fabio | I/O library for images produced by 2D X-ray detector | Machine Learning library

studlist = ['mario;90;80', 'denis;80;70', 'fabio;60;70']

for student in studlist:
    name, *scores = student.split(';')
    print(f"The total score of {name} is {sum(int(s) for s in scores)}")

# The total score of mario is 170
# The tot

studlist = ['mario;90;80', 'denis;80;70', 'fabio;60;70']

for name_score in studlist:
    name_score_list = name_score.split(";")
    print('the total score of',name_score_list[0], 'is' , int(name_score_list[1])+int(name_score_list[2]))

weight = K.variable(initializer(shape, dtype=dtype), dtype=dtype, ......

def initialize_weights(shape, dtype=None):
  return np.random.normal(loc = 0.0, scale = 1e-2, size = shape)

def initialize_bias(shape, dtype

from dd import autoref as _bdd


# assignments where the Boolean function is TRUE
data = {'0 0 0 0 0', '0 0 0 1 0', '1 1 1 1 0'}

# variable names
vrs = [f'x{i}' for i in range(1, 6)]
# convert the assignments to dictionaries
assignments =

import logging, sys, os
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format='%(message)s | \'%(name)s:%(lineno)s\'')
log = logging.getLogger(os.path.basename(__file__))

log.debug("hello logging linked to source")

def Decrypt():
    cipher_decrypt = AES.new(key, AES.MODE_CFB, iv=iv)   # <-- add this
    with open(fileConfigBIN, "rb") as binary_file:
        data1 = binary_file.read()
        print("DATA READ FROM FILE: ", data1)
        deciphere

pred_df = df[df['my_column'].isna()]        #For the prediction, use a Dataframe with only the missing values. Problem solved
df_x = pred_df[['lat','long']]
prediction = clf.predict(df_x)
df.loc[df['my_column'].isna(), 'my_column'] = predi

d = np.zeros((Ns+1, Ns+1), dtype=np.complex_)
for j in range(2, Ns):
    for k in range(1, j+1):
        d[j,k] = D(P[j], P[k])

A = np.zeros((Ns-1, Ns-1), dtype=np.complex_)
for j in range(1, Ns-1):
    for k in range(1, j+1):
        A[j

subprocess.check_output(["git", "fetch", "origin", ">>", "C:/bitbucket_backup/backup.log", "2>&1"], cwd='C:/bitbucket_backup/loopx', shell=True)

output = subprocess.check_output(["git", "fetch", "origi

export_csv_to_influx \
--csv test.csv \
--dbname test \
--measurement sample \
--tag_columns EntryType,Source,MachineName \
--field_columns EntryType,Source,EventID,MachineName,Message \
--time_column TimeGenerated \
--user admin \
--passw