scout/server/blueprints/dashboard/controllers.py
def get_analysis_types(adapter, total_cases, institute_id=None, slice_query=None):
    """ Return information about analysis types.
        Group cases based on analysis type for the individuals.
    Args:
        adapter(adapter.MongoAdapter)
        total_cases(int): Total number of cases
        institute_id(str)
        slice_query(str): Query to filter cases to obtain statistics for.
    Returns:
        analysis_types array of hashes with name: analysis_type(str), count: count(int)

    """
    # Group cases based on analysis type of the individuals
    query = {}

    subquery = {}
    if institute_id and slice_query:
        subquery = adapter.cases(owner=institute_id, name_query=slice_query,
                              yield_query=True)
    elif institute_id:
        subquery = adapter.cases(owner=institute_id, yield_query=True)
    elif slice_query:
        subquery = adapter.cases(name_query=slice_query, yield_query=True)

    query = {'$match': subquery}

    pipeline = []
    if query:
        pipeline.append(query)

    pipeline.append({'$unwind': '$individuals'})
    pipeline.append({'$group': {'_id': '$individuals.analysis_type', 'count': {'$sum': 1}}})
    analysis_query = adapter.case_collection.aggregate(pipeline)
    analysis_types = [{'name': group['_id'], 'count': group['count']} for group in analysis_query]

    return analysis_types
def get_analysis_types(adapter, total_cases, institute_id=None, slice_query=None):
    """ Return information about analysis types.
        Group cases based on analysis type for the individuals.
    Args:
        adapter(adapter.MongoAdapter)
        total_cases(int): Total number of cases
        institute_id(str)
        slice_query(str): Query to filter cases to obtain statistics for.
    Returns:
        analysis_types array of hashes with name: analysis_type(str), count: count(int)

    """
    # Group cases based on analysis type of the individuals
    query = {}

    subquery = {}
    if institute_id and slice_query:
        subquery = adapter.cases(owner=institute_id, name_query=slice_query,
                              yield_query=True)
    elif institute_id:
        subquery = adapter.cases(owner=institute_id, yield_query=True)
    elif slice_query:
        subquery = adapter.cases(name_query=slice_query, yield_query=True)

    query = {'$match': subquery}

    pipeline = []
    if query:
        pipeline.append(query)

    pipeline.append({'$unwind': '$individuals'})
    pipeline.append({'$group': {'_id': '$individuals.analysis_type', 'count': {'$sum': 1}}})
    analysis_query = adapter.case_collection.aggregate(pipeline)
    analysis_types = [{'name': group['_id'], 'count': group['count']} for group in analysis_query]

    return analysis_types
Return information about analysis types.
        Group cases based on analysis type for the individuals.
    Args:
        adapter(adapter.MongoAdapter)
        total_cases(int): Total number of cases
        institute_id(str)
        slice_query(str): Query to filter cases to obtain statistics for.
    Returns:
        analysis_types array of hashes with name: analysis_type(str), count: count(int)