jponf

# -*- coding: utf-8 -*-

"""Stack tracer for multi-threaded applications.

This code is a copy of https://pypi.python.org/pypi/stacktracer/0.1.2
with minor modifications.


Usage:

jponf

# -*- coding: utf-8 -*-

import numpy as np

import sklearn.utils

from scipy.stats import anderson, kstest, normaltest, shapiro
from sklearn.cluster import KMeans

jponf

import tensorflow as tf
import math

class WarmupCosineDecayLRScheduler(
  tf.keras.optimizers.schedules.LearningRateSchedule):

    def __init__(self, 
                 max_lr: float,
                 warmup_steps: int,
                 decay_steps: int,

jponf

// Open browser JS console and Copy&Paste the following code
function ConnectButton(){
    console.log("Connect pushed"); 
    document.querySelector("#top-toolbar > colab-connect-button").shadowRoot.querySelector("#connect").click() 
}
setInterval(ConnectButton, 300000);

jponf

def aitken_interpolation(x, y):
  if len(x) != len(y):
    raise ValueError()
  
  # Constants
  x_poly = np.polynomial.Polynomial([0, 1])
  
  # Initialize algorithm
  n = len(x)
  p = [np.polynomial.Polynomial([y[0]])]

jponf

import numpy as np

# `data` is expected to be a numpy array
def filter_outliers_iqr(data, iqr_factor=1.5):
    quartile_1, quartile_3 = np.percentile(data, (25, 75))
    iqr = quartile_3 - quartile_1
    lw_bound = quartile_1 - (iqr * iqr_factor)
    up_bound = quartile_3 + (iqr * iqr_factor)

    return data[data >= lw_bound & data <= up_bound]