Often, you want the user to choose n options (where n is small-ish) from a very large (hundreds or thousands) number of possibilities. Good UX around this dictates that the user should be able to search for the options they want.
This gist puts together a minimal example of binding a search field with multiple checkboxes using ipywidgets.
| def openfile_dialog(): | |
| from PyQt5 import QtGui | |
| from PyQt5 import QtGui, QtWidgets | |
| app = QtWidgets.QApplication([dir]) | |
| fname = QtWidgets.QFileDialog.getOpenFileName(None, "Select a file...", '.', filter="All files (*)") | |
| return str(fname) |
| import numpy as np | |
| import pylab as pl | |
| from numpy import fft | |
| def fourierExtrapolation(x, n_predict): | |
| n = x.size | |
| n_harm = 10 # number of harmonics in model | |
| t = np.arange(0, n) | |
| p = np.polyfit(t, x, 1) # find linear trend in x | |
| x_notrend = x - p[0] * t # detrended x |
| __all__ = ( | |
| ####### Class Objects | |
| #CoGetClassObject - Normal, not wrapped | |
| 'CoDllGetClassObject', #Get ClassObject from a DLL file | |
| ####### ClassFactory::CreateInstance Wrappers | |
| 'CoCreateInstanceFromFactory', #Create an object via IClassFactory::CreateInstance | |
| 'CoCreateInstanceFromFactoryLicenced', #Create a licenced object via IClassFactory2::CreateInstanceLic |
This configuration worked for me, hope it helps
It is based on: https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b
and on: https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support
