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你好，我是很新的Python语言，我收到以下错误，运行test.py文件时Python对象调用错误
Traceback (most recent call last):
File "D:/Py Charm projects/Example/test.py", line 3, in <module>
repository = Repository(Config)
File "D:\Py Charm projects\Example\repository.py", line 29, in __init__
assert isinstance(config, Config)
AssertionError
test.py
from repository import Repository
from configuration import Config
repository = Repository(Config)
dataset, labels = repository.get_dataset_and_labels()
库.py
import json
import re
import time
from random import random
from glob import glob
from os.path import basename, dirname
from os.path import sep as path_sep
from os.path import join as path_join
from datetime import datetime
from numpy import inf, array
from pandas import DataFrame
from configuration import Config
__author__ = 'luis'
methods = []
def method_list(method):
if method not in methods:
methods.append(method)
return method
class Repository(object):
def __init__(self, config):
self.expert_locations = {}
assert isinstance(config, Config)
self.config = config
self.base_path = config.base_path
self.config_path = config.config_path
self.sample_path = config.path_user_sample
self.expert_data_path = config.expert_data_path
self.users = []
self.access_points = {}
self.locations = {}
self.goal_types = {}
self.goals = {}
self.goals_timetable = {}
self.samples = {}
self.expert_samples = {}
self.expert_validation_samples = {}
self.fingerprints = {}
for m in methods:
m(self)
@method_list
def load_users(self):
user_file = "%s/users.json" % self.config_path
with open(user_file) as fd:
jf = json.load(fd)
for u in jf:
self.users.append(u['user_id'])
@method_list
def load_locations(self):
user_file = "%s/goallist.json" % self.config_path
with open(user_file) as fd:
jf = json.load(fd)
for loc in jf:
self.locations.setdefault((loc['latitude'], loc['longitude']), set())
@method_list
def load_goals(self):
file_list = glob('%s/Goals/Goals*/*.json' % self.config_path)
for f in file_list:
goal_type = re.match(".*_([a-z]*)", dirname(f)).group(1)
time_name = basename(f).split(".")[0]
ts = time.mktime(time.strptime(time_name, "%Y-%m-%d_%H-%M-%S"))
with open(f) as fd:
jf = json.load(fd)
for loc in jf:
priority = self.goals.setdefault(goal_type, {}).setdefault(ts, {})
priority[(loc['location']['latitude'], loc['location']['longitude'])] = loc['priority']
self.goal_types = dict([x[::-1] for x in enumerate(self.goals)])
@method_list
def load_expert_data(self):
file_list = glob("%s/%s" % (self.expert_data_path, self.config.expert_data_glob_pattern))
for f in file_list:
user = re.match(".*StampRally_([a-z]*)/", dirname(f)).group(1)
time_name = basename(f).split(".")[0]
ts = time.mktime(time.strptime(time_name, "%Y-%m-%d_%H-%M-%S"))
with open(f) as fd:
jf = json.load(fd)
for fingerprint in jf:
loc = (fingerprint['location']['latitude'], fingerprint['location']['longitude'])
for mac, v in fingerprint['fingerprint']['wifi'].items():
# self.access_points.setdefault(mac, set()).add(loc)
self.expert_locations.setdefault(loc, set()).add(mac)
self.expert_samples.setdefault(ts, {}).setdefault(user, {}).setdefault(loc, []).append(
{'level': v["level"], 'mac': mac})
@method_list
def load_expert_data_test(self):
file_list = glob("%s/%s" % (self.expert_data_path, self.config.expert_data_test_glob_pattern))
for f in file_list:
user = re.match(".*StampRally_([a-z]*)/", dirname(f)).group(1)
time_name = basename(f).split(".")[0]
ts = time.mktime(time.strptime(time_name, "%Y-%m-%d_%H-%M-%S"))
with open(f) as fd:
jf = json.load(fd)
for fingerprint in jf:
loc = (fingerprint['location']['latitude'], fingerprint['location']['longitude'])
for mac, v in fingerprint['fingerprint'].items():
# self.access_points.setdefault(mac, set()).add(loc)
self.expert_locations.setdefault(loc, set()).add(mac)
self.expert_validation_samples.setdefault(ts, {}).setdefault(user, {}).setdefault(loc, []).append(
{'level': v["level"], 'mac': mac})
@method_list
def load_goals_timetable(self):
file_list = glob('%s/Goals/Users/*.json' % self.config_path)
for f in file_list:
time_name = basename(f).split(".")[0]
ts = time.mktime(time.strptime(time_name, "%Y-%m-%d_%H-%M-%S"))
with open(f) as fd:
jf = json.load(fd)
try:
goal_type = jf.values()[0]
except IndexError:
continue
self.goals_timetable.setdefault(ts, []).append(self.goal_types[goal_type])
@method_list
def load_samples(self):
file_list = glob('%s/StampRally_*/%s/*.json' % (self.config.data_set_path, self.sample_path))
for f in file_list:
user = re.match(".*StampRally_([em][0-9])/", dirname(f)).group(1)
time_name = basename(f).split(".")[0]
ts = time.mktime(time.strptime(time_name, "%Y-%m-%d_%H-%M-%S"))
with open(f) as fd:
jf = json.load(fd)
for fingerprint in jf:
loc = (fingerprint['location']['latitude'], fingerprint['location']['longitude'])
for mac, v in fingerprint['fingerprint']['wifi'].items():
self.access_points.setdefault(mac, set()).add(loc)
self.locations[loc].add(mac)
self.samples.setdefault(ts, {}).setdefault(user, {}).setdefault(loc, []).append(
{'level': v["level"], 'mac': mac})
def iter_samples(self, time_filter=None, user_filter=None, loc_filter=None):
time_filter = time_filter and time_filter or (0., inf)
user_filter = user_filter and re.compile(user_filter) or re.compile(".*")
for ts, users in filter(lambda x: time_filter[0] <= x[0] <= time_filter[1], self.samples.items()):
for u, locations in filter(lambda x: user_filter.search(x[0]), users.items()):
for loc, fingerprints in filter(lambda x: not loc_filter and True or loc_filter == x[0],
locations.items()):
for fingerprint in fingerprints:
mac = fingerprint['mac']
value = fingerprint['level']
yield [ts, u, loc, mac, value]
def iter_fingerprints(self, time_filter=None, user_filter=None, loc_filter=None, group_filter=None, src='samples'):
time_filter = time_filter and time_filter or (0., inf)
user_filter = user_filter and re.compile(user_filter) or re.compile(".*")
src = getattr(self, src)
for ts, users in src.items():
if not (time_filter[0] <= ts <= time_filter[1]):
continue
for u, locations in users.items():
if not user_filter.search(u):
continue
for loc, fingerprints in locations.items():
if loc_filter and loc_filter != loc:
continue
if group_filter:
try:
fps = [fp for fp in fingerprints if fp['mac'] in group_filter[loc]]
except TypeError:
fps = [fp for fp in fingerprints if fp['mac'] in group_filter]
except KeyError:
fps = fingerprints
yield [ts, u, loc, fps]
continue
yield [ts, u, loc, fingerprints]
def get_dataset_and_labels(self, columns=None, **kwargs):
df = []
labels = []
for ts, usr, loc, fingerprint in self.iter_fingerprints(**kwargs):
fp = dict([(m['mac'], m['level']) for m in fingerprint])
df.append(fp)
labels.append(loc)
return DataFrame(df, columns=columns), array(labels)
def create_time_series(self, time_filter=None, user_filter=None, sample_time=70):
time_filter = time_filter and time_filter or (0., inf)
user_filter = user_filter and re.compile(user_filter) or re.compile(".*")
time_series = []
for ts, users in filter(lambda x: time_filter[0] <= x[0] <= time_filter[1], self.samples.items()):
lts = ts
for u, locations in filter(lambda x: user_filter.search(x[0]), users.items()):
for loc, fingerprints in locations.items():
for fingerprint in fingerprints:
mac = fingerprint['mac']
lts += random()
time_series.append([lts, mac])
lts += sample_time
return time_series
@method_list
def update_week_specs(self):
week_stats = {}
for ts in self.samples:
date = datetime.fromtimestamp(ts)
week = date.strftime("%W")
week_stats.setdefault(week, []).append(ts)
self.config.week_specs = dict([("W%s" % w, (min(v), max(v))) for w, v in week_stats.items()])
self.config.week_names = sorted(self.config.week_specs.keys(), key=lambda x: self.config.week_specs[x][0])
configuration.py
from os.path import sep as path_sep
from os.path import join as path_join
class Config(object):
base_path = "."
date_format = "%Y-%m-%d_%H-%M-%S"
recording_start = 1390202100.0
stages = []
var_fill = -200.
knn_var_fill = -90.
week_specs = {"W03": (1390202100.6, 1390589153.57),
"W04": (1390806000.32, 1391193208.91),
"W05": (1391410800.65, 1391797033.75),
"W06": (1392015600.01, 1392398212.78)}
week_names = sorted(week_specs.keys())
week_for_evaluation = week_names
path_user_sample=path_join("Uploads", "TrainData")
expert_data_glob_pattern = path_join("StampRally_*", "Uploads", "TrainData", "*.json")
expert_data_test_glob_pattern = path_join("StampRally_*", "ValidationData", "*.json")
k = 50
@property
def data_set_path(self):
return path_join(self.base_path, "SCSUT2014v1", "EXP201312")
@property
def expert_data_path(self):
return path_join(self.base_path, "SCSUT2014v1", "TESTDATA")
@property
def config_path(self):
return path_join(self.data_set_path, "StampRally")
@property
def results_path(self):
return path_join(self.base_path, "results")
@property
def rules_path(self):
return path_join(self.results_path, 'rules')
@property
def unified_time_series_path(self):
return path_join(self.results_path, 'timeseries')
@property
def titarl_configs_path(self):
return path_join(self.base_path, 'titarl_cfg')
@property
def rule_learning_template(self):
return path_join(self.base_path, "learning_config_e0.xml")
@property
def learn_all_file(self):
return path_join(self.base_path, "learn_all.bat")
@property
def log_path(self):
return path_join(self.base_path, "logs")
@property
def trees_path(self):
return path_join(self.results_path, "trees")
config = Config()
paths = []
for attrib in dir(config):
if "_path" in attrib:
paths.append(attrib)
for path in [config.titarl_configs_path, config.unified_time_series_path, config.rules_path, config.trees_path]:
paths.append("%s%squarterly" % (path, path_sep))
config.paths = paths
请帮助我，我不知道是什么错误是，我已经在谷歌搜索一样好，但没有得到任何解决这个错误，什么样的错误这是我无法理解，所以请帮助我卡在这里，因为我对Python语言很新。
在哪个文件做我有编辑？ –