def test_value(self):
a = np.array([1, 2, 3, 4])
b = Value.array_like(array=a, unit=ureg.amp)
print(b[0])
a = np.array([[1, 2, 3, 4], [1, 2, 3, 4]])
b = Value.array_like(array=a, unit=ureg.amp)
print(b[0][0])
f = Field(field='voltage', name='nothing')
print(f)
a = Value(value=3.0,
unit=ureg.amp,
name='input_voltage',
tf_shape=(None, 1))
c = 1 / a
array = np.array([a, a, a], dtype=object)
b = Value(value=2.0, unit=ureg.volt * ureg.volt, name='input_current')
d = ureg.amp * array
r = array * b
f = b * array
boo = r == f
tmep = 1.0 * ureg.volt
f = 2.0 * ureg.microvolt
temp = tmep + f
temp = tmep.to_reduced_units()
d = a * 2.0
f = 2.0 * a
c = 1.0
r = 1.0 * ureg.volt
t = ureg.volt * 1.0
d = a == b
r = a.tensor
d = 5
def test_value(self):
# test the array_like function
a = np.array([1, 2, 3, 4])
b = Value.array_like(array=a, unit=ureg.amp)
self.assertEquals(Value(1, ureg.amp), b[0],
'Error in Value.array_like()')
a = np.array([[1, 2, 3, 4], [1, 2, 3, 4]])
b = Value.array_like(array=a, unit=ureg.amp)
self.assertEquals(Value(1, ureg.amp), b[0][0],
'Error in Value.array_like()')
# test math operations
a = Value(1, ureg.amp)
a_n = 1
b = Value(2, ureg.amp)
c = Value(3, ureg.amp)
d = Value(4, ureg.volt)
e = Value(2, ureg.ohm)
# test the add function
self.assertEqual(c, a + b, 'Error in Value.__add__()')
# test the subtract function
self.assertEqual(c - b, a, 'Error in Value.__sub__()')
# test the multiply function
self.assertEqual(d, b * e, 'Error in Value.__mul__()')
self.assertEqual(a, a * a_n, 'Error in Value.__mul__()')
# test the divide function
self.assertEqual(d / e, b, 'Error in Value.__truediv__()')
self.assertEqual(a, a / a_n, 'Error in Value.__truediv__()')
f = Field(field='voltage', name='nothing')
print(f)
a = Value(value=3.0,
unit=ureg.amp,
name='input_voltage',
tf_shape=(None, 1))
c = 1 / a
array = np.array([a, a, a], dtype=object)
b = Value(value=2.0, unit=ureg.volt * ureg.volt, name='input_current')
d = ureg.amp * array
r = array * b
f = b * array
boo = r == f
tmep = 1.0 * ureg.volt
f = 2.0 * ureg.microvolt
temp = tmep + f
temp = tmep.to_reduced_units()
d = a * 2.0
f = 2.0 * a
c = 1.0
r = 1.0 * ureg.volt
t = ureg.volt * 1.0
d = a == b
r = a.tensor
d = 5
def test_tlmextraction(self):
# path = '/home/connor/Documents/Stanford_Projects/Extractions/src/SampleData/FETExampleData/nano_patterning.csv'
# idvg_path = '/home/connor/Documents/Stanford_Projects/Extractions/fetextraction/SemiPy/SampleData/TLMExampleData'
idvg_path = '/home/connor/Documents/Stanford_Projects/Extractions/SemiPy/SampleData/TLMExampleDataShort'
# idvg_path = '/home/connor/Documents/Stanford_Projects/Extractions/fetextraction/SemiPy/SampleData/TLMExampleDataShort'
# idvd_path = '/home/connor/Documents/Stanford_Projects/Extractions/fetextraction/SemiPy/SampleData/FETExampleData/WSe2_Sample_4_Id_Vd.txt'
# idvg_path = '/home/connor/Documents/Stanford_Projects/Extractions/fetextraction/SemiPy/SampleData/FETExampleData/WSe2_Sample_4_Id_Vg.txt'
widths = Value(4.0, ureg.micrometer)
# lengths = Value.array_like(np.array([0.5, 1.0, 2.0, 2.5, 3.0, 3.5]), unit=ureg.micrometer)
lengths = Value.array_like(np.array([1.0, 0.5, 2.0]),
unit=ureg.micrometer)
tox = Value(90, ureg.nanometer)
result = TLMExtractor(widths=widths,
lengths=lengths,
tox=tox,
epiox=3.9,
device_polarity='n',
idvg_path=idvg_path,
vd_values=[1.0, 2.0])
result.save_tlm_plots()
a = 5
def __init__(self,
min_value,
max_value,
unit,
num=None,
step=None,
*args,
**kwargs):
assert num is not None or step is not None, 'You must give a step or num value'
if num is not None:
self.range = np.linspace(min_value, max_value, num)
elif step is not None:
self.range = np.arange(min_value, max_value, step)
self.range = Value.array_like(self.range, unit=unit)
def test_tlmextraction(self):
# Change these filepaths to match TLM data
idvd_path = get_abs_semipy_path(
'SampleData/TLMExampleData/WSe2_Sample_4_Id_Vd.txt') # unused
idvg_path = get_abs_semipy_path('SampleData/TLMExampleData')
widths = Value(4.0, ureg.micrometer)
lengths = Value.array_like(np.array([0.5, 1.0, 2.0, 2.5, 3.0, 3.5]),
unit=ureg.micrometer)
#lengths = Value.array_like(np.array([1.0, 2.0, 0.5]), unit=ureg.micrometer)
#lengths = Value.array_like(np.array([2.0, 0.5, 1.0]), unit=ureg.micrometer)
gate_oxide = SiO2(thickness=Value(30, ureg.nanometer))
channel = MoS2(layer_number=1)
result = TLMExtractor(widths=widths,
lengths=lengths,
gate_oxide=gate_oxide,
channel=channel,
FET_class=nTFT,
idvg_path=idvg_path,
vd_values=[1.0, 2.0],
substrate=Silicon())
result.save_tlm_plots()
import unittest
from SemiPy.Extractors.TLM.TLMExtractor import TLMExtractor
from SemiPy.Devices.Devices.FET.ThinFilmFET import nTFT
from SemiPy.Devices.Materials.Oxides.MetalOxides import SiO2
from SemiPy.Devices.Materials.Semiconductors.BulkSemiconductors import Silicon
from SemiPy.Devices.Materials.TwoDMaterials.TMD import MoS2
from SemiPy.helper.paths import get_abs_semipy_path
from physics.value import Value, ureg
import numpy as np
idvd_path = get_abs_semipy_path(
'SampleData/TLMExampleData/WSe2_Sample_4_Id_Vd.txt') # unused
idvg_path = get_abs_semipy_path('SampleData/TLMExampleData')
widths = Value(4.0, ureg.micrometer)
lengths = Value.array_like(np.array([0.5, 1.0, 2.0, 2.5, 3.0, 3.5]),
unit=ureg.micrometer)
gate_oxide = SiO2(thickness=Value(30, ureg.nanometer))
channel = MoS2(layer_number=1)
result = TLMExtractor(widths=widths,
lengths=lengths,
gate_oxide=gate_oxide,
channel=channel,
FET_class=nTFT,
idvg_path=idvg_path,
vd_values=[1.0, 2.0],
substrate=Silicon())
result.save_tlm_plots()
def __extract_data(self):
"""
Extract the properties of the FET given the available data, including transconductance (gm), subthreshold swing (ss), field-effect
mobility (mufe), threshold voltage (vt), max on current (max_Ion), min off current at max Ion Vd (min_Ioff),
Returns:
None
"""
print('starting extraction')
# now compute the vt and gm using the max Vd
vd = self.idvg.get_secondary_indep_values()
# adjust the shape to be [num_set, 1]
vd = Value.array_like(np.expand_dims(np.array(vd), axis=-1),
unit=ureg.volt)
max_vd = max(vd)
vg = self.idvg.get_column('vg')
max_vg = self.FET.max_value(vg)
# get the max and min Ion
ion = self.idvg.get_column('id')
max_ion, max_ion_i = self.FET.max_value(ion, return_index=True)
max_ion_vd = vd[max_ion_i[0], 0]
max_ion_vg = vg[max_ion_i]
self.FET.max_Ion.set(value=max_ion,
input_values={
'Vg': max_ion_vg,
'Vd': max_ion_vd
})
# compute the gm
gm_fwd, max_gm_fwd, max_gm_fwd_i = self._extract_gm(fwd=True,
return_max=True)
gm_bwd, max_gm_bwd, max_gm_bwd_i = self._extract_gm(bwd=True,
return_max=True)
gm = np.concatenate((gm_fwd, gm_bwd), axis=-1)
self.idvg.add_column(column_name='gm', column_data=gm)
max_gm, max_gm_i = self.FET.max_slope_value(
self.idvg.get_column(column_name='gm'), return_index=True)
max_gm_vd = vd[max_gm_i[0], 0]
max_gm_input_values = {
'Vg': self.idvg.get_column_set('vg', max_gm_vd)[max_gm_i[-1]],
'Vd': max_gm_vd
}
self.FET.max_gm.set(max_gm, max_gm_input_values)
# print('set gm')
# Now extract the Vt values
vt_fwd = self._extract_vt(index=max_gm_fwd_i,
max_gm=max_gm_fwd,
fwd=True)
vt_bwd = self._extract_vt(index=max_gm_bwd_i,
max_gm=max_gm_bwd,
bwd=True)
self.FET.Vt_fwd.set(vt_fwd)
self.FET.Vt_bwd.set(vt_bwd)
# compute the ss
ss = self._slope(y_data=self.idvg.get_column('vg'),
x_data=np.log10(self.idvg.get_column('id')),
keep_dims=True)
self.idvg.add_column(column_name='ss', column_data=ss)
self.FET.min_ss = ss
# print('computing properties')
self.FET.compute_properties()
# print('adjusting n')
# now compute the carrier density
n = self.FET.vg_to_n(self.idvg.get_column('vg'))
self.idvg.add_column('n', n)
# print('adding r')
# now compute the resistance
r = vd / self.idvg.get_column('id')
self.idvg.add_column('resistance', r)
def _plot_line(self, x_min, x_max, a, b):
x_data = Value.array_like(array=np.linspace(x_min, x_max),
unit=x_min.unit)
y_data = x_data * a + b
plt.plot(x_data, y_data)
def _convert_to_value(unit):
# creates a lambda function for converting values to a unit
return lambda x: Value.array_like(x, unit=unit)
