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map data models

master
vargburz 5 years ago
parent
commit
14403e353f
  1. 33
      tools/analytic_model_tester.py

33
tools/analytic_model_tester.py

@ -3,24 +3,30 @@ ANALYTICS_PATH = '../analytics'
TESTS_PATH = '../tests'
sys.path.extend([ANALYTICS_PATH, TESTS_PATH])
import pandas as pd
import numpy as np
import asyncio
from typing import List, Tuple
import utils
from analytic_types.segment import Segment
from analytic_unit_manager import AnalyticUnitManager
START_TIMESTAMP = 1523889000000
# TODO: get_dataset
# TODO: get_segment
PEAK_DATA_MODELS = []
# dataset with 3 peaks
TEST_DATA = [0, 0, 3, 5, 7, 5, 3, 0, 0, 1, 0, 1, 4, 6, 8, 6, 4, 1, 0, 0, 0, 1, 0, 3, 5, 7, 5, 3, 0, 1, 1]
# TODO: more convenient way to specify labeled segments
POSITIVE_SEGMENTS = [{ 'from': 1, 'to': 7 }, { 'from': 22, 'to': 28 }]
NEGATIVE_SEGMENTS = [{ 'from': 11, 'to': 17 }]
DATA_MODELS = [
{
'type': 'peak',
'serie': TEST_DATA,
'segments': {
'positive': POSITIVE_SEGMENTS,
'negative': NEGATIVE_SEGMENTS
}
}
]
class TesterSegment():
@ -64,18 +70,19 @@ class Metric():
class TestDataModel():
def __init__(self, data_values: List[float], positive_segments, negative_segments, model_type: str):
def __init__(self, data_values: List[float], positive_segments: List[dict], negative_segments: List[dict], model_type: str):
self.data_values = data_values
self.positive_segments = positive_segments
self.negative_segments = negative_segments
self.model_type = model_type
def get_segments_for_detection(self, positive_amount, negative_amount):
def get_segments_for_detection(self, positive_amount: int, negative_amount: int):
positive_segments = [segment for idx, segment in enumerate(self.get_positive_segments()) if idx < positive_amount]
negative_segments = [segment for idx, segment in enumerate(self.get_negative_segments()) if idx < negative_amount]
return positive_segments + negative_segments
def get_formated_segments(self, segments, positive: bool):
def get_formated_segments(self, segments: List[dict], positive: bool):
# TODO: add enum
return [TesterSegment(segment['from'], segment['to'], positive).get_segment() for segment in segments]
def get_positive_segments(self):
@ -111,8 +118,14 @@ class TestDataModel():
task['payload']['segments'] = segments
return task
PEAK_DATA_MODEL = TestDataModel(TEST_DATA, POSITIVE_SEGMENTS, NEGATIVE_SEGMENTS, 'peak')
PEAK_DATA_MODELS.append(PEAK_DATA_MODEL)
PEAK_DATA_MODELS = list(map(
lambda data_model: TestDataModel(
data_model['serie'],
data_model['segments']['positive'],
data_model['segments']['negative'],
data_model['type']
)
))
async def main(model_type: str) -> None:
table_metric = []

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