Example #1
0
def main():
    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'E_Prescription.settings')
    try:
        from django.core.management import execute_from_command_line
    except ImportError as exc:
        raise ImportError(
            "Couldn't import Django. Are you sure it's installed and "
            "available on your PYTHONPATH environment variable? Did you "
            "forget to activate a virtual environment?")
    execute_from_command_line(sys.argv)
Example #2
0
def main():
    """Run administrative tasks."""
    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'mqp_project.settings')
    try:
        from django.core.management import execute_from_command_line
    except ImportError as exc:
        raise ImportError(
            "Couldn't import Django. Are you sure it's installed and available on your PYTHONPATH environment variable? Did you forget to activate a virtual environment?"
        ) from exc
    execute_from_command_line(sys.argv)
Example #3
0
    def init_partitioner(self):
        self.prediction_model_algorithm = None
        self.partition_algorithm = None

        if self.PREDICTION_MODEL_ALGORITHM == 'FENNEL' or self.PARTITIONER_ALGORITHM == 'FENNEL':

            import pyximport
            pyximport.install()
            from graph_partitioning import fennel

            if self.PREDICTION_MODEL_ALGORITHM == 'FENNEL':
                self.prediction_model_algorithm = fennel.FennelPartitioner(
                    self.prediction_model_alpha)
                if self.verbose > 0:
                    print(
                        "FENNEL partitioner loaded for generating PREDICTION MODEL."
                    )

            if self.PARTITIONER_ALGORITHM == 'FENNEL':
                self.partition_algorithm = fennel.FennelPartitioner()
                if self.verbose > 0:
                    print(
                        "FENNEL partitioner loaded for making shelter assignments."
                    )

        if self.PREDICTION_MODEL_ALGORITHM == 'SCOTCH':

            sys.path.insert(0, self.SCOTCH_PYLIB_REL_PATH)

            # check if the library is present
            if not os.path.isfile(self.SCOTCH_LIB_PATH):
                raise ImportError(
                    "Could not locate the SCOTCH library file at: {}".format(
                        self.SCOTCH_LIB_PATH))

            from graph_partitioning import scotch_partitioner

            self.prediction_model_algorithm = scotch_partitioner.ScotchPartitioner(
                self.SCOTCH_LIB_PATH)

            if self.verbose > 0:
                print(
                    "SCOTCH partitioner loaded for generating PREDICTION MODEL."
                )

        if self.prediction_model_algorithm == None:
            raise NoPartitionerException(
                "Prediction model partitioner not specified or incorrect. Available partitioners are 'FENNEL' or 'SCOTCH'."
            )
        if self.partition_algorithm == None:
            raise NoPartitionerException(
                "Assignment partitioner not specified or incorrect. Available partitioners is 'FENNEL'."
            )
Example #4
0
#!/usr/bin/env python
import os
import sys
from builtins import ImportError

if __name__ == "__main__":
    os.environ.setdefault("DJANGO_SETTINGS_MODULE", "cvanalysis.settings")
    try:
        from django.core.management import execute_from_command_line
    except ImportError as exc:
        raise ImportError(
            "Couldn't import Django. Are you sure it's installed and "
            "available on your PYTHONPATH environment variable? Did you "
            "forget to activate a virtual environment?") from exc
    execute_from_command_line(sys.argv)
Example #5
0
    def init_partitioner(self):
        self.prediction_model_algorithm = None
        self.partition_algorithm = None

        if self.PREDICTION_MODEL_ALGORITHM == 'FENNEL' or self.PARTITIONER_ALGORITHM == 'FENNEL':

            import pyximport
            pyximport.install()
            from graph_partitioning import fennel

            if self.PREDICTION_MODEL_ALGORITHM == 'FENNEL':
                self.prediction_model_algorithm = fennel.FennelPartitioner(
                    self.prediction_model_alpha,
                    self.FENNEL_FRIEND_OF_A_FRIEND_ENABLED)
                if self.verbose > 0:
                    print(
                        "FENNEL partitioner loaded for generating PREDICTION MODEL."
                    )

            if self.PARTITIONER_ALGORITHM == 'FENNEL':
                self.partition_algorithm = fennel.FennelPartitioner(
                    FRIEND_OF_FRIEND_ENABLED=self.
                    FENNEL_FRIEND_OF_A_FRIEND_ENABLED)
                if self.verbose > 0:
                    print(
                        "FENNEL partitioner loaded for making shelter assignments."
                    )

            if self.FENNEL_NODE_REORDERING_ENABLED:
                # compute the node leverage centrality scores for the whole graph
                self.fennel_centrality_reordered_nodes = utils.leverage_centrality(
                    self.G)

        if self.PREDICTION_MODEL_ALGORITHM == 'SCOTCH':

            #sys.path.insert(0, self.SCOTCH_PYLIB_REL_PATH)

            # check if the library is present
            if not os.path.isfile(self.SCOTCH_LIB_PATH):
                raise ImportError(
                    "Could not locate the SCOTCH library file at: {}".format(
                        self.SCOTCH_LIB_PATH))

            from graph_partitioning import scotch_partitioner

            self.prediction_model_algorithm = scotch_partitioner.ScotchPartitioner(
                self.SCOTCH_LIB_PATH,
                virtualNodesEnabled=self.use_virtual_nodes)
            if self.verbose > 0:
                print(
                    "SCOTCH partitioner loaded for generating PREDICTION MODEL."
                )

            if self.PARTITIONER_ALGORITHM == 'SCOTCH':
                # use the same prediction_model_algorithm for both batch and prediction modes
                self.partition_algorithm = self.prediction_model_algorithm
                if self.verbose > 0:
                    print(
                        "SCOTCH partitioner loaded for making shelter assignments."
                    )

        if self.PREDICTION_MODEL_ALGORITHM == 'PATOH':
            #sys.path.insert(0, self.SCOTCH_PYLIB_REL_PATH)

            # check if the library is present
            if not os.path.isfile(self.PATOH_LIB_PATH):
                raise ImportError(
                    "Could not locate the PaToH library file at: {}".format(
                        self.PATOH_LIB_PATH))

            from graph_partitioning import patoh_partitioner

            isQuiet = False
            if (self.verbose == 0):
                isQuiet = True

            self.prediction_model_algorithm = patoh_partitioner.PatohPartitioner(
                self.PATOH_LIB_PATH,
                quiet=isQuiet,
                partitioningIterations=self.PATOH_ITERATIONS,
                hyperedgeExpansionMode=self.PATOH_HYPEREDGE_EXPANSION_MODE)
            if self.verbose > 0:
                print(
                    "PaToH partitioner loaded for generating PREDICTION MODEL."
                )

            if self.PARTITIONER_ALGORITHM == 'PATOH':
                # use the same prediction_model_algorithm for both batch and prediction modes
                self.partition_algorithm = self.prediction_model_algorithm
                if self.verbose > 0:
                    print(
                        "PaToH partitioner loaded for making shelter assignments."
                    )

            # edge expansion happens via hyperedge expansion in PaToH's patoh_data.py script
            if (self.edge_expansion_enabled):
                self.edge_expansion_enabled = False
                self.prediction_model_algorithm.hyperedgeExpansionMode = self.PATOH_HYPEREDGE_EXPANSION_MODE
            else:
                self.prediction_model_algorithm.hyperedgeExpansionMode = 'no_expansion'

        if self.prediction_model_algorithm == None:
            raise NoPartitionerException(
                "Prediction model partitioner not specified or incorrect. Available partitioners are 'FENNEL' or 'SCOTCH'."
            )
        if self.partition_algorithm == None:
            raise NoPartitionerException(
                "Assignment partitioner not specified or incorrect. Available partitioners is 'FENNEL'."
            )