Alex-Kopylov

dvc list -R --dvc-only ./

Alex-Kopylov

xset r rate 300 50

Alex-Kopylov

sudo pacman -S pulseaudio-alsa

Alex-Kopylov

def resumetable(df):
    print(f"Dataset Shape: {df.shape}")
    summary = pd.DataFrame(df.dtypes,columns=['dtypes'])
    summary = summary.reset_index()
    summary['Name'] = summary['index']
    summary = summary[['Name','dtypes']]
    summary['Missing'] = df.isnull().sum().values    
    summary['Uniques'] = df.nunique().values
    summary['First Value'] = df.loc[0].values
    summary['Second Value'] = df.loc[1].values

Alex-Kopylov

import matplotlib.pyplot as plt
import numpy as np

def show_images(images, cols = 1, titles = None):
    """Display a list of images in a single figure with matplotlib.
    
    Parameters
    ---------
    images: List of np.arrays compatible with plt.imshow.
    

Alex-Kopylov

def getSymbolBeforeDigit(x):
  for i, c in enumerate(x):
    if c.isdigit(): 
      return x[i-1]
pd.to_numeric(data['Толщина_перед_смоткой'].apply(lambda x: x.split(getSymbolBeforeDigit(x))[1].replace(',','.')))

Alex-Kopylov

import time
import hashlib

t1 = time.time()

train_hashes = [hashlib.sha1(x).digest() for x in train_dataset]
valid_hashes = [hashlib.sha1(x).digest() for x in valid_dataset]
test_hashes  = [hashlib.sha1(x).digest() for x in test_dataset]

valid_in_train = np.in1d(valid_hashes, train_hashes)

Alex-Kopylov

def randomize(dataset, labels):
  permutation = np.random.permutation(labels.shape[0])
  shuffled_dataset = dataset[permutation,:,:]
  shuffled_labels = labels[permutation]
  return shuffled_dataset, shuffled_labels
train_dataset, train_labels = randomize(train_dataset, train_labels)
test_dataset, test_labels = randomize(test_dataset, test_labels)
valid_dataset, valid_labels = randomize(valid_dataset, valid_labels)