def iteration(self, f: Oracle, x: np.ndarray,
optimizer: Callable[[Callable], Optimizer], iteration: int,
payload: Any) -> Tuple[np.ndarray, Any]:
grad = f.grad(*x)
# print(f"x = {x}, grad = {grad}")
correct_hesse = make_positive_definite(f.hesse(*x), self._stats)
inv_hes = np.linalg.inv(correct_hesse)
p = inv_hes.dot(grad)
# p = p / np.linalg.norm(p)
# print(f"p = {p}")
def g(lmbd):
return f(*(x - p * lmbd))
opt = optimizer(g)
opt._stats = self._stats
coeff = opt.optimize()
# print(f"coeff = {coeff}")
# print(f"prev_f = {f(*x)}, cur_f = {f(*(x - p * coeff))}")
delta = p * coeff
self._stats.report('*', p.size)
x1 = x - delta
self._stats.report('-', x.size)
return x1, None
def generate_mix_testcase(mixcase_list):
if not mixcase_list:
logger.info("没有需要组合的用例")
return None
oracle = Oracle(readconfig.db_url)
logger.info("<开始生成组合测试用例>")
for sl in mixcase_list:
mixid = sl['XF_MIXID']
caseid_list = sl['XF_CASEID'].split(',')
caseid_str = ','.join(caseid_list)
caseids = str(tuple(caseid_list))
if len(caseid_list) == 1:
caseids = caseids.replace(',', '')
# order by caseid,tsid
sql = "select * from xf_testcase where xf_caseid in %s " \
"order by instr('%s',rtrim(cast(xf_caseid as nchar))),xf_tsid" % (caseids, caseid_str)
loop_kwlist = oracle.dict_fetchall(sql)
if loop_kwlist:
func = DemoTestCase.group(loop_kwlist)
method_name = "test_" + mixid
setattr(DemoTestCase, method_name, func)
logger.info("已生成组合用例 %s ,包含基础用例id %s" % (method_name, caseid_list))
Action.set_case_info(method_name, loop_kwlist[0]["XF_CASEDESC"],
DemoTestCase)
else:
logger.info("基础用例id %s 错误,无法生成组合用例 test_%s " %
(caseid_list, mixid))
logger.info("<组合测试用例生成结束>")
oracle.close()
def get_location(self, location_id):
oracle = Oracle(readconfig.db_url)
sql = "select xf_location from xf_pagelocation where xf_locationid = '%s'" % location_id
location_list = oracle.dict_fetchall(sql)
if not location_list:
raise Exception("错误location_id ：%s，无法找到对应的location" % location_id)
location = location_list[0]['XF_LOCATION']
# clear string blank
location = location.strip()
# complement the location
# solve problem: prevent location id from maintain many time
# for example: add row case: location id change by rule
if "%s" in location:
location_ = location
location_ = location.replace("%s", "")
match_value = (re.findall("\[(.+?)\]",
location_))[0] # match a value in []
match_value = match_value.replace("=", ",")
# change location format to "[contains(@id,XXX)]" from [@id="XXX"]
rep_value = "[contains(" + match_value + ")]"
location_ = re.sub("\[(.+?)\]", rep_value, location_, count=1)
count = len(self.driver.find_elements_by_xpath(location_)) - 1
# count = self._use_keyword("count_elements", location_) - 1
location = location.replace("%s", str(count))
return location
def generate_testcases(testcaseid_list):
if testcaseid_list == []:
logger.info("找不到基础用例信息")
return None
oracle = Oracle(readconfig.db_url)
logger.info("<开始生成基础测试用例>")
for tl in testcaseid_list:
caseid = tl['XF_CASEID']
# notice the order of step execution
sql = "select * from xf_testcase where xf_caseid='%s' order by xf_tsid" % caseid
loop_kwlist = oracle.dict_fetchall(sql)
if loop_kwlist:
ifmix = loop_kwlist[0][
'XF_IFMIX'] # it will not execute the case if ifmix larger than 0
if ifmix:
logger.info("测试用例 %s 不能单独执行" % caseid)
else:
func = DemoTestCase.group(loop_kwlist)
method_name = "test_" + caseid
setattr(DemoTestCase, method_name, func)
logger.info("已生成用例 %s" % method_name)
Action.set_case_info(method_name,
loop_kwlist[0]["XF_CASEDESC"],
DemoTestCase)
else:
logger.info("找不到该用例id %s，无法生成用例 test_%s" % (caseid, caseid))
logger.info("<基础测试用例生成结束>")
oracle.close()
def get_location(self, location_id):
oracle = Oracle(readconfig.db_url)
sql = "select xf_location from xf_pagelocation where xf_locationid = '%s'" % location_id
location_list = oracle.dict_fetchall(sql)
location = location_list[0]['XF_LOCATION']
if location is None:
raise Exception("location_id 错误，无法找到对应的location")
return location
def locate_menu_by_id(self,*location_ids):
oracle = Oracle(readconfig.db_url)
sql = ""
for location_id in location_ids:
sql = "select xf_location from xf_pagelocation where xf_locationid = '%s'" % location_id
location_list = oracle.dict_fetchall(sql)
location = location_list[0]['XF_LOCATION']
if location == None:
raise Exception("location_id 错误，无法找到对应的location")
self.click(location)
def run(self,
f: Oracle,
x0: np.ndarray,
step_optimizer: Callable[[Callable], Optimizer],
iterations: Optional[int] = None,
dx: Optional[float] = None,
df: Optional[float] = None) -> OptimizationResult:
x = x0
iteration_count = 0
trajectory = [x]
cause = None
payload = self.init()
self._stats.clear()
f.reset_stat()
while (iterations is None) or (iteration_count < iterations):
self._stats.start()
x1, payload = self.iteration(f, x, step_optimizer, iteration_count,
payload)
self._stats.stop()
trajectory.append(x1)
delta = np.linalg.norm(x1 - x)
self._stats.report('*', x.size)
self._stats.report('+', x.size - 1)
# self._stats.report('sqrt', 1)
if dx is not None and np.linalg.norm(delta) < dx:
cause = "Exceed limit of accuracy for argument"
break
if df is not None and abs(f(*x1) - f(*x)) < df:
cause = "Exceed limit of accuracy for function"
break
if x.dot(x) > 1e10:
cause = "Divergence"
break
if np.linalg.norm(f.grad(*x)) < 1e-10:
cause = "Plateau"
break
iteration_count += 1
x = x1
self._stats.assimilate(f)
if cause is None:
cause = "Exceed limit of iterations"
arithm_stats = self._stats.arithm
if len(self._stats.extra) > 0:
arithm_stats = f'{arithm_stats} (+{",".join(list(map(lambda x: str(x[1] * 15), self._stats.extra.items())))})'
calls = [self._stats.fcalls, self._stats.gcalls, self._stats.hcalls]
return OptimizationResult(x0, x, iteration_count, trajectory, cause, f,
self.name(), self._stats.memory,
self._stats.elapsed_time, arithm_stats,
calls)
def iteration(self, f: Oracle, x: np.ndarray,
optimizer: Callable[[Callable], Optimizer], iteration: int,
payload: Any) -> Tuple[np.ndarray, Any]:
grad = f.grad(*x)
def g(lmbd):
return f(*(x - grad * lmbd))
opt = optimizer(g)
opt._stats = self._stats
coeff = optimizer(g).optimize()
delta = grad * coeff
self._stats.report('*', grad.size)
x1 = x - delta
self._stats.report('-', x.size)
return x1, None
def iteration(self, f: Oracle, x: np.ndarray,
optimizer: Callable[[Callable], Optimizer], iteration: int,
payload: Any) -> Tuple[np.ndarray, Any]:
ws, ps = payload
def __square(w: np.ndarray) -> float:
self._stats.report('*', w.size)
self._stats.report('+', w.size - 1)
return w.dot(w)
ws.append(-f.grad(*x)) # w_k
gamma = 0.0
if iteration % len(x) != 0:
gamma = __square(ws[-1]) / __square(ws[-2])
self._stats.report('/', 1)
p = ws[-1]
# p = p # / np.linalg.norm(p)
if gamma != 0.0:
p += gamma * ps[-1]
self._stats.report('*', p.size)
self._stats.report('+', p.size)
ps.append(p)
def g(lmbd):
return f(*(x + p * lmbd))
opt = optimizer(g)
opt._stats = self._stats
lr = opt.optimize()
# print(lr)
#
# print((ws[-1][0] * p[0] + ws[-1][1] * p[1]) /
# ((202.0 * p[0] - 200 * p[1]) * p[0] +
# (-200 * p[0] + 200 * p[1]) * p[1]))
# print(ws, p)
delta = p * lr
self._stats.report('*', p.size)
# print(f"latest gradient(w): {ws[-1]}, p = {p}, delta = {delta}, x = {x}, gamma = {gamma}, lr = {lr}")
x1 = x + delta
self._stats.report('+', x.size)
return x1, [ws, ps]
tmid = sl['TMID']
tcid_list = tcid.split(',')
for func_name in tcid_list:
demotestcase.use_keyword(DemoTestCase, func_name)
setattr(DemoTestCase, 'test_' + tmid, '')
def _generate_testsuite(tcid):
"""new a testsuite"""
tcid_list = tcid.split(',')
tests = []
for tl in tcid_list:
tl = "test_" + tl
tests.append(tl)
suite = unittest.TestSuite(map(DemoTestCase, tests))
return suite
oracle = Oracle(readconfig.db_url)
keyword_list = oracle.dict_fetchall(
"select * from xf_tcdata order by tcid,tsid")
_generate_testmethod(keyword_list)
suite_list = oracle.dict_fetchall("select * from xf_tsuite order by tmid")
oracle.close()
if __name__ == "__main__":
unittest.TextTestRunner().run()
# result = unittest.main(verbosity=2)
np.array([-1.0, 1.0]),
np.array([3.0, 2.0]),
np.array([0.1, -0.5]),
]
it = 100
for i in range(3):
print(f'Function {reprs[i]}:')
descent_results = []
conjugate_results = []
newton_results = []
for x0 in initial_points:
f = Oracle(2, functions[i], gradients[i], hesse[i], reprs[i])
descent_result = GradientDescent().run(
f,
x0,
lambda g: FibonacciOptimizer(g, (0.0, 1.01), 1e-5),
df=1e-6,
iterations=it)
descent_results.append(descent_result)
conj_result = ConjugateGradients().run(
f,
x0,
lambda g: FibonacciOptimizer(g, (0.0, 1.01), 1e-5),
df=1e-6,
iterations=it)
conjugate_results.append(conj_result)
# print("----")
from common.oracle import Oracle
from config import readconfig
from common.logger import logger
oracle = Oracle(readconfig.db_url)
Flag = readconfig.debug_mode
# deciding execute all testcases or debug some testcases controling by the config mode in ini,if mode == 1,
# debug case,else execute all testcases
# the config executeuser deciding whose testcase to execute
if Flag:
logger.info("***调试模式***")
execute_user = readconfig.execute_user
if execute_user == '':
sql = "select xf_caseid from xf_casedebug where xf_executeuser is null " \
"and xf_caseid is not null order by xf_caseid"
testcaseid_list = oracle.dict_fetchall(sql)
sql = "select xf_mixid from xf_casedebug where xf_executeuser is null " \
"and xf_mixid is not null order by xf_mixid"
mixid_list = oracle.dict_fetchall(sql)
else:
sql = "select xf_caseid from xf_casedebug where xf_executeuser = '******' " \
"and xf_caseid is not null order by xf_caseid" % execute_user
testcaseid_list = oracle.dict_fetchall(sql)
sql = "select xf_mixid from xf_casedebug where xf_executeuser = '******' " \
"and xf_mixid is not null order by xf_mixid" % execute_user
mixid_list = oracle.dict_fetchall(sql)
mixcase_list = []
for i in mixid_list:
mixid = i["XF_MIXID"]
sql = "select * from xf_mixcase where xf_mixid = '%s'" % mixid