def save_prediction():
    '''

    This router function saves the prediction results generated from a computed
    svm or svr prediction session.  During its attempt, it returns a json
    string, with the following value:

        - integer, codified indicator of save attempt:
            - 0, successfully stored the prediction result
            - 1, unsuccessfully stored the prediction result
            - 2, status was not 'valid'
            - 3, improper request submitted

    '''

    if request.method == 'POST':
        # programmatic-interface
        if request.get_json():
            results = request.get_json()
            data = results['data']

        # web-interface: double decoder required, since nested encoding
        elif request.form:
            results = request.form
            data = json.loads(json.loads(results['data']))

        # invalid request
        else:
            return json.dumps({'status': 3})

        # local variables
        status = results['status']
        type = results['model_type']
        title = results['title']

        # save prediction
        if status == 'valid':
            prediction = Prediction()
            result = prediction.save(data, type, title)['result']

            # notification: prediction status
            if result == 0:
                return json.dumps({'status': 0})
            else:
                return json.dumps({'status': 1})

        # notification: status not valid
        else:
            return json.dumps({'status': 2})
Exemple #2
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def save_prediction():
    '''

    This router function saves the prediction results generated from a computed
    svm or svr prediction session.  During its attempt, it returns a json
    string, with the following value:

        - integer, codified indicator of save attempt:
            - 0, successfully stored the prediction result
            - 1, unsuccessfully stored the prediction result
            - 2, status was not 'valid'
            - 3, improper request submitted

    '''

    if request.method == 'POST':
        # programmatic-interface
        if request.get_json():
            results = request.get_json()
            data = results['data']

        # web-interface: double decoder required, since nested encoding
        elif request.form:
            results = request.form
            data = json.loads(json.loads(results['data']))

        # invalid request
        else:
            return json.dumps({'status': 3})

        # local variables
        status = results['status']
        type = results['model_type']
        title = results['title']

        # save prediction
        if status == 'valid':
            prediction = Prediction()
            result = prediction.save(data, type, title)['result']

            # notification: prediction status
            if result == 0:
                return json.dumps({'status': 0})
            else:
                return json.dumps({'status': 1})

        # notification: status not valid
        else:
            return json.dumps({'status': 2})
Exemple #3
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def retrieve_prediction_titles():
    '''

    This router function retrieves all prediction titles, stored via the
    'save_prediction' router function. During its attempt, it returns a json
    string, with the following value:

        - integer, codified indicator of database query:
            - 0, successful retrieval of prediction titles
            - 1, unsuccessful retrieval of prediction titles
            - 2, improper request submitted
        - string, array of prediction titles

    '''

    if request.method == 'POST':
        # programmatic-interface
        if request.get_json():
            results = request.get_json()
            model_type = results['model_type']

        # web-interface
        elif request.form:
            results = request.form
            args = json.loads(results['args'])
            model_type = args['model_type']

        # invalid request
        else:
            return json.dumps({'status': 2})

        # query database
        prediction = Prediction()
        response = prediction.get_all_titles(model_type)

        # return results: datetime is not serializable, without 'default'
        #                 string serializer, for incompatible objects.
        #
        if response['status']:
            return json.dumps({
                'status': 0,
                'titles': response['result']
            },
                              default=str)

        else:
            return json.dumps({'status': 1, 'titles': None})
def retrieve_prediction_titles():
    '''

    This router function retrieves all prediction titles, stored via the
    'save_prediction' router function. During its attempt, it returns a json
    string, with the following value:

        - integer, codified indicator of database query:
            - 0, successful retrieval of prediction titles
            - 1, unsuccessful retrieval of prediction titles
            - 2, improper request submitted
        - string, array of prediction titles

    '''

    if request.method == 'POST':
        # programmatic-interface
        if request.get_json():
            results = request.get_json()
            model_type = results['model_type']

        # web-interface
        elif request.form:
            results = request.form
            args = json.loads(results['args'])
            model_type = args['model_type']

        # retrieve all titles
        else:
            model_type = 'all'

        # query database
        prediction = Prediction()
        response = prediction.get_all_titles(model_type)

        # return results: datetime is not serializable, without 'default'
        #                 string serializer, for incompatible objects.
        #
        if response['status']:
            return json.dumps({
                'status': 0,
                'titles': response['result']
            }, default=str)

        else:
            return json.dumps({'status': 1, 'titles': None})
def retrieve_prediction():
    '''

    This router function retrieves a specified prediction parameter.

        - integer, codified indicator of save attempt:
            - 0, successful retrieval of specified prediction parameter
            - 1, unsuccessful retrieval of specified prediction parameter
            - 2, improper request submitted
            - 3, invalid 'model_type'
        - string, prediction parameter

    '''

    if request.method == 'POST':
        # programmatic-interface
        if request.get_json():
            results = request.get_json()
            id_result = results['id_result']

        # web-interface
        elif request.form:
            results = request.form
            id_result = json.loads(results['id_result'])

        # invalid request
        else:
            return json.dumps({'status': 2})

        # query database and return results
        prediction = Prediction()
        result = prediction.get_result(id_result)
        model_type = prediction.get_model_type(id_result)['result']

        if model_type == 'svm':
            classes = prediction.get_value(id_result, model_type, 'class')
            df = prediction.get_value(id_result, model_type, 'decision_function')
            prob = prediction.get_value(id_result, model_type, 'probability')

            if (
                result['status'] and
                classes['status'] and
                df['status'] and
                prob['status']
            ):
                # return results: queried 'decimal' database values, are not
                #                 json serializable, without using the 'default'
                #                 string serializer.
                #
                return json.dumps({
                    'status': 0,
                    'result': result['result'],
                    'classes': classes['result'],
                    'decision_function': df['result'],
                    'probability': prob['result']
                }, default=str)
            else:
                return json.dumps({'status': 1})

        elif model_type == 'svr':
            coefficient = prediction.get_value(id_result, model_type, 'r2')

            if coefficient['status']:
                # return results: queried 'decimal' database values, are not
                #                 json serializable, without using the 'default'
                #                 string serializer.
                #
                return json.dumps({
                    'status': 0,
                    'result': result['result'],
                    'r2': coefficient['result']
                }, default=str)
            else:
                return json.dumps({'status': 1})

        else:
            return json.dumps({'status': 3})
Exemple #6
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def retrieve_prediction():
    '''

    This router function retrieves a specified prediction parameter.

        - integer, codified indicator of save attempt:
            - 0, successful retrieval of specified prediction parameter
            - 1, unsuccessful retrieval of specified prediction parameter
            - 2, improper request submitted
            - 3, invalid 'model_type'
        - string, prediction parameter

    '''

    if request.method == 'POST':
        # programmatic-interface
        if request.get_json():
            results = request.get_json()
            id_result = results['id_result']

        # web-interface
        elif request.form:
            results = request.form
            args = json.loads(results['args'])
            id_result = args['id_result']

        # invalid request
        else:
            return json.dumps({'status': 2})

        # query database and return results
        prediction = Prediction()
        result = prediction.get_result(id_result)
        model_type = prediction.get_model_type(id_result)['result']

        if model_type == 'svm':
            classes = prediction.get_value(id_result, model_type, 'class')
            df = prediction.get_value(id_result, model_type,
                                      'decision_function')
            prob = prediction.get_value(id_result, model_type, 'probability')

            if (result['status'] and classes['status'] and df['status']
                    and prob['status']):
                # return results: queried 'decimal' database values, are not
                #                 json serializable, without using the 'default'
                #                 string serializer.
                #
                return json.dumps(
                    {
                        'status': 0,
                        'result': result['result'],
                        'classes': classes['result'],
                        'decision_function': df['result'],
                        'probability': prob['result']
                    },
                    default=str)
            else:
                return json.dumps({'status': 1})

        elif model_type == 'svr':
            coefficient = prediction.get_value(id_result, model_type, 'r2')

            if coefficient['status']:
                # return results: queried 'decimal' database values, are not
                #                 json serializable, without using the 'default'
                #                 string serializer.
                #
                return json.dumps(
                    {
                        'status': 0,
                        'result': result['result'],
                        'r2': coefficient['result']
                    },
                    default=str)
            else:
                return json.dumps({'status': 1})

        else:
            return json.dumps({'status': 3})