def read_sparda_ethik(self,infile,is_sparda=True):
blz = None
baccount_no = None
r = 0 if is_sparda else 1
for row in utils.get_csv('iso-8859-4',infile,replacenl=is_sparda):
if not row:
continue
if row[0]=='BLZ:':
blz = int(row[1])
continue
if row[0]=='Konto:':
baccount_no = int(row[1])
continue
date = utils.convert_date4(row[0])
if not date:
continue
if row[9+r]=='Anfangssaldo':
self.sbal = utils.read_float(row[11+r],row[12+r])
continue
if row[9+r]=='Endsaldo':
self.ebal = utils.read_float(row[11+r],row[12+r])
continue
be = BankStatementEntry(self)
be.posting_date = date
be.purpose = row[8+r]
be.partner = row[3+r]
be.partner_iban = row[5+r]
be.amount = utils.read_float(row[11+r],row[12+r])
be.cleanup()
self.entries.append(be)
if blz and baccount_no:
self.iban = utils.iban_de(blz,baccount_no)
def main():
data = np.transpose(utils.get_csv('data.csv'))
X = data[0]
y = data[1]
theta0, theta1 = train(X, y)
plot_line(data, theta0, theta1)
utils.put_csv('parameters.csv', theta0, theta1)
def test_items_serializers(
client,
item_lib_martigny, # on shelf
item_lib_fully, # on loan
csv_header,
json_header,
rero_json_header,
patron_martigny,
librarian_martigny,
librarian_sion,
loan_pending_martigny):
"""Test record retrieval."""
login_user(client, librarian_martigny)
item_url = url_for('invenio_records_rest.item_item',
pid_value=item_lib_fully.pid)
response = client.get(item_url, headers=json_header)
assert response.status_code == 200
data = get_json(response)
assert data['metadata'].get('item_type', {}).get('$ref')
item_url = url_for('invenio_records_rest.item_item',
pid_value=item_lib_martigny.pid)
response = client.get(item_url, headers=json_header)
assert response.status_code == 200
data = get_json(response)
assert data['metadata'].get('item_type', {}).get('$ref')
item_url = url_for('invenio_records_rest.item_item',
pid_value=item_lib_fully.pid,
resolve=1)
response = client.get(item_url, headers=json_header)
data = get_json(response)
assert data['metadata'].get('item_type', {}).get('pid')
# test if all key exist into response with a value
for key in ['created', 'updated', 'id', 'links', 'metadata']:
assert key in data
assert data[key]
list_url = url_for('invenio_records_rest.item_list')
response = client.get(list_url, headers=rero_json_header)
assert response.status_code == 200
list_url = url_for('api_item.inventory_search')
response = client.get(list_url, headers=csv_header)
assert response.status_code == 200
data = get_csv(response)
assert data
assert '"pid","document_pid","document_title","document_creator",' \
'"document_main_type","document_sub_type","library_name",' \
'"location_name","barcode","call_number","second_call_number",' \
'"enumerationAndChronology","item_type","temporary_item_type",' \
'"temporary_item_type_end_date","general_note","staff_note",' \
'"checkin_note","checkout_note","loans_count","checkout_date",' \
'"due_date","last_transaction_date","status","created",' \
'"issue_status","issue_status_date","issue_claims_count",' \
'"issue_expected_date","issue_regular"' in data
def download_fulfill():
'''
Will redirect the user to download the csv file that matches
the given uid.
Note: currently not secure, but the contents of the csv are not
critical.
'''
uid = request.args.get('fname')
to_serve = utils.get_csv(fname, directory=DIRECTORY)
return send_file(to_serve)
def institution_process(countries: Dict[str, Country]) -> List[Institution]:
rows = get_row(dbc.GRID_DATABASE_DIR / "institutes.csv")
row_count = csv_size(dbc.GRID_DATABASE_DIR / "institutes.csv")
attrs = ["addresses", "acronyms", "aliases", "labels", "links", "types"]
# Group the GRID data tables by grid_id for better access.
institution_attrs = [
get_csv(dbc.GRID_DATABASE_DIR / f"{attr}.csv", "grid_id")
for attr in attrs
]
institutions_list: List[Institution] = []
pbar = tqdm(total=row_count)
for row in rows:
nullify(row)
# Get all the data related to the current institution.
address, acronym, alias, label, link, type = [
attr.get(row["grid_id"]) for attr in institution_attrs
]
# Create 'soup' variable for fuzzy matching of institutions.
soup = [row["name"]]
if address:
country = dbc.country_name_mapper(address[0].pop("country"))
institution = Institution(**{**row, **address[0]})
institution.country = countries[country]
soup.append(country)
else:
institution = Institution(**row)
if acronym:
institution.acronyms = [Acronym(**i) for i in acronym]
soup.extend(i["acronym"] for i in acronym)
if alias:
institution.aliases = [Alias(**i) for i in alias]
soup.extend(i["alias"] for i in alias)
if label:
institution.labels = [Label(**i) for i in label]
soup.extend(i["label"] for i in label)
if link:
institution.links = [Link(**i) for i in link]
if type:
institution.types = [Type(**i) for i in type]
institution.soup = " | ".join(i for i in soup)
institutions_list.append(institution)
pbar.update()
pbar.close()
del institution_attrs # Free-up memory (~ 10^5 institutions).
return institutions_list
def run():
station_ids_to_plot = None # [508, 509, 510, 101, 102]
stations = {}
timestamps = []
last_timestamp = None
station_names = {}
for row in get_csv('stations.csv'):
station_id = int(row['station_id:ID(Station)'])
station_names[station_id] = row['name'].replace('/', '/\n')
for row in get_csv('extra/free_bikes_at_station.csv'):
if last_timestamp != row['timestamp:INT']:
last_timestamp = row['timestamp:INT']
timestamps.append(
datetime.fromtimestamp(float(row['timestamp:INT'])))
station_id = int(row['station_id:INT'])
if station_ids_to_plot and station_id not in station_ids_to_plot:
continue
if not station_id in stations:
stations[station_id] = []
station = stations[station_id]
station.append(int(row['free_bikes:INT']))
plot(timestamps, stations, station_names)
def test_items_serializers(
client,
item_lib_martigny, # on shelf
item_lib_fully, # on loan
csv_header,
json_header,
rero_json_header,
patron_martigny_no_email,
librarian_martigny_no_email,
librarian_sion_no_email,
loan_pending_martigny):
"""Test record retrieval."""
login_user(client, librarian_martigny_no_email)
item_url = url_for('invenio_records_rest.item_item',
pid_value=item_lib_fully.pid)
response = client.get(item_url, headers=json_header)
assert response.status_code == 200
data = get_json(response)
assert data['metadata'].get('item_type').get('$ref')
item_url = url_for('invenio_records_rest.item_item',
pid_value=item_lib_martigny.pid)
response = client.get(item_url, headers=json_header)
assert response.status_code == 200
data = get_json(response)
assert data['metadata'].get('item_type').get('$ref')
item_url = url_for('invenio_records_rest.item_item',
pid_value=item_lib_fully.pid,
resolve=1)
response = client.get(item_url, headers=json_header)
data = get_json(response)['metadata']
assert data.get('item_type').get('pid')
list_url = url_for('invenio_records_rest.item_list')
response = client.get(list_url, headers=rero_json_header)
assert response.status_code == 200
list_url = url_for('invenio_records_rest.item_list')
response = client.get(list_url, headers=csv_header)
assert response.status_code == 200
data = get_csv(response)
assert data
assert '"pid","document_pid","document_title","document_creator",' \
'"document_type","location_name","barcode","call_number",' \
'"second_call_number","loans_count","last_transaction_date",' \
'"status","created"' in data
def read_sparkasse(self,infile):
first_row = True
for row in utils.get_csv('iso-8859-4',infile):
if not row:
continue
if first_row:
first_row = False
continue
be = BankStatementEntry(self)
self.iban = row[0]
be.posting_date = utils.convert_date2(row[1])
be.purpose = row[4]
be.partner = row[11]
be.partner_iban = row[12]
be.amount = utils.read_float(row[14])
be.cleanup()
self.entries.append(be)
def test_stats_get(client, stats, csv_header):
"""Test record retrieval."""
item_url = url_for('invenio_records_rest.stat_item', pid_value=stats.pid)
res = client.get(item_url)
assert res.status_code == 200
assert res.headers['ETag']
data = get_json(res)
# Check metadata
for k in ['created', 'updated', 'metadata', 'links']:
assert k in data
# Check self links
res = client.get(to_relative_url(data['links']['self']))
assert res.status_code == 200
# CSV format
item_url = url_for('invenio_records_rest.stat_item',
pid_value=stats.pid,
format='csv')
res = client.get(item_url, headers=csv_header)
assert res.status_code == 200
data = get_csv(res)
assert data == (
'library id,library name,number_of_active_patrons,'
'number_of_checkins,number_of_checkouts,'
'number_of_deleted_items,number_of_documents,'
'number_of_items,number_of_librarians,number_of_libraries,'
'number_of_new_items,number_of_new_patrons,'
'number_of_order_lines,number_of_patrons,'
'number_of_renewals,number_of_requests,'
'number_of_satisfied_ill_request\r\n'
'lib3,Library of Fully,0,0,0,0,1,1,0,2,1,0,0,0,0,0,0\r\n'
'lib1,Library of Martigny-ville,0,0,0,0,1,1,0,2,1,0,0,0,0,0,0\r\n'
'lib4,Library of Sion,0,0,0,0,1,1,0,1,1,0,0,0,0,0,0\r\n')
list_url = url_for('invenio_records_rest.stat_list')
res = client.get(list_url)
assert res.status_code == 200
data = get_json(res)
assert data['hits']['hits']
def get_baccount(cls,infile):
blz = None
baccount_no = None
iban = None
for row in utils.get_csv('iso-8859-4',infile):
if not row:
continue
if row[0]=='BLZ:':
blz = int(row[1])
continue
if row[0]=='Konto:':
baccount_no = int(row[1])
continue
if row[0][0:2]=='DE':
iban = row[0]
break
if blz and baccount_no:
iban = utils.iban_de(blz,baccount_no)
break
if iban and iban in BankAccount.baccounts_by_iban:
return (BankAccount.baccounts_by_iban[iban],iban)
else:
return (None,iban)
import numpy as np
import utils as utils
import functools as ft
import train as t
from plot_line import plot_line
data = np.transpose(utils.get_csv('data.csv'))
X = data[0]
y = data[1]
sample_size = .1
mask = np.random.sample(y.size)
while (((mask < sample_size) == True).size == 0):
mask = np.random.sample(y.size)
train = mask >= sample_size
test = mask < sample_size
theta0, theta1 = t.train(X[train], y[train])
estimation = theta0 + theta1 * X[test]
error = abs((estimation - y[test]) / y[test])
error = sum(error) / error.size
print("sample size = {}".format(y[train].size))
print("test size = {}".format(y[test].size))
print("error = {:2f}%".format(error * 100))
import numpy as np
import utils as utils
try:
m = int(input("mileage: "))
parameters = utils.get_csv('parameters.csv')
theta0 = parameters[0]
theta1 = parameters[1]
prediction = theta0 + m * theta1
print("estimate: {:.2f}".format(prediction))
except ValueError:
print("Please enter valid int input")
import matplotlib as mpl
mpl.use('TkAgg')
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import utils as utils
from train import cost
import numpy as np
from functools import partial
fig = plt.figure()
ax = fig.gca(projection='3d')
data = utils.get_csv('data.csv')
data = np.transpose(data)
km = data[0]
price = data[1]
m = 40
theta0 = np.linspace(7000, 9000, num=m)
theta1 = np.linspace(-0.05, 0.0, num=m)
theta0, theta1 = np.meshgrid(theta0, theta1)
def partial_cost(theta0, theta1):
return cost(km, price, theta0, theta1)
cost_fun = np.vectorize(partial_cost)
Z = cost_fun(theta0, theta1)
surf = ax.plot_surface(theta0, theta1, Z, rstride=1, cstride=1, cmap=mpl.cm.coolwarm,
linewidth=0, antialiased=False)
fig.colorbar(surf, shrink=0.5, aspect=10)
plt.show()