fixing naming convention in to_isis for proper communication with plio

        for _, n in self.nodes(data='data'):

            n.generate_vrt(**kwargs)

    def to_isis(self, path, flistpath=None,sql = """

    def to_isis(self, path, flistpath=None,points_sql = """

SELECT points.id,

        measures.serial,

        points.pointtype,

        points.apriori,

        points.adjusted,

        points.active

FROM measures

INNER JOIN points ON measures.pointid = points.id

WHERE

    points.active = True AND

    measures.active=TRUE AND

    measures.jigreject=FALSE AND

    measures.imageid NOT IN

        (SELECT measures.imageid

        FROM measures

        INNER JOIN points ON measures.pointid = points.id

        WHERE measures.active = true and measures.jigreject = false AND points.active = True

        GROUP BY measures.imageid

        HAVING COUNT(DISTINCT measures.pointid)  < 3);

""",

measures_sql="""

SELECT measures.serial,

        measures.sample,

        measures.line,

        measures.measuretype,

        measures.imageid

        measures.imageid,

        measures.active,

        measures.jigreject,

        measures.aprioriline,

        measures.apriorisample

FROM measures

INNER JOIN points ON measures.pointid = points.id

WHERE

              The sql query to execute in the database.

        """

        df = pd.read_sql(sql, engine)

        df.rename(columns={'imageid':'image_index','id':'point_id', 'pointtype' : 'type',

            'sample':'x', 'line':'y', 'serial': 'serialnumber', 'measuretype':'measure_type'}, inplace=True)

        #since measures and points tables contain some of the same attributes

        #read them in seperately and rename

        points_df = pd.read_sql(points_sql, engine)

        points_df.rename(columns={'pointtype' : 'pointType', 'jigreject' : 'pointJigsawRejected'}, inplace=True)

        points_df['pointIgnore'] = ~points_df['active']

        measures_df = pd.read_sql(measures_sql, engine)

        measures_df.rename(columns={'serial' : 'serialnumber', 'measuretype' : 'measureType',

                                    'jigreject' : 'measureJigsawRejected'}, inplace=True)

        measures_df['measureIgnore'] = ~measures_df['active']

        #combine for passing to plio

        df = pd.concat([points_df, measures_df], axis=1, sort=False)

        #create columns in the dataframe; zeros ensure plio (/protobuf) will

        #ignore unless populated with alternate values

        #recalculate the control point lat/lon from control measures which where

        #"massaged" by the phase and template matcher.

        for i, row in df.iterrows():

            if row['type'] == 3 or row['type'] == 4:

            if row['pointType'] == 3 or row['pointType'] == 4:

                apriori_geom = swkb.loads(row['apriori'], hex=True)

                row['aprioriX'] = apriori_geom.x

                row['aprioriY'] = apriori_geom.y

            flistpath = os.path.splitext(path)[0] + '.lis'

        target = config['spatial'].get('target', None)

        ids = df['image_index'].unique()

        ids = df['imageid'].unique()

        fpaths = [self.nodes[i]['data']['image_path'] for i in ids]

        for f in self.files:

            if f not in fpaths: