Kautenja

Kautenja

"""This Python script counts words in a Markdown / LaTeX document(s).

Usage:
	python3 count_words.py <filename or directory>
	
It will ignore ATX headers, LaTeX & Markdown comments, and LaTeX markup tags.

TODO: inline HTML, Markdown images & tables
"""

Kautenja

class Array(object):
    """A list that indexes like an array [1...n] (for algorithm analysis)."""
    
    def __init__(self, items: list) -> None:
        """Create a new array from a list."""
        self.items = items
        
    def __repr__(self) -> str:
        """Return an executable string represention of `self`."""
        return '{}({})'.format(self.__class__.__name__, self.items)

Kautenja

"""A method to calculate the number of True/False Positive/Negative guesses."""
import numpy as np


def tpfp(predictions: np.ndarray,
         ground_truth: np.ndarray,
         negative: int=0.0,
         positive: int=1.0,
         normalize: bool=True) -> dict:
    """

Kautenja

"""A simple method wrapping around `confusion_matrix`."""


def confusion_dataframe(*args, **kwargs):
    """
    Generate an sklearn confusion matrix as a DataFrame.

    Args:
        *args: positional args for `confusion_matrix`
        **kwargs: keyword args for `confusion_matrix`

Kautenja

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd


def heatmap(data, 
    size_scale:int = 100, 
    figsize: tuple = (15, 12), 
    x_rotation: int = 270, 

Kautenja

"""An object to show a realtime plot of the value of a discrete line."""
from matplotlib import pyplot as plt
from matplotlib.ticker import MaxNLocator


class RealtimePlot(object):
    """A simple realtime plot to show the value of a discrete line."""

    def __init__(self, figsize: tuple=(4, 4)) -> None:
        """

Kautenja

"""An implementation of the Intersection over Union (IoU) metric for Keras."""
from keras import backend as K


def iou(y_true, y_pred, label: int):
    """
    Return the Intersection over Union (IoU) for a given label.

    Args:
        y_true: the expected y values as a one-hot

Kautenja

"""Methods to get the model name of GPUs used by TensorFlow."""
from tensorflow.python.client import device_lib


def get_device_model(device) -> str:
    """
    Return the model of a TensorFlow device.

    Args:
        device: the device to get the model name of

Kautenja

Compress

tar cf - <files> -P | pv -s $(du -sb <files> | awk '{print $1}') | gzip > <some .tar.gz file>

where:

• `` is the root-mounted (i.e. starts with /) path to the files