def main():
PC = Computer_case(comp_id=1, manufacturer="BeQuiet!", price=299)
plyta1 = Motherboard(comp_id=2, manufacturer="Gigabyte", price=399)
procesor1 = Processor(comp_id=3,
manufacturer="intel",
model="i5-8600",
price=999)
procesor2 = Processor(comp_id=4,
manufacturer="AMD",
model="Ryzen 5 1600",
price=999)
ram1 = Memory(comp_id=5,
manufacturer="Corsair",
price=390,
memory_type="DDR4",
capacity=16)
ram2 = Memory(comp_id=6,
manufacturer="GoodRam",
price=300,
memory_type="DDR4",
capacity=16)
powersupply1 = Powersupply(comp_id=7,
manufacturer="BeQuiet!",
price=290,
ps_size=600)
plyta1.add_component(procesor1)
plyta1.add_component(ram1)
plyta1.add_component(ram2)
PC.add_component(powersupply1)
PC.add_component(plyta1)
PC.do_operation(plyta1.mb_components_price())
def test_create_combined_data():
data = '0.123,-0.123,5;0.456,-0.789,0.111;-0.212,0.001,1;'
parser = Parser(data)
processor = Processor(parser.parsed_data)
assert processor.dot_product_data == [0.0, 0.0, 0.0005219529804999682]
assert processor.filtered_data == [0, 0, 4.753597533351234e-05]
def test_create_separated_data():
data = '0.028,-0.072,5|0.129,-0.945,-5;0,-0.07,0.06|0.123,-0.947,5;0.2,-1,2|0.1,-0.9,3;'
parser = Parser(data)
processor = Processor(parser.parsed_data)
assert processor.dot_product_data == [-24.928348, 0.36629, 6.92]
assert processor.filtered_data == [0, 0, -1.7004231121083724]
def test_create_non_zero_data():
user = User('female', 167, 70)
trial = Trial('walk 1', 100, 18)
parser = Parser(open('test/data/female-167-70_walk2-100-10.txt').read())
processor = Processor(parser.parsed_data)
analyzer = Analyzer(processor.filtered_data, user, trial)
assert analyzer.steps == 10
assert analyzer.delta == -8
assert analyzer.distance == 700
assert analyzer.time == 1037 / 100
from models.processor import Processor
from models.leap import LEAPModel
from exp.coverage import config_mimic as config
from utils.data import dump
config = config.get_config()
print(config.saved_model_file.split('/')[-1])
p = Processor(config)
model = LEAPModel(p, config)
# model.do_train()
model.load_params(
'build/mimic_sort_seq2seq_len_50_seed13_100d_lr0.001_h256.model')
# model.do_reinforce(scorer)
model.do_eval(training=False,
filename='mimic_unsort_seq2seq.h256.txt',
max_batch=5000)
# model.load_params('../models/resume_seed13_100d_lr0.001_h256.model')
# ret = model.do_generate(data)
#
# from utils.eval import Evaluator
# eva = Evaluator()
# cnt = 0
# truth = []
# sum_jaccard = 0
# for line in open("seq2seq.h256.txt"):
# if cnt % 3 == 1:
# truth = set(line.strip().split("T: ")[1].split(" "))
def feed(self):
self.parser = Parser(self.data)
self.processor = Processor(self.parser.parsed_data)
self.analyzer = Analyzer(self.processor.filtered_data, self.user,
self.trial)