kmc.electrodes[cf.Q] = Q[k] * V_high
kmc.update_V()
kmc.simulate_discrete(prehops=500, hops=5000)
output[k] = kmc.current[cf.output]
outputArray[i, j] = output
fitness += cf.Fitness(output, cf.target)
genePool.fitness[j] = fitness / avg
fitnessArray[i, j] = genePool.fitness[j]
# Status print
print("Generation nr. " + str(i + 1) + " completed")
print("Highest fitness: " + str(max(genePool.fitness)))
# Evolve to the next generation
genePool.NextGen()
# Save experiment
filepath = SaveLib.createSaveDirectory(cf.filepath, cf.name)
SaveLib.saveExperiment(filepath,
geneArray=geneArray,
fitnessArray=fitnessArray,
outputArray=outputArray,
target=cf.target,
P=P,
Q=Q)
domain = kmc_dn_utils.visualize_basic(kmc)
plt.figure()
plt.plot(output)
plt.show()
w = cf.InputGen()[3] # Weight array
target = cf.TargetGen()[1] # Target signal
# np arrays to save genePools, outputs and fitness
geneArray = np.zeros((cf.generations, cf.genomes, cf.genes))
outputArray = np.zeros((cf.generations, cf.genomes, len(x[0])))
fitnessArray = np.zeros((cf.generations, cf.genomes))
# Temporary arrays, overwritten each generation
fitnessTemp = np.zeros((cf.genomes, cf.fitnessavg))
outputAvg = np.zeros((cf.fitnessavg, len(x[0])))
outputTemp = np.zeros((cf.genomes, len(x[0])))
controlVoltages = np.zeros(cf.genes)
# Initialize save directory
saveDirectory = SaveLib.createSaveDirectory(cf.filepath, cf.name)
# Initialize main figure
mainFig = PlotBuilder.initMainFigEvolution(cf.genes, cf.generations, cf.genelabels, cf.generange)
# Initialize instruments
ivvi = InstrumentImporter.IVVIrack.initInstrument()
# Initialize genepool
genePool = Evolution.GenePool(cf)
#%% Measurement loop
for i in range(cf.generations):
for j in range(cf.genomes):
# Set the DAC voltages
w = cf.InputGen()[3] # Weight array
target = cf.TargetGen()[1] # Target signal
# np arrays to save genePools, outputs and fitness
geneArray = np.zeros((cf.generations, cf.genomes, cf.genes))
outputArray = np.zeros((cf.generations, cf.genomes, len(x[0])))
fitnessArray = np.zeros((cf.generations, cf.genomes))
# Temporary arrays, overwritten each generation
fitnessTemp = np.zeros((cf.genomes, cf.fitnessavg))
outputAvg = np.zeros((cf.fitnessavg, len(x[0])))
outputTemp = np.zeros((cf.genomes, len(x[0])))
controlVoltages = np.zeros(cf.genes)
# Initialize save directory
saveDirectory = SaveLib.createSaveDirectory(cf.filepath, cf.name)
# Initialize main figure
mainFig = PlotBuilder.initMainFigEvolution(cf.genes, cf.generations,
cf.genelabels, cf.generange)
# Initialize NN
main_dir = r'../../test/NN_test/data4nn/Data_for_testing/'
dtype = torch.cuda.FloatTensor
net = staNNet(main_dir + 'TEST_NN.pt')
# Initialize genepool
genePool = Evolution.GenePool(cf)
#%% Measurement loop
# Update constant quantities that depend on I_0 and ab
kmc.calc_E_constant()
kmc.calc_transitions_constant()
# Define input signals
P = [0, 1, 0, 1]
Q = [0, 0, 1, 1]
w = [1, 1, 1, 1]
kmc.electrodes[cf.output, 3] = 0
# Initialize arrays to save experiment
geneArray = np.zeros((cf.generations, cf.genomes, cf.genes))
currentArray = np.zeros((cf.generations, cf.genomes, 8, 4 * cf.avg))
voltageArray = np.zeros((cf.generations, cf.genomes, 8, 4 * cf.avg))
fitnessArray = np.zeros((cf.generations, cf.genomes))
filepath = SaveLib.createSaveDirectory(cf.filepath, cf.name)
# Save experiment (also copies files)
SaveLib.saveExperiment(filepath,
geneArray=geneArray,
fitnessArray=fitnessArray,
currentArray=currentArray,
voltageArray=voltageArray,
target=cf.target,
P=P,
Q=Q)
for i in range(cf.generations):
geneArray[i] = genePool.pool
for j in range(cf.genomes):
if (i == 0 and j == 1):
tic = time.time()
import sys
# Initialize config object
cf = config.experiment_config()
# Construct configuration array
voltages = grid(cf.electrodes, cf.voltageGrid)
voltages = voltages[:, ::-1]
print('First two indices are inputs, rest CV. Fastest CV has the last index!')
# Init data container
data = np.zeros((voltages.shape[0], voltages.shape[1] + cf.samples))
data[:, :voltages.shape[1]] = voltages
# initialize save directory
saveDirectory = SaveLib.createSaveDirectory(cf.filepath, cf.name)
# Initialize instruments
ivvi = InstrumentImporter.IVVIrack.initInstrument(dac_step=500,
dac_delay=0.001)
nr_blocks = len(cf.input1) * len(cf.input2)
blockSize = int(len(voltages) / nr_blocks)
assert len(
voltages
) == blockSize * nr_blocks, 'Nr of gridpoints not divisible by nr_blocks!!'
#main acquisition loop
for j in range(nr_blocks):
print('Getting Data for block ' + str(j) + '...')
start_block = time.time()
InstrumentImporter.IVVIrack.setControlVoltages(ivvi,
import SkyNEt.modules.Evolution as Evolution
import SkyNEt.modules.SaveLib as SaveLib
import kmc_dopant_networks as kmc_dn
import kmc_dopant_networks_utils as kmc_dn_utils
import numpy as np
import matplotlib.pyplot as plt
import config_single_shot as config
import time
cf = config.experiment_config()
saveDirectory = SaveLib.createSaveDirectory(cf.filepath, cf.name)
#%% System setup
xdim = 1
ydim = 1
# Load layouts
acceptor_layouts = np.load('acceptor_layouts.npy')
donor_layouts = np.load('donor_layouts.npy')
# Define 8 electrodes
electrodes = np.zeros((8, 4))
electrodes[0] = [0, ydim / 4, 0, 0]
electrodes[1] = [0, 3 * ydim / 4, 0, 0]
electrodes[2] = [xdim, ydim / 4, 0, 10]
electrodes[3] = [xdim, 3 * ydim / 4, 0, 0]
electrodes[4] = [xdim / 4, 0, 0, 0]
electrodes[5] = [3 * xdim / 4, 0, 0, 0]
electrodes[6] = [xdim / 4, ydim, 0, 0]
electrodes[7] = [3 * xdim / 4, ydim, 0, 0]
import SkyNEt.modules.Evolution as Evolution
import SkyNEt.modules.SaveLib as SaveLib
import kmc_dopant_networks as kmc_dn
import kmc_dopant_networks_utils as kmc_dn_utils
import numpy as np
import matplotlib.pyplot as plt
import config_temperature_dependence as config
import time
cf = config.experiment_config()
saveDirectory = SaveLib.createSaveDirectory(cf.filepath, cf.name)
#%% System setup
xdim = 1
ydim = 1
# Load layouts
acceptor_layouts = np.load('acceptor_layouts.npy')
donor_layouts = np.load('donor_layouts.npy')
# Define 8 electrodes
electrodes = np.zeros((2, 4))
electrodes[0] = [0, ydim / 2, 0, 0]
electrodes[1] = [1, ydim / 2, 0, 0]
kmc = kmc_dn.kmc_dn(1, 0, xdim, ydim, 0, electrodes=electrodes)
kmc.load_acceptors(acceptor_layouts[cf.layout])
kmc.load_donors(donor_layouts[cf.layout])
# Set parameters
import SkyNEt.modules.SaveLib as SaveLib
import matplotlib.pyplot as plt
from SkyNEt.instruments import InstrumentImporter
import numpy as np
import os
import config_IV as config
# Load the information from the config class.
config = config.experiment_config()
# Initialize save directory.
saveDirectory = SaveLib.createSaveDirectory(config.filepath, config.name)
# Define the device input using the function in the config class.
Input = config.Sweepgen(config.v_high, config.v_low, config.n_points,
config.direction)
# Measure using the device specified in the config class.
if config.device == 'nidaq':
Output = InstrumentImporter.nidaqIO.IO(Input, config.fs)
elif config.device == 'adwin':
adwin = InstrumentImporter.adwinIO.InitInstrument()
Output = InstrumentImporter.adwinIO.IO(adwin, Input, config.fs)
else:
print('specify measurement device')
# Save the Input and Output
SaveLib.saveExperiment(saveDirectory, input=Input, output=Output)
# Plot the IV curve.
plt.figure()
import SkyNEt.modules.Evolution as Evolution
import SkyNEt.modules.SaveLib as SaveLib
import kmc_dopant_networks as kmc_dn
import kmc_dopant_networks_utils as kmc_dn_utils
import numpy as np
import matplotlib.pyplot as plt
import config_IV as config
cf = config.experiment_config()
saveDirectory = SaveLib.createSaveDirectory(cf.filepath, cf.name)
#%% System setup
xdim = 1
ydim = 1
layout = 0
# Load layouts
acceptor_layouts = np.load('acceptor_layouts.npy')
donor_layouts = np.load('donor_layouts.npy')
# Define 8 electrodes
electrodes = np.zeros((8, 4))
electrodes[0] = [0, ydim / 4, 0, 0]
electrodes[1] = [0, 3 * ydim / 4, 0, 0]
electrodes[2] = [xdim, ydim / 4, 0, 10]
electrodes[3] = [xdim, 3 * ydim / 4, 0, 0]
electrodes[4] = [xdim / 4, 0, 0, 0]
electrodes[5] = [3 * xdim / 4, 0, 0, 0]
electrodes[6] = [xdim / 4, ydim, 0, 0]
electrodes[7] = [3 * xdim / 4, ydim, 0, 0]
import SkyNEt.modules.Evolution as Evolution
import SkyNEt.modules.SaveLib as SaveLib
import kmc_dopant_networks as kmc_dn
import kmc_dopant_networks_utils as kmc_dn_utils
import numpy as np
import matplotlib.pyplot as plt
import config_single_shot as config
import time as timelib
cf = config.experiment_config()
saveDirectory = SaveLib.createSaveDirectory(cf.filepath, cf.name)
#%% System setup
xdim = 1
ydim = 1
layout = 0
# Load layouts
acceptor_layouts = np.load('acceptor_layouts.npy')
donor_layouts = np.load('donor_layouts.npy')
# Define 8 electrodes
electrodes = np.zeros((8, 4))
electrodes[0] = [0, ydim / 4, 0, 0]
electrodes[1] = [0, 3 * ydim / 4, 0, 0]
electrodes[2] = [xdim, ydim / 4, 0, 10]
electrodes[3] = [xdim, 3 * ydim / 4, 0, 0]
electrodes[4] = [xdim / 4, 0, 0, 0]
electrodes[5] = [3 * xdim / 4, 0, 0, 0]
electrodes[6] = [xdim / 4, ydim, 0, 0]
input1 = [-900, 0, 900]
voltageGrid = [*controlVoltages, input2, input1]
electrodes = len(voltageGrid) #amount of electrodes
acqTime = 0.01
samples = 50
#construct configuration array
voltages = grid(electrodes, voltageGrid)
voltages = voltages[:, ::-1]
print('First two indices are inputs, rest CV. Fastest CV has the last index!')
# init data container
data = np.zeros((voltages.shape[0], voltages.shape[1] + samples))
data[:, :voltages.shape[1]] = voltages
# initialize save directory
saveDirectory = SaveLib.createSaveDirectory(filepath, name)
# initialize instruments
ivvi = IVVIrack.initInstrument(dac_step=500, dac_delay=0.001)
nr_blocks = len(input1) * len(input2)
blockSize = int(len(voltages) / nr_blocks)
assert len(
voltages
) == blockSize * nr_blocks, 'Nr of gridpoints not divisible by nr_blocks!!'
#main acquisition loop
for j in range(nr_blocks):
print('Getting Data for block ' + str(j) + '...')
start_block = time.time()
IVVIrack.setControlVoltages(ivvi, voltages[j * blockSize, :])
time.sleep(1) #extra delay to account for changing the input voltages
for i in range(blockSize):
# Initialize data array
outputs = np.zeros((len(cf.layouts), len(cf.voltagelist)))
# Load layouts and target
acceptor_layouts = np.load('acceptor_layouts.npy')
donor_layouts = np.load('donor_layouts.npy')
voltagelist = cf.voltagelist
# Define 2 electrodes
electrodes = np.zeros((2, 4))
electrodes[0] = [0, ydim / 2, 0, 0]
electrodes[1] = [1, ydim / 2, 0, 0]
# Initialize arrays to save experiment
filepath = SaveLib.createSaveDirectory(cf.filepath, cf.name)
os.makedirs(filepath + '/kmc_objects')
for ii in range(len(cf.layouts)):
layout = cf.layouts[ii]
# Initialize kmc
if (cf.use_random_layout):
kmc = kmc_dn.kmc_dn(cf.layoutsize,
cf.layoutsize // 10,
xdim,
ydim,
0,
electrodes=electrodes)
else:
kmc = kmc_dn.kmc_dn(1, 0, xdim, ydim, 0, electrodes=electrodes)
kmc.load_acceptors(acceptor_layouts[layout])
# Initialize kmc
kmc = kmc_dn.kmc_dn(1, 0, xdim, ydim, 0, electrodes=electrodes)
kmc.load_acceptors(acceptor_layouts[layout])
kmc.load_donors(donor_layouts[layout])
# Parameters
kT = cf.kT
prehops = cf.prehops
hops = cf.hops
kmc.kT = kT
# Initialize arrays to save experiment
geneArray = np.zeros((cf.generations, cf.genomes, cf.genes))
outputArray = np.zeros((cf.generations, cf.genomes, len(voltagelist)))
fitnessArray = np.zeros((cf.generations, cf.genomes))
filepath = SaveLib.createSaveDirectory(cf.filepath, cf.name)
# Save experiment (also copies files)
SaveLib.saveExperiment(
filepath,
geneArray=geneArray,
fitnessArray=fitnessArray,
outputArray=outputArray,
voltagelist=voltagelist,
target=target,
)
for i in range(cf.generations):
geneArray[i] = genePool.pool
for j in range(cf.genomes):
# Time estimation
