wiccy46

# Find python path
import os
import sys
os.path.dirname(sys.executable)

# Abs path of project:
os.path.dirname(os.path.abspath(__file__))

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conda create -n yourenvname python=x.x anaconda

conda remove --name myenv --all

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Terminal: conda install -c conda-forge jupyter_contrib_nbextensions conda install -c conda-forge jupyter_nbextensions_configuratorj

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for i in value_in_dB:
	print pow (10, float(i)/20)

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import time

def timeit(method):
    def timed(*args, **kw):
        ts = time.time()
        result = method(*args, **kw)
        te = time.time()
        if 'log_time' in kw:
            name = kw.get('log_name', method.__name__.upper())
            kw['log_time'][name] = int((te - ts) * 1000)

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def get_all_data(fp):
    l = os.listdir(fp)
    try: l.remove(".DS_Store") 
    except: pass
    for i, fname in enumerate(l):
        temp_df = pd.read_csv(fp + fname)
        if (i == 0):
            r = temp_df
        else:
            r = r.append(temp_df)

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from PyQt5.QtGui import QPainter, QPen, QFont
from PyQt5.QtWidgets import QAbstractButton, QSlider, QWidget, QVBoxLayout, QHBoxLayout,\
    QStyleOptionSlider, QStyle
from PyQt5.QtCore import Qt, QRect, QPoint
import numpy as np

class LabeledSlider(QWidget):
    def __init__(self, minimum, maximum, interval=1, orientation=Qt.Horizontal,
            labels=None, p0=0, parent=None):

wiccy46

To rename a tab where you are : $psise.CurrentPowerShellTab.DisplayName = 'Dev'

To rename a remote tab, you need to do that from a local one (where the first tab is [0] ): $psise.PowerShellTabs[1].DisplayName = 'Remote-Server01'

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def mse(imageA, imageB):
    # the 'Mean Squared Error' between the two images is the
    # sum of the squared difference between the two images;
    # NOTE: the two images must have the same dimension
    err = np.sum((imageA - imageB) ** 2)
    err /= float(imageA.shape[0] * imageA.shape[1])
    # return the MSE, the lower the error, the more "similar"
    # the two images are
    return err

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"""1: Peak Detection"""

def envfol_peak_detection(sig, sr, chunk=4, order=6, lpfreq=150):
    """Envelope follower based on peak detection"""
    s = sig.shape[0] // chunk
    new_sig = np.array_split(np.abs(sig), s)
    result = []
    for i in new_sig:
        result.append(np.max(i))
    result = np.array(result)