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This commit is contained in:
mehak-sachdeva 2017-02-01 11:42:58 -05:00
parent cbd95fa0a2
commit d7bccc1063
3 changed files with 28 additions and 20 deletions
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2
src/py/crankshaft/crankshaft/analysis_data_provider.py
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@ -119,7 +119,7 @@ class AnalysisDataProvider(object):
for a in params['feature_columns']]) for a in params['feature_columns']])
query = ''' query = '''
SELECT SELECT
Array({joined_features}) As features Array[{joined_features}] As features
FROM ({subquery}) as q FROM ({subquery}) as q
'''.format(subquery=params['subquery'], '''.format(subquery=params['subquery'],
joined_features=joined_features) joined_features=joined_features)

18
src/py/crankshaft/crankshaft/segmentation/segmentation.py
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@ -68,8 +68,7 @@ class Segmentation(object):
""" """
params = {"subquery": target_query, params = {"subquery": target_query,
"id_col": id_col, "id_col": id_col}
"feature_columns": feature_columns}
target, features, target_mean, \ target, features, target_mean, \
feature_means = self.clean_data(variable, feature_columns, query) feature_means = self.clean_data(variable, feature_columns, query)
@ -81,6 +80,10 @@ class Segmentation(object):
rowid = self.data_provider.get_segmentation_data(params) rowid = self.data_provider.get_segmentation_data(params)
'''
rowid = [{'ids': [2.9, 4.9, 4, 5, 6]}]
'''
return zip(rowid, result, accuracy_array) return zip(rowid, result, accuracy_array)
def predict_segment(self, model, feature_columns, target_query, def predict_segment(self, model, feature_columns, target_query,
@ -101,9 +104,12 @@ class Segmentation(object):
results = [] results = []
cursors = self.data_provider.get_segmentation_predict_data(params) cursors = self.data_provider.get_segmentation_predict_data(params)
# cursors = [{'': ,
# '': }] '''
# cursors = [{'features': [[m1[0],m2[0],m3[0]],[m1[1],m2[1],m3[1]],
[m1[2],m2[2],m3[2]]]}]
'''
while True: while True:
rows = cursors.fetch(batch_size) rows = cursors.fetch(batch_size)
if not rows: if not rows:
@ -131,7 +137,7 @@ class Segmentation(object):
data = self.data_provider.get_segmentation_model_data(params) data = self.data_provider.get_segmentation_model_data(params)
''' '''
data: [{'target': [2.9, 4.9, 4, 5, 6]}, data = [{'target': [2.9, 4.9, 4, 5, 6]},
{'feature1': [1,2,3,4]}, {'feature2' : [2,3,4,5]} {'feature1': [1,2,3,4]}, {'feature2' : [2,3,4,5]}
] ]
''' '''

4
src/py/crankshaft/test/test_segmentation.py
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@ -1,9 +1,11 @@
import unittest import unittest
import numpy as np import numpy as np
from helper import plpy, fixture_file from helper import plpy, fixture_file
from crankshaft.analysis_data_provider import AnalysisDataProvider
from crankshaft.segmentation import Segmentation from crankshaft.segmentation import Segmentation
import json import json
class RawDataProvider(AnalysisDataProvider): class RawDataProvider(AnalysisDataProvider):
def __init__(self, raw_data1, raw_data2, raw_data3): def __init__(self, raw_data1, raw_data2, raw_data3):
self.raw_data1 = raw_data1 self.raw_data1 = raw_data1
@ -19,6 +21,7 @@ class RawDataProvider(AnalysisDataProvider):
def get_segmentation_model_data(self, params): def get_segmentation_model_data(self, params):
return self.raw_data3 return self.raw_data3
class SegmentationTest(unittest.TestCase): class SegmentationTest(unittest.TestCase):
"""Testing class for Moran's I functions""" """Testing class for Moran's I functions"""
@ -49,7 +52,6 @@ class SegmentationTest(unittest.TestCase):
training_data = self.generate_random_data(n_samples, random_state_train) training_data = self.generate_random_data(n_samples, random_state_train)
test_data, test_y = self.generate_random_data(n_samples, random_state_test, row_type=True) test_data, test_y = self.generate_random_data(n_samples, random_state_test, row_type=True)
ids = [{'cartodb_ids': range(len(test_data))}] ids = [{'cartodb_ids': range(len(test_data))}]
rows = [{'x1': 0, 'x2': 0, 'x3': 0, 'y': 0, 'cartodb_id': 0}] rows = [{'x1': 0, 'x2': 0, 'x3': 0, 'y': 0, 'cartodb_id': 0}]