Travis Niederhauser travis23

## find_index_of_first_nonzero_occurrence.py
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
    """

## sort_matched_arrays.py
# 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))

## remove_nonunique_times.py
indices = np.unique(time_arr.values, return_index=True)[1]
time_strict = time_arr.values[indices]
response_strict = response_arr.values[indices]

## change_tab_title.ipynb

      
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                travis23
                / change_tab_title.ipynb
            
            
              Created
              August 29, 2019 23:46
            
              
                [JupyterLab Change Tab Title] #jupyterlab
              
          
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## verify_path_exists.py
def verify_path_exists(path_):
    try:
        assert os.path.exists(path_)
    except (AssertionError,) as error:
        print()
        print('Path not found')
        print(path_)
        raise FileNotFoundError

## ranges_in_between_ranges.py
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

## read_csv.py
# 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

## create_data_directory.py
import os

import pendulum

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

## OpenJupyterLab.bat
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

## RunOnLoad.html
<head><script>
function initialize()
        /* Initialize the web page */
        {
            /* Do stuff */
        }
</script></head>

<body onload="initialize()">
	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
	"""
	# 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))
	indices = np.unique(time_arr.values, return_index=True)[1]
	time_strict = time_arr.values[indices]
	response_strict = response_arr.values[indices]
	def verify_path_exists(path_):
	try:
	assert os.path.exists(path_)
	except (AssertionError,) as error:
	print()
	print('Path not found')
	print(path_)
	raise FileNotFoundError
	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
	# 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
	import os

	import pendulum

	def create_data_directory(
	data_kind, # 'VolCal'
	data_source_id,
	timezone,
	parent_directory
	):
	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
	<head><script>
	function initialize()
	/* Initialize the web page */
	{
	/* Do stuff */
	}
	</script></head>

	<body onload="initialize()">