travis23

set root=C:\Users\user\Anaconda3

call %root%\Scripts\activate.bat %root%

call activate py37

call cd "C:\Users\TNiederhauser\Dropbox (Medic)\MedicData\Floor Scale"

call jupyter lab

travis23

import os

import pendulum

def create_data_directory(
        data_kind,  # 'VolCal'
        data_source_id,
        timezone,
        parent_directory
):

travis23

# See https://stackoverflow.com/questions/7894856/line-contains-null-byte-in-csv-reader-python

with open(path_to_csv_file) as f:
    reader = csv.reader((x.replace('\0', '') for x in f), delimiter=',')  # Handle null values
    while True:
        try:
            line = next(reader)
        except StopIteration:
            break
        print(line)  # process lines

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def create_logger(log_file_path, display_level, file_level):
    """
    Logs to file as well as to display.

    See https://www.dataquest.io/blog/advanced-jupyter-notebooks-tutorial/

    Args:
        log_file_path (str):
        display_level (int): logging.INFO for example
        file_level (int): logging.INFO for example

travis23

def get_ranges_in_between_ranges(df, start_name, stop_name):
    """
    Get range boundaries in between range boundaries arranged to be strictly increasing. 
    For example if we had three range boundaries where the range start and stop values
    are found in two separate columns in a dataframe, 
    
    start, stop
    -----------
     0,     5
     7,     8

travis23

travis23

# Sometimes timeseries need to be concatenated and then sorted so that the time vector is monotonic. 

# ---- Monotonic in x, but not strictly increasing
# ********************************************************************************
x1 = np.array([1, 2, 3, 4, 4])  # Not all of the values are unique
y1 = np.array([10, 20, 30, 42, 40])
x2 = np.array([1.5, 2.5, 3.5, 4.5])
y2 = np.array([15, 25, 35, 45])

x_ = np.concatenate((x1, x2))

travis23

import numpy as np

def find_index_of_first_nonzero_occurrence(array):
    """
    Find the index of the first non-zero occurrence in a numpy array.
    This is essentially a wrapper around np.flatnonzero(). If there are 
    no non-zero values None is returned. 
    
    array (numpy array): Should be 1d array and all elements should be numeric
    """

travis23

import matplotlib.pyplot as plt
from matplotlib import gridspec
import mplcursors

annotations0 = ['cat', 'dog', 'hare']
x = [1, 2, 3]
y = [0, 2.5, 3]

fontsize=20

travis23

import fnmatch

pattern = "aaa_*"  # Special characters '*' and '?'

list_of_all_files = ['aaa_1.json', 'a.json', 'b.json']

for filename in list_of_all_files:
    if fnmatch.fnmatch(filename, pattern):
        print(filename)