Beispiel #1
0
    def __init__(self, cluster, api=None):

        if not (isinstance(cluster, dict) and 'resource' in cluster
                and cluster['resource'] is not None):
            if api is None:
                api = BigML(storage=STORAGE)
            self.resource_id = get_cluster_id(cluster)
            if self.resource_id is None:
                raise Exception(
                    api.error_message(cluster,
                                      resource_type='cluster',
                                      method='get'))
            query_string = ONLY_MODEL
            cluster = retrieve_resource(api,
                                        self.resource_id,
                                        query_string=query_string)
        if 'object' in cluster and isinstance(cluster['object'], dict):
            cluster = cluster['object']

        if 'clusters' in cluster and isinstance(cluster['clusters'], dict):
            status = get_status(cluster)
            if 'code' in status and status['code'] == FINISHED:
                clusters = cluster['clusters']['clusters']
                self.centroids = [Centroid(centroid) for centroid in clusters]
                self.scales = {}
                self.scales.update(cluster['scales'])
                self.term_forms = {}
                self.tag_clouds = {}
                self.term_analysis = {}
                fields = cluster['clusters']['fields']
                for field_id, field in fields.items():
                    if field['optype'] == 'text':

                        self.term_forms[field_id] = {}
                        self.term_forms[field_id].update(
                            field['summary']['term_forms'])
                        self.tag_clouds[field_id] = {}
                        self.tag_clouds[field_id].update(
                            field['summary']['tag_cloud'])
                        self.term_analysis[field_id] = {}
                        self.term_analysis[field_id].update(
                            field['term_analysis'])
                ModelFields.__init__(self, fields)
                if not all(
                    [field_id in self.fields for field_id in self.scales]):
                    raise Exception("Some fields are missing"
                                    " to generate a local cluster."
                                    " Please, provide a cluster with"
                                    " the complete list of fields.")
            else:
                raise Exception("The cluster isn't finished yet")
        else:
            raise Exception("Cannot create the Cluster instance. Could not"
                            " find the 'clusters' key in the resource:\n\n%s" %
                            cluster)
Beispiel #2
0
    def __init__(self, cluster, api=None):

        if not (isinstance(cluster, dict) and 'resource' in cluster and
                cluster['resource'] is not None):
            if api is None:
                api = BigML(storage=STORAGE)
            self.resource_id = get_cluster_id(cluster)
            if self.resource_id is None:
                raise Exception(api.error_message(cluster,
                                                  resource_type='cluster',
                                                  method='get'))
            query_string = ONLY_MODEL
            cluster = retrieve_resource(api, self.resource_id,
                                        query_string=query_string)
        if 'object' in cluster and isinstance(cluster['object'], dict):
            cluster = cluster['object']

        if 'clusters' in cluster and isinstance(cluster['clusters'], dict):
            status = get_status(cluster)
            if 'code' in status and status['code'] == FINISHED:
                clusters = cluster['clusters']['clusters']
                self.centroids = [Centroid(centroid) for centroid in clusters]
                self.scales = {}
                self.scales.update(cluster['scales'])
                self.term_forms = {}
                self.tag_clouds = {}
                self.term_analysis = {}
                fields = cluster['clusters']['fields']
                for field_id, field in fields.items():
                    if field['optype'] == 'text':

                        self.term_forms[field_id] = {}
                        self.term_forms[field_id].update(field[
                            'summary']['term_forms'])
                        self.tag_clouds[field_id] = {}
                        self.tag_clouds[field_id].update(field[
                            'summary']['tag_cloud'])
                        self.term_analysis[field_id] = {}
                        self.term_analysis[field_id].update(
                            field['term_analysis'])
                ModelFields.__init__(self, fields)
                if not all([field_id in self.fields for
                            field_id in self.scales]):
                    raise Exception("Some fields are missing"
                                    " to generate a local cluster."
                                    " Please, provide a cluster with"
                                    " the complete list of fields.")
            else:
                raise Exception("The cluster isn't finished yet")
        else:
            raise Exception("Cannot create the Cluster instance. Could not"
                            " find the 'clusters' key in the resource:\n\n%s" %
                            cluster)
Beispiel #3
0
    def __init__(self, cluster, api=None, cache_get=None):

        self.api = get_api_connection(api)
        self.centroids = None
        if use_cache(cache_get):
            # using a cache to store the cluster attributes
            self.__dict__ = load(get_cluster_id(cluster), cache_get)

            for index, centroid in enumerate(self.centroids):
                self.centroids[index] = Centroid(centroid)
            self.cluster_global = Centroid(self.cluster_global)
            return

        self.resource_id = None
        self.cluster_global = None
        self.total_ss = None
        self.within_ss = None
        self.between_ss = None
        self.ratio_ss = None
        self.critical_value = None
        self.input_fields = []
        self.summary_fields = []
        self.default_numeric_value = None
        self.k = None
        self.summary_fields = []
        self.scales = {}
        self.term_forms = {}
        self.tag_clouds = {}
        self.term_analysis = {}
        self.item_analysis = {}
        self.items = {}
        self.datasets = {}

        self.resource_id, cluster = get_resource_dict( \
            cluster, "cluster", api=self.api)

        if 'object' in cluster and isinstance(cluster['object'], dict):
            cluster = cluster['object']

        if 'clusters' in cluster and isinstance(cluster['clusters'], dict):
            status = get_status(cluster)
            if 'code' in status and status['code'] == FINISHED:
                self.default_numeric_value = cluster.get( \
                    "default_numeric_value")
                self.summary_fields = cluster.get("summary_fields", [])
                self.input_fields = cluster.get("input_fields", [])
                self.datasets = cluster.get("cluster_datasets", {})
                the_clusters = cluster['clusters']
                cluster_global = the_clusters.get('global')
                clusters = the_clusters['clusters']
                self.centroids = [Centroid(centroid) for centroid in clusters]
                self.cluster_global = cluster_global
                if cluster_global:
                    self.cluster_global = Centroid(cluster_global)
                    # "global" has no "name" and "count" then we set them
                    self.cluster_global.name = GLOBAL_CLUSTER_LABEL
                    self.cluster_global.count = \
                        self.cluster_global.distance['population']
                self.total_ss = the_clusters.get('total_ss')
                self.within_ss = the_clusters.get('within_ss')
                if not self.within_ss:
                    self.within_ss = sum(centroid.distance['sum_squares'] for
                                         centroid in self.centroids)
                self.between_ss = the_clusters.get('between_ss')
                self.ratio_ss = the_clusters.get('ratio_ss')
                self.critical_value = cluster.get('critical_value', None)
                self.k = cluster.get('k')
                self.scales.update(cluster['scales'])
                self.term_forms = {}
                self.tag_clouds = {}
                self.term_analysis = {}
                fields = cluster['clusters']['fields']
                summary_fields = cluster['summary_fields']
                for field_id in summary_fields:
                    try:
                        del fields[field_id]
                    except KeyError:
                        # clusters retrieved from API will only contain
                        # model fields
                        pass
                for field_id, field in list(fields.items()):
                    if field['optype'] == 'text':
                        self.term_forms[field_id] = {}
                        self.term_forms[field_id].update(field[
                            'summary']['term_forms'])
                        self.tag_clouds[field_id] = {}
                        self.tag_clouds[field_id].update(field[
                            'summary']['tag_cloud'])
                        self.term_analysis[field_id] = {}
                        self.term_analysis[field_id].update(
                            field['term_analysis'])
                    if field['optype'] == 'items':
                        self.items[field_id] = {}
                        self.items[field_id].update(
                            dict(field['summary']['items']))
                        self.item_analysis[field_id] = {}
                        self.item_analysis[field_id].update(
                            field['item_analysis'])

                missing_tokens = cluster['clusters'].get('missing_tokens')
                ModelFields.__init__(self, fields,
                                     missing_tokens=missing_tokens)
                if not all([field_id in self.fields for
                            field_id in self.scales]):
                    raise Exception("Some fields are missing"
                                    " to generate a local cluster."
                                    " Please, provide a cluster with"
                                    " the complete list of fields.")
            else:
                raise Exception("The cluster isn't finished yet")
        else:
            raise Exception("Cannot create the Cluster instance. Could not"
                            " find the 'clusters' key in the resource:\n\n%s" %
                            cluster)
Beispiel #4
0
    def __init__(self, cluster, api=None):

        self.resource_id = None
        self.centroids = None
        self.cluster_global = None
        self.total_ss = None
        self.within_ss = None
        self.between_ss = None
        self.ratio_ss = None
        self.critical_value = None
        self.k = None
        self.scales = {}
        self.term_forms = {}
        self.tag_clouds = {}
        self.term_analysis = {}
        self.item_analysis = {}
        self.items = {}
        if not (isinstance(cluster, dict) and 'resource' in cluster and
                cluster['resource'] is not None):
            if api is None:
                api = BigML(storage=STORAGE)
            self.resource_id = get_cluster_id(cluster)
            if self.resource_id is None:
                raise Exception(api.error_message(cluster,
                                                  resource_type='cluster',
                                                  method='get'))
            query_string = ONLY_MODEL
            cluster = retrieve_resource(api, self.resource_id,
                                        query_string=query_string)
        else:
            self.resource_id = get_cluster_id(cluster)
        if 'object' in cluster and isinstance(cluster['object'], dict):
            cluster = cluster['object']

        if 'clusters' in cluster and isinstance(cluster['clusters'], dict):
            status = get_status(cluster)
            if 'code' in status and status['code'] == FINISHED:
                the_clusters = cluster['clusters']
                cluster_global = the_clusters.get('global')
                clusters = the_clusters['clusters']
                self.centroids = [Centroid(centroid) for centroid in clusters]
                self.cluster_global = cluster_global
                if cluster_global:
                    self.cluster_global = Centroid(cluster_global)
                    # "global" has no "name" and "count" then we set them
                    self.cluster_global.name = GLOBAL_CLUSTER_LABEL
                    self.cluster_global.count = \
                        self.cluster_global.distance['population']
                self.total_ss = the_clusters.get('total_ss')
                self.within_ss = the_clusters.get('within_ss')
                if not self.within_ss:
                    self.within_ss = sum(centroid.distance['sum_squares'] for
                                         centroid in self.centroids)
                self.between_ss = the_clusters.get('between_ss')
                self.ratio_ss = the_clusters.get('ratio_ss')
                self.critical_value = cluster.get('critical_value', None)
                self.k = cluster.get('k')
                self.scales.update(cluster['scales'])
                self.term_forms = {}
                self.tag_clouds = {}
                self.term_analysis = {}
                fields = cluster['clusters']['fields']
                summary_fields = cluster['summary_fields']
                for field_id in summary_fields:
                    del fields[field_id]
                for field_id, field in fields.items():
                    if field['optype'] == 'text':
                        self.term_forms[field_id] = {}
                        self.term_forms[field_id].update(field[
                            'summary']['term_forms'])
                        self.tag_clouds[field_id] = {}
                        self.tag_clouds[field_id].update(field[
                            'summary']['tag_cloud'])
                        self.term_analysis[field_id] = {}
                        self.term_analysis[field_id].update(
                            field['term_analysis'])
                    if field['optype'] == 'items':
                        self.items[field_id] = {}
                        self.items[field_id].update(
                            dict(field['summary']['items']))
                        self.item_analysis[field_id] = {}
                        self.item_analysis[field_id].update(
                            field['item_analysis'])

                ModelFields.__init__(self, fields)
                if not all([field_id in self.fields for
                            field_id in self.scales]):
                    raise Exception("Some fields are missing"
                                    " to generate a local cluster."
                                    " Please, provide a cluster with"
                                    " the complete list of fields.")
            else:
                raise Exception("The cluster isn't finished yet")
        else:
            raise Exception("Cannot create the Cluster instance. Could not"
                            " find the 'clusters' key in the resource:\n\n%s" %
                            cluster)
Beispiel #5
0
    def __init__(self, cluster, api=None):

        self.resource_id = None
        self.centroids = None
        self.cluster_global = None
        self.total_ss = None
        self.within_ss = None
        self.between_ss = None
        self.ratio_ss = None
        self.critical_value = None
        self.default_numeric_value = None
        self.k = None
        self.summary_fields = []
        self.scales = {}
        self.term_forms = {}
        self.tag_clouds = {}
        self.term_analysis = {}
        self.item_analysis = {}
        self.items = {}
        self.datasets = {}
        self.api = api

        # checks whether the information needed for local predictions is in
        # the first argument
        if isinstance(cluster, dict) and \
                not check_model_fields(cluster):
            # if the fields used by the cluster are not
            # available, use only ID to retrieve it again
            cluster = get_cluster_id(cluster)
            self.resource_id = cluster

        if not (isinstance(cluster, dict) and 'resource' in cluster
                and cluster['resource'] is not None):
            if api is None:
                api = BigML(storage=STORAGE)
                self.api = api
            self.resource_id = get_cluster_id(cluster)
            if self.resource_id is None:
                raise Exception(
                    api.error_message(cluster,
                                      resource_type='cluster',
                                      method='get'))
            query_string = ONLY_MODEL
            cluster = retrieve_resource(api,
                                        self.resource_id,
                                        query_string=query_string)
        else:
            self.resource_id = get_cluster_id(cluster)
        if 'object' in cluster and isinstance(cluster['object'], dict):
            cluster = cluster['object']

        if 'clusters' in cluster and isinstance(cluster['clusters'], dict):
            status = get_status(cluster)
            if 'code' in status and status['code'] == FINISHED:
                self.default_numeric_value = cluster.get( \
                    "default_numeric_value")
                self.summary_fields = cluster.get("summary_fields", [])
                self.datasets = cluster.get("cluster_datasets", {})
                the_clusters = cluster['clusters']
                cluster_global = the_clusters.get('global')
                clusters = the_clusters['clusters']
                self.centroids = [Centroid(centroid) for centroid in clusters]
                self.cluster_global = cluster_global
                if cluster_global:
                    self.cluster_global = Centroid(cluster_global)
                    # "global" has no "name" and "count" then we set them
                    self.cluster_global.name = GLOBAL_CLUSTER_LABEL
                    self.cluster_global.count = \
                        self.cluster_global.distance['population']
                self.total_ss = the_clusters.get('total_ss')
                self.within_ss = the_clusters.get('within_ss')
                if not self.within_ss:
                    self.within_ss = sum(centroid.distance['sum_squares']
                                         for centroid in self.centroids)
                self.between_ss = the_clusters.get('between_ss')
                self.ratio_ss = the_clusters.get('ratio_ss')
                self.critical_value = cluster.get('critical_value', None)
                self.k = cluster.get('k')
                self.scales.update(cluster['scales'])
                self.term_forms = {}
                self.tag_clouds = {}
                self.term_analysis = {}
                fields = cluster['clusters']['fields']
                summary_fields = cluster['summary_fields']
                for field_id in summary_fields:
                    try:
                        del fields[field_id]
                    except KeyError:
                        # clusters retrieved from API will only contain
                        # model fields
                        pass
                for field_id, field in fields.items():
                    if field['optype'] == 'text':
                        self.term_forms[field_id] = {}
                        self.term_forms[field_id].update(
                            field['summary']['term_forms'])
                        self.tag_clouds[field_id] = {}
                        self.tag_clouds[field_id].update(
                            field['summary']['tag_cloud'])
                        self.term_analysis[field_id] = {}
                        self.term_analysis[field_id].update(
                            field['term_analysis'])
                    if field['optype'] == 'items':
                        self.items[field_id] = {}
                        self.items[field_id].update(
                            dict(field['summary']['items']))
                        self.item_analysis[field_id] = {}
                        self.item_analysis[field_id].update(
                            field['item_analysis'])

                ModelFields.__init__(self, fields)
                if not all(
                    [field_id in self.fields for field_id in self.scales]):
                    raise Exception("Some fields are missing"
                                    " to generate a local cluster."
                                    " Please, provide a cluster with"
                                    " the complete list of fields.")
            else:
                raise Exception("The cluster isn't finished yet")
        else:
            raise Exception("Cannot create the Cluster instance. Could not"
                            " find the 'clusters' key in the resource:\n\n%s" %
                            cluster)
Beispiel #6
0
    def __init__(self, cluster, api=None):

        self.resource_id = None
        self.centroids = None
        self.cluster_global = None
        self.total_ss = None
        self.within_ss = None
        self.between_ss = None
        self.ratio_ss = None
        self.critical_value = None
        self.k = None
        self.scales = {}
        self.term_forms = {}
        self.tag_clouds = {}
        self.term_analysis = {}
        self.item_analysis = {}
        self.items = {}
        if not (isinstance(cluster, dict) and 'resource' in cluster and
                cluster['resource'] is not None):
            if api is None:
                api = BigML(storage=STORAGE)
            self.resource_id = get_cluster_id(cluster)
            if self.resource_id is None:
                raise Exception(api.error_message(cluster,
                                                  resource_type='cluster',
                                                  method='get'))
            query_string = ONLY_MODEL
            cluster = retrieve_resource(api, self.resource_id,
                                        query_string=query_string)
        else:
            self.resource_id = get_cluster_id(cluster)
        if 'object' in cluster and isinstance(cluster['object'], dict):
            cluster = cluster['object']

        if 'clusters' in cluster and isinstance(cluster['clusters'], dict):
            status = get_status(cluster)
            if 'code' in status and status['code'] == FINISHED:
                the_clusters = cluster['clusters']
                cluster_global = the_clusters.get('global')
                clusters = the_clusters['clusters']
                self.centroids = [Centroid(centroid) for centroid in clusters]
                self.cluster_global = cluster_global
                if cluster_global:
                    self.cluster_global = Centroid(cluster_global)
                    # "global" has no "name" and "count" then we set them
                    self.cluster_global.name = GLOBAL_CLUSTER_LABEL
                    self.cluster_global.count = \
                        self.cluster_global.distance['population']
                self.total_ss = the_clusters.get('total_ss')
                self.within_ss = the_clusters.get('within_ss')
                if not self.within_ss:
                    self.within_ss = sum(centroid.distance['sum_squares'] for
                                         centroid in self.centroids)
                self.between_ss = the_clusters.get('between_ss')
                self.ratio_ss = the_clusters.get('ratio_ss')
                self.critical_value = cluster.get('critical_value', None)
                self.k = cluster.get('k')
                self.scales.update(cluster['scales'])
                self.term_forms = {}
                self.tag_clouds = {}
                self.term_analysis = {}
                fields = cluster['clusters']['fields']
                summary_fields = cluster['summary_fields']
                for field_id in summary_fields:
                    del fields[field_id]
                for field_id, field in fields.items():
                    if field['optype'] == 'text':
                        self.term_forms[field_id] = {}
                        self.term_forms[field_id].update(field[
                            'summary']['term_forms'])
                        self.tag_clouds[field_id] = {}
                        self.tag_clouds[field_id].update(field[
                            'summary']['tag_cloud'])
                        self.term_analysis[field_id] = {}
                        self.term_analysis[field_id].update(
                            field['term_analysis'])
                    if field['optype'] == 'items':
                        self.items[field_id] = {}
                        self.items[field_id].update(
                            dict(field['summary']['items']))
                        self.item_analysis[field_id] = {}
                        self.item_analysis[field_id].update(
                            field['item_analysis'])

                ModelFields.__init__(self, fields)
                if not all([field_id in self.fields for
                            field_id in self.scales]):
                    raise Exception("Some fields are missing"
                                    " to generate a local cluster."
                                    " Please, provide a cluster with"
                                    " the complete list of fields.")
            else:
                raise Exception("The cluster isn't finished yet")
        else:
            raise Exception("Cannot create the Cluster instance. Could not"
                            " find the 'clusters' key in the resource:\n\n%s" %
                            cluster)