 'gersMessage' - A description of the most recent details about evaluating the @MLModel@ .
--
-- * 'gersEvaluationDataSourceId' - The @DataSource@ used for this evaluation.
--
-- * 'gersResponseStatus' - -- | The response status code.
getEvaluationResponse
    :: Int -- ^ 'gersResponseStatus'
    -> GetEvaluationResponse
getEvaluationResponse pResponseStatus_ =
    GetEvaluationResponse'
    { _gersStatus = Nothing
    , _gersPerformanceMetrics = Nothing
    , _gersLastUpdatedAt = Nothing
    , _gersCreatedAt = Nothing
    , _gersComputeTime = Nothing
    , _gersInputDataLocationS3 = Nothing
    , _gersMLModelId = Nothing
    , _gersStartedAt = Nothing
    , _gersFinishedAt = Nothing
    , _gersCreatedByIAMUser = Nothing
    , _gersName = Nothing
    , _gersLogURI = Nothing
    , _gersEvaluationId = Nothing
    , _gersMessage = Nothing
    , _gersEvaluationDataSourceId = Nothing
    , _gersResponseStatus = pResponseStatus_
    }

-- | The status of the evaluation. This element can have one of the following values:     * @PENDING@ - Amazon Machine Language (Amazon ML) submitted a request to evaluate an @MLModel@ .    * @INPROGRESS@ - The evaluation is underway.    * @FAILED@ - The request to evaluate an @MLModel@ did not run to completion. It is not usable.    * @COMPLETED@ - The evaluation process completed successfully.    * @DELETED@ - The @Evaluation@ is marked as deleted. It is not usable.
gersStatus :: Lens' GetEvaluationResponse (Maybe EntityStatus)
gersStatus = lens _gersStatus (\ s a -> s{_gersStatus = a});

-- | Measurements of how well the @MLModel@ performed using observations referenced by the @DataSource@ . One of the following metric is returned based on the type of the @MLModel@ :      * BinaryAUC: A binary @MLModel@ uses the Area Under the Curve (AUC) technique to measure performance.      * RegressionRMSE: A regression @MLModel@ uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.     * MulticlassAvgFScore: A multiclass @MLModel@ uses the F1 score technique to measure performance.  For more information about performance metrics, please see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide> .
gersPerformanceMetrics :: Lens' GetEvaluationResponse (Maybe PerformanceMetrics)
gersPerformanceMetrics = lens _gersPerformanceMetrics (\ s a -> s{_gersPerformanceMetrics = a});

-- | The time of the most recent edit to the @Evaluation@ . The time is expressed in epoch time.
gersLastUpdatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime)
gersLastUpdatedAt = lens _gersLastUpdatedAt (\ s a -> s{_gersLastUpdatedAt = a}) . mapping _Time;

-- | The time that the @Evaluation@ was created. The time is expressed in epoch time.
gersCreatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime)
gersCreatedAt = lens _gersCreatedAt (\ s a -> s{_gersCreatedAt = a}) . mapping _Time;

-- | The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the @Evaluation@ , normalized and scaled on computation resources. @ComputeTime@ is only available if the @Evaluation@ is in the @COMPLETED@ state.
gersComputeTime :: Lens' GetEvaluationResponse (Maybe Integer)
gersComputeTime = lens _gersComputeTime (\ s a -> s{_gersComputeTime = a});

-- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
gersInputDataLocationS3 :: Lens' GetEvaluationResponse (Maybe Text)
gersInputDataLocationS3 = lens _gersInputDataLocationS3 (\ s a -> s{_gersInputDataLocationS3 = a});

-- | The ID of the @MLModel@ that was the focus of the evaluation.
gersMLModelId :: Lens' GetEvaluationResponse (Maybe Text)
gersMLModelId = lens _gersMLModelId (\ s a -> s{_gersMLModelId = a});

-- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as @INPROGRESS@ . @StartedAt@ isn't available if the @Evaluation@ is in the @PENDING@ state.
gersStartedAt :: Lens' GetEvaluationResponse (Maybe UTCTime)
gersStartedAt = lens _gersStartedAt (\ s a -> s{_gersStartedAt = a}) . mapping _Time;

-- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as @COMPLETED@ or @FAILED@ . @FinishedAt@ is only available when the @Evaluation@ is in the @COMPLETED@ or @FAILED@ state.
gersFinishedAt :: Lens' GetEvaluationResponse (Maybe UTCTime)
gersFinishedAt = lens _gersFinishedAt (\ s a -> s{_gersFinishedAt = a}) . mapping _Time;

-- | The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.
gersCreatedByIAMUser :: Lens' GetEvaluationResponse (Maybe Text)
gersCreatedByIAMUser = lens _gersCreatedByIAMUser (\ s a -> s{_gersCreatedByIAMUser = a});

-- | A user-supplied name or description of the @Evaluation@ .
gersName :: Lens' GetEvaluationResponse (Maybe Text)
gersName = lens _gersName (\ s a -> s{_gersName = a});

-- | A link to the file that contains logs of the @CreateEvaluation@ operation.
gersLogURI :: Lens' GetEvaluationResponse (Maybe Text)
gersLogURI = lens _gersLogURI (\ s a -> s{_gersLogURI = a});

-- | The evaluation ID which is same as the @EvaluationId@ in the request.
gersEvaluationId :: Lens' GetEvaluationResponse (Maybe Text)
gersEvaluationId = lens _gersEvaluationId (\ s a -> s{_gersEvaluationId = a});

-- | A description of the most recent details about evaluating the @MLModel@ .
gersMessage :: Lens' GetEvaluationResponse (Maybe Text)
gersMessage = lens _gersMessage (\ s a -> s{_gersMessage = a});

-- | The @DataSource@ used for this evaluation.
gersEvaluationDataSourceId :: Lens' GetEvaluationResponse (Maybe Text)
gersEvaluationDataSourceId = lens _gersEvaluationDataSourceId (\ s a -> s{_gersEvaluationDataSourceId = a});

-- | -- | The response status code.
gersResponseStatus :: Lens' GetEvaluationResponse Int
gersResponseStatus = lens _gersResponseStatus (\ s a -> s{_gersResponseStatus = a});

instance NFData GetEvaluationResponse