SuperShinyEyes

#!/usr/bin/env python
#
# Very basic example of using Python and IMAP to iterate over emails in a
# gmail folder/label.  This code is released into the public domain.
#
# RKI July 2013
# http://www.voidynullness.net/blog/2013/07/25/gmail-email-with-python-via-imap/
#
import sys
import imaplib

SuperShinyEyes

import matplotlib.pyplot as plt
import soundfile as sf
import librosa
import librosa.display

plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.serif'] = 'Ubuntu'
plt.rcParams['font.monospace'] = 'Ubuntu Mono'
plt.rcParams['font.size'] = 10
plt.rcParams['axes.labelsize'] = 10   # Time and Hz, i.e. labels

SuperShinyEyes

import matplotlib.pyplot as plt
import soundfile as sf
import librosa

plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.serif'] = 'Ubuntu'
plt.rcParams['font.monospace'] = 'Ubuntu Mono'
plt.rcParams['font.size'] = 10
plt.rcParams['axes.labelsize'] = 10   # Time and Hz, i.e. labels
plt.rcParams['axes.labelweight'] = 'bold'

SuperShinyEyes

import tensorflow as tf
from time import time

start = time()

mnist = tf.keras.datasets.mnist

(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

SuperShinyEyes

FROM nvidia/cuda:9.0-base-ubuntu16.04

LABEL maintainer="Seyoung Park <[email protected]>"

# This Dockerfile is forked from Tensorflow Dockerfile

# Pick up some PyTorch gpu dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
        build-essential \
        cuda-command-line-tools-9-0 \

SuperShinyEyes

name: how-bots-type
channels:
  - pytorch
  - defaults
dependencies:
  - click=7.0
  - ffmpeg=4.0
  - ipython=7.2
  - jupyterlab=0.35
  - matplotlib=3.0

SuperShinyEyes

#----------------------------------------------------------
# Remove local uncommited changes 
# https://docs.gitlab.com/ee/topics/git/numerous_undo_possibilities_in_git/
git reset --hard

#----------------------------------------------------------
# Fetch
# https://www.atlassian.com/git/tutorials/syncing/git-fetch
git fetch origin master

SuperShinyEyes

def shelving(ys, cut_off, gain, mode='low'):
    '''Shelving filter for bass
    
    Args:
        ys (numpy.array): 1D signals
        cut_off (float): Normalized cut-off frequency. 0 < cut_off < 1
        gain (float): gain in dB
    '''
    gain 		= 10 ** (gain / 20)          # NOTE: is it 20 or 40?
    wc 			= 2 * np.pi * cut_off / 44100  # cut_off frequency in radians(0 <= wc <= pi)

SuperShinyEyes

import numpy as np
from scipy import constants


def fibonacci(n):
    """Calculate fibonacci system in signal processing way; weighted sum of fundamental modes.
    The complexity: O(1).
    """
    p = constants.golden
    return int(np.around(

SuperShinyEyes

class EasyDict(dict):
    def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs)
    def __getattr__(self, name): return self[name]
    def __setattr__(self, name, value): self[name] = value
    def __delattr__(self, name): del self[name]