fsausset

from keras.models import Sequential
from keras.models import model_from_json
from keras import backend as K
import tensorflow as tf
from tensorflow.python.tools import freeze_graph
import os

# Load existing model.
with open("model.json",'r') as f:
    modelJSON = f.read()

samoshkin

bind -T root F12  \
  set prefix None \;\
  set key-table off \;\
  set status-style "fg=$color_status_text,bg=$color_window_off_status_bg" \;\
  set window-status-current-format "#[fg=$color_window_off_status_bg,bg=$color_window_off_status_current_bg]$separator_powerline_right#[default] #I:#W# #[fg=$color_window_off_status_current_bg,bg=$color_window_off_status_bg]$separator_powerline_right#[default]" \;\
  set window-status-current-style "fg=$color_dark,bold,bg=$color_window_off_status_current_bg" \;\
  if -F '#{pane_in_mode}' 'send-keys -X cancel' \;\
  refresh-client -S \;\

bind -T off F12 \

maidens

from __future__ import print_function, division

from math import sqrt

from scipy.special import ndtri

def _proportion_confidence_interval(r, n, z):
    """Compute confidence interval for a proportion.
    
    Follows notation described on pages 46--47 of [1].