andersx

  
 $system
   mwords=250
 $end

 $contrl
   scftyp=rhf
   runtyp=energy
   local=ruednbrg
   mplevl=0

andersx

from __future__ import print_function

import os

import csv
import ast

from copy import deepcopy

import scipy

andersx

default-sample-format = float32le
default-sample-rate = 96000
alternate-sample-rate = 96000
default-sample-channels = 2
default-channel-map = front-left,front-right
default-fragments = 2
default-fragment-size-msec = 125
resample-method = speex-float-5
enable-lfe-remixing = no
high-priority = yes

andersx

def multiprocessing_func(pids, compounds_list, rd):

    for i in pids:
       rep_out = generate_fchl_acsf(
           compounds[i].nuclear_charges,
           compounds[i].coordinates,
           **rep_params)
       rd[i] = rep_out

manager = mp.Manager()

andersx

#!/usr/bin/env python3
from __future__ import print_function

import numpy as np
import qml
from qml.math import svd_solve
from time import time

from scipy.linalg import lstsq

andersx

#!/usr/bin/env python

from __future__ import print_function

import numpy as np

import qml
import qml.fchl

from qml.fchl import generate_representation

andersx

# MIT License
#
# Copyright (c) 2017 Anders Steen Christensen
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:

andersx

do i = 1, n

  partial(:) = get_partial(i)
  
  do j = 1, n
  
    k(j, i) = k(j, i) + dot_product(partial(:), deriv(:, j))
    
  enddo
  

andersx

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-396 nvidia-modprobe
sudo reboot now

#Test with
nvidia-smi

# Install Nvidia drivers from apt with Ubuntu 18.04
sudo ubuntu-drivers autoinstall

andersx

import numpy as np
import scipy


def kpca(K, n=2, centering=True):
    
    assert K.shape[0] == K.shape[1], "Square matrix required for Kernel PCA."
    assert np.allclose(K, K.T, atol=1e-8), "Symmetric matrix required for Kernel PCA."

    # First center kernel.