wallaroo.wallaroo_ml_ops_api_client.models.assays_get_results_response_200_item_summarizer_type_0
1from typing import Any, Dict, List, Type, TypeVar, Union, cast 2 3import attr 4 5from ..models.assays_get_results_response_200_item_summarizer_type_0_aggregation import \ 6 AssaysGetResultsResponse200ItemSummarizerType0Aggregation 7from ..models.assays_get_results_response_200_item_summarizer_type_0_bin_mode import \ 8 AssaysGetResultsResponse200ItemSummarizerType0BinMode 9from ..models.assays_get_results_response_200_item_summarizer_type_0_metric import \ 10 AssaysGetResultsResponse200ItemSummarizerType0Metric 11from ..models.assays_get_results_response_200_item_summarizer_type_0_type import \ 12 AssaysGetResultsResponse200ItemSummarizerType0Type 13from ..types import UNSET, Unset 14 15T = TypeVar("T", bound="AssaysGetResultsResponse200ItemSummarizerType0") 16 17@attr.s(auto_attribs=True) 18class AssaysGetResultsResponse200ItemSummarizerType0: 19 """ Defines the summarizer/test we want to conduct 20 21 Attributes: 22 bin_mode (AssaysGetResultsResponse200ItemSummarizerType0BinMode): 23 aggregation (AssaysGetResultsResponse200ItemSummarizerType0Aggregation): 24 metric (AssaysGetResultsResponse200ItemSummarizerType0Metric): How we calculate the score between two 25 histograms/vecs. Add pct_diff and sum_pct_diff? 26 num_bins (int): 27 type (AssaysGetResultsResponse200ItemSummarizerType0Type): 28 bin_weights (Union[Unset, None, List[float]]): 29 provided_edges (Union[Unset, None, List[float]]): 30 """ 31 32 bin_mode: AssaysGetResultsResponse200ItemSummarizerType0BinMode 33 aggregation: AssaysGetResultsResponse200ItemSummarizerType0Aggregation 34 metric: AssaysGetResultsResponse200ItemSummarizerType0Metric 35 num_bins: int 36 type: AssaysGetResultsResponse200ItemSummarizerType0Type 37 bin_weights: Union[Unset, None, List[float]] = UNSET 38 provided_edges: Union[Unset, None, List[float]] = UNSET 39 additional_properties: Dict[str, Any] = attr.ib(init=False, factory=dict) 40 41 42 def to_dict(self) -> Dict[str, Any]: 43 bin_mode = self.bin_mode.value 44 45 aggregation = self.aggregation.value 46 47 metric = self.metric.value 48 49 num_bins = self.num_bins 50 type = self.type.value 51 52 bin_weights: Union[Unset, None, List[float]] = UNSET 53 if not isinstance(self.bin_weights, Unset): 54 if self.bin_weights is None: 55 bin_weights = None 56 else: 57 bin_weights = self.bin_weights 58 59 60 61 62 provided_edges: Union[Unset, None, List[float]] = UNSET 63 if not isinstance(self.provided_edges, Unset): 64 if self.provided_edges is None: 65 provided_edges = None 66 else: 67 provided_edges = self.provided_edges 68 69 70 71 72 73 field_dict: Dict[str, Any] = {} 74 field_dict.update(self.additional_properties) 75 field_dict.update({ 76 "bin_mode": bin_mode, 77 "aggregation": aggregation, 78 "metric": metric, 79 "num_bins": num_bins, 80 "type": type, 81 }) 82 if bin_weights is not UNSET: 83 field_dict["bin_weights"] = bin_weights 84 if provided_edges is not UNSET: 85 field_dict["provided_edges"] = provided_edges 86 87 return field_dict 88 89 90 91 @classmethod 92 def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T: 93 d = src_dict.copy() 94 bin_mode = AssaysGetResultsResponse200ItemSummarizerType0BinMode(d.pop("bin_mode")) 95 96 97 98 99 aggregation = AssaysGetResultsResponse200ItemSummarizerType0Aggregation(d.pop("aggregation")) 100 101 102 103 104 metric = AssaysGetResultsResponse200ItemSummarizerType0Metric(d.pop("metric")) 105 106 107 108 109 num_bins = d.pop("num_bins") 110 111 type = AssaysGetResultsResponse200ItemSummarizerType0Type(d.pop("type")) 112 113 114 115 116 bin_weights = cast(List[float], d.pop("bin_weights", UNSET)) 117 118 119 provided_edges = cast(List[float], d.pop("provided_edges", UNSET)) 120 121 122 assays_get_results_response_200_item_summarizer_type_0 = cls( 123 bin_mode=bin_mode, 124 aggregation=aggregation, 125 metric=metric, 126 num_bins=num_bins, 127 type=type, 128 bin_weights=bin_weights, 129 provided_edges=provided_edges, 130 ) 131 132 assays_get_results_response_200_item_summarizer_type_0.additional_properties = d 133 return assays_get_results_response_200_item_summarizer_type_0 134 135 @property 136 def additional_keys(self) -> List[str]: 137 return list(self.additional_properties.keys()) 138 139 def __getitem__(self, key: str) -> Any: 140 return self.additional_properties[key] 141 142 def __setitem__(self, key: str, value: Any) -> None: 143 self.additional_properties[key] = value 144 145 def __delitem__(self, key: str) -> None: 146 del self.additional_properties[key] 147 148 def __contains__(self, key: str) -> bool: 149 return key in self.additional_properties
@attr.s(auto_attribs=True)
class
AssaysGetResultsResponse200ItemSummarizerType0:
18@attr.s(auto_attribs=True) 19class AssaysGetResultsResponse200ItemSummarizerType0: 20 """ Defines the summarizer/test we want to conduct 21 22 Attributes: 23 bin_mode (AssaysGetResultsResponse200ItemSummarizerType0BinMode): 24 aggregation (AssaysGetResultsResponse200ItemSummarizerType0Aggregation): 25 metric (AssaysGetResultsResponse200ItemSummarizerType0Metric): How we calculate the score between two 26 histograms/vecs. Add pct_diff and sum_pct_diff? 27 num_bins (int): 28 type (AssaysGetResultsResponse200ItemSummarizerType0Type): 29 bin_weights (Union[Unset, None, List[float]]): 30 provided_edges (Union[Unset, None, List[float]]): 31 """ 32 33 bin_mode: AssaysGetResultsResponse200ItemSummarizerType0BinMode 34 aggregation: AssaysGetResultsResponse200ItemSummarizerType0Aggregation 35 metric: AssaysGetResultsResponse200ItemSummarizerType0Metric 36 num_bins: int 37 type: AssaysGetResultsResponse200ItemSummarizerType0Type 38 bin_weights: Union[Unset, None, List[float]] = UNSET 39 provided_edges: Union[Unset, None, List[float]] = UNSET 40 additional_properties: Dict[str, Any] = attr.ib(init=False, factory=dict) 41 42 43 def to_dict(self) -> Dict[str, Any]: 44 bin_mode = self.bin_mode.value 45 46 aggregation = self.aggregation.value 47 48 metric = self.metric.value 49 50 num_bins = self.num_bins 51 type = self.type.value 52 53 bin_weights: Union[Unset, None, List[float]] = UNSET 54 if not isinstance(self.bin_weights, Unset): 55 if self.bin_weights is None: 56 bin_weights = None 57 else: 58 bin_weights = self.bin_weights 59 60 61 62 63 provided_edges: Union[Unset, None, List[float]] = UNSET 64 if not isinstance(self.provided_edges, Unset): 65 if self.provided_edges is None: 66 provided_edges = None 67 else: 68 provided_edges = self.provided_edges 69 70 71 72 73 74 field_dict: Dict[str, Any] = {} 75 field_dict.update(self.additional_properties) 76 field_dict.update({ 77 "bin_mode": bin_mode, 78 "aggregation": aggregation, 79 "metric": metric, 80 "num_bins": num_bins, 81 "type": type, 82 }) 83 if bin_weights is not UNSET: 84 field_dict["bin_weights"] = bin_weights 85 if provided_edges is not UNSET: 86 field_dict["provided_edges"] = provided_edges 87 88 return field_dict 89 90 91 92 @classmethod 93 def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T: 94 d = src_dict.copy() 95 bin_mode = AssaysGetResultsResponse200ItemSummarizerType0BinMode(d.pop("bin_mode")) 96 97 98 99 100 aggregation = AssaysGetResultsResponse200ItemSummarizerType0Aggregation(d.pop("aggregation")) 101 102 103 104 105 metric = AssaysGetResultsResponse200ItemSummarizerType0Metric(d.pop("metric")) 106 107 108 109 110 num_bins = d.pop("num_bins") 111 112 type = AssaysGetResultsResponse200ItemSummarizerType0Type(d.pop("type")) 113 114 115 116 117 bin_weights = cast(List[float], d.pop("bin_weights", UNSET)) 118 119 120 provided_edges = cast(List[float], d.pop("provided_edges", UNSET)) 121 122 123 assays_get_results_response_200_item_summarizer_type_0 = cls( 124 bin_mode=bin_mode, 125 aggregation=aggregation, 126 metric=metric, 127 num_bins=num_bins, 128 type=type, 129 bin_weights=bin_weights, 130 provided_edges=provided_edges, 131 ) 132 133 assays_get_results_response_200_item_summarizer_type_0.additional_properties = d 134 return assays_get_results_response_200_item_summarizer_type_0 135 136 @property 137 def additional_keys(self) -> List[str]: 138 return list(self.additional_properties.keys()) 139 140 def __getitem__(self, key: str) -> Any: 141 return self.additional_properties[key] 142 143 def __setitem__(self, key: str, value: Any) -> None: 144 self.additional_properties[key] = value 145 146 def __delitem__(self, key: str) -> None: 147 del self.additional_properties[key] 148 149 def __contains__(self, key: str) -> bool: 150 return key in self.additional_properties
Defines the summarizer/test we want to conduct
Attributes: bin_mode (AssaysGetResultsResponse200ItemSummarizerType0BinMode): aggregation (AssaysGetResultsResponse200ItemSummarizerType0Aggregation): metric (AssaysGetResultsResponse200ItemSummarizerType0Metric): How we calculate the score between two histograms/vecs. Add pct_diff and sum_pct_diff? num_bins (int): type (AssaysGetResultsResponse200ItemSummarizerType0Type): bin_weights (Union[Unset, None, List[float]]): provided_edges (Union[Unset, None, List[float]]):
AssaysGetResultsResponse200ItemSummarizerType0( bin_mode: wallaroo.wallaroo_ml_ops_api_client.models.assays_get_results_response_200_item_summarizer_type_0_bin_mode.AssaysGetResultsResponse200ItemSummarizerType0BinMode, aggregation: wallaroo.wallaroo_ml_ops_api_client.models.assays_get_results_response_200_item_summarizer_type_0_aggregation.AssaysGetResultsResponse200ItemSummarizerType0Aggregation, metric: wallaroo.wallaroo_ml_ops_api_client.models.assays_get_results_response_200_item_summarizer_type_0_metric.AssaysGetResultsResponse200ItemSummarizerType0Metric, num_bins: int, type: wallaroo.wallaroo_ml_ops_api_client.models.assays_get_results_response_200_item_summarizer_type_0_type.AssaysGetResultsResponse200ItemSummarizerType0Type, bin_weights: Union[wallaroo.wallaroo_ml_ops_api_client.types.Unset, NoneType, List[float]] = <wallaroo.wallaroo_ml_ops_api_client.types.Unset object>, provided_edges: Union[wallaroo.wallaroo_ml_ops_api_client.types.Unset, NoneType, List[float]] = <wallaroo.wallaroo_ml_ops_api_client.types.Unset object>)
2def __init__(self, bin_mode, aggregation, metric, num_bins, type, bin_weights=attr_dict['bin_weights'].default, provided_edges=attr_dict['provided_edges'].default): 3 self.bin_mode = bin_mode 4 self.aggregation = aggregation 5 self.metric = metric 6 self.num_bins = num_bins 7 self.type = type 8 self.bin_weights = bin_weights 9 self.provided_edges = provided_edges 10 self.additional_properties = __attr_factory_additional_properties()
Method generated by attrs for class AssaysGetResultsResponse200ItemSummarizerType0.
def
to_dict(self) -> Dict[str, Any]:
43 def to_dict(self) -> Dict[str, Any]: 44 bin_mode = self.bin_mode.value 45 46 aggregation = self.aggregation.value 47 48 metric = self.metric.value 49 50 num_bins = self.num_bins 51 type = self.type.value 52 53 bin_weights: Union[Unset, None, List[float]] = UNSET 54 if not isinstance(self.bin_weights, Unset): 55 if self.bin_weights is None: 56 bin_weights = None 57 else: 58 bin_weights = self.bin_weights 59 60 61 62 63 provided_edges: Union[Unset, None, List[float]] = UNSET 64 if not isinstance(self.provided_edges, Unset): 65 if self.provided_edges is None: 66 provided_edges = None 67 else: 68 provided_edges = self.provided_edges 69 70 71 72 73 74 field_dict: Dict[str, Any] = {} 75 field_dict.update(self.additional_properties) 76 field_dict.update({ 77 "bin_mode": bin_mode, 78 "aggregation": aggregation, 79 "metric": metric, 80 "num_bins": num_bins, 81 "type": type, 82 }) 83 if bin_weights is not UNSET: 84 field_dict["bin_weights"] = bin_weights 85 if provided_edges is not UNSET: 86 field_dict["provided_edges"] = provided_edges 87 88 return field_dict
@classmethod
def
from_dict(cls: Type[~T], src_dict: Dict[str, Any]) -> ~T:
92 @classmethod 93 def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T: 94 d = src_dict.copy() 95 bin_mode = AssaysGetResultsResponse200ItemSummarizerType0BinMode(d.pop("bin_mode")) 96 97 98 99 100 aggregation = AssaysGetResultsResponse200ItemSummarizerType0Aggregation(d.pop("aggregation")) 101 102 103 104 105 metric = AssaysGetResultsResponse200ItemSummarizerType0Metric(d.pop("metric")) 106 107 108 109 110 num_bins = d.pop("num_bins") 111 112 type = AssaysGetResultsResponse200ItemSummarizerType0Type(d.pop("type")) 113 114 115 116 117 bin_weights = cast(List[float], d.pop("bin_weights", UNSET)) 118 119 120 provided_edges = cast(List[float], d.pop("provided_edges", UNSET)) 121 122 123 assays_get_results_response_200_item_summarizer_type_0 = cls( 124 bin_mode=bin_mode, 125 aggregation=aggregation, 126 metric=metric, 127 num_bins=num_bins, 128 type=type, 129 bin_weights=bin_weights, 130 provided_edges=provided_edges, 131 ) 132 133 assays_get_results_response_200_item_summarizer_type_0.additional_properties = d 134 return assays_get_results_response_200_item_summarizer_type_0