def read_data():
import models
df = pd.read_csv('udemy_data.csv')
for index, _df in df.iterrows():
# date型への変更
date = datetime.datetime.strptime(_df['date'], '%Y/%m/%d').date()
row = models.Data(date=date,
subscribers=_df['subscribers'],
reviews=_df['reviews'])
db_session.add(row)
db_session.commit()
def getDataInOrange():
data = json.loads(request.data.decode('utf-8'))
if len(data) > 0:
device_id = data['device_id']
print(data)
for sensor in data["sensors"]:
print(sensor)
sensor_data = models.Data()
sensor_data.device_id = device_id
sensor_data.sensor_id = sensor['id']
sensor_data.data = sensor['data']
sensor_data.save()
return jsonify({'message': 'data send', 'code': 200})
return jsonify({'message': 'dont send data', 'code': 500})
import models LSTM256 = models.LSTM(256, 3) LSTM256.create_model() Data = models.Data([1, 1, 1], 20000, 0.01) Data.getData() LSTM256.fit_model(5, Data) LSTM256.print_stats() LSTM256.model.summary() LSTM256_States = models.States(1100, 1000) LSTM256_States.create_unperturbed(LSTM256, Data) LSTM256_States.create_pertrurbed(LSTM256, Data) print(LSTM256_States.unperturbed - LSTM256_States.perturbed) LSTM256_lyapunov = models.Lyapunov(LSTM256_States) LSTM256_lyapunov.plot_exponent(LSTM256_States) LSTM_Layer = LSTM256.model.layers[0] LSTM_Layer.weights import matplotlib.pyplot as plt plt.plot(np.linspace(1, 10, 20), line)
def parse_implementation_schedule(schedule, out, package_filename):
out["last_updated_date"] = datetime.datetime.now()
out["publisher_actual"] = schedule.find("metadata").find("publisher").text
out["publisher_code_actual"] = schedule.find("metadata").find(
"publisher").get("code")
out["schedule_version_actual"] = schedule.find("metadata").find(
"version").text
out["schedule_date_actual"] = schedule.find("metadata").find("date").text
out["publisher_original"] = schedule.find("metadata").find(
"publisher").text
out["publisher_code_original"] = schedule.find("metadata").find(
"publisher").get("code")
out["schedule_version_original"] = schedule.find("metadata").find(
"version").text
out["schedule_date_original"] = schedule.find("metadata").find("date").text
sched = models.ImpSchedule(**out)
db.session.add(sched)
db.session.commit()
pd = {}
#properties come from module properties.py
for k, v in properties.properties.items():
try:
pd[k] = (eval(v["data"]))
except AttributeError:
pass
for k, v in pd.items():
d = models.ImpScheduleData()
d.publisher_id = sched.id
d.segment = k
d.segment_value_actual = v
d.segment_value_original = v
db.session.add(d)
elements = models.Element.query.all()
for element in elements:
# element name is element.name
for p in (models.Property.query.filter_by(
parent_element=element.id).all()):
data = models.Data()
data.property_id = p.id
data.impschedule_id = sched.id
if (p.defining_attribute is not None):
path = "/[@" + p.defining_attribute + '="' + p.defining_attribute_value + '"]'
element_name = element.name + path
else:
element_name = element.name
try:
data.status_actual = schedule.find(element.level).find(
element_name).find("status").get("category")
except AttributeError:
pass
try:
data.exclusions = schedule.find(element.level).find(
element_name).find("exclusions").find("narrative").text
except AttributeError:
pass
if (data.exclusions is None):
data.exclusions = ""
try:
data.notes_actual = schedule.find(
element.level).find(element_name).find("notes").text
except AttributeError:
data.notes_actual = ""
try:
data.date_actual = datetime.datetime.strptime(
schedule.find(element.level).find(element_name).find(
"publication-date").text, "%Y-%m-%d")
except AttributeError:
pass
data.date_recorded = datetime.datetime.now()
db.session.add(data)
db.session.commit()
return "Done "
def setUp(self):
self._data_file = models.Data(filename='test_data.csv')