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Refactor: reduce the read-in loop in sts_line #6148

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Merged
merged 1 commit into from
Apr 14, 2025
Merged

Refactor: reduce the read-in loop in sts_line #6148

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2 changes: 1 addition & 1 deletion tools/stm/plot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,7 +59,7 @@
start_points = [0, 0, 8]
end_points = [2, 0, 8]
distance = np.linalg.norm(np.array(end_points) - np.array(start_points))
biases, points, dIdV_map = stm.line_sts(biasstart, biasend, biasstep, start_points, end_points, 50)
biases, points, current, dIdV_map = stm.line_sts(biasstart, biasend, biasstep, start_points, end_points, 50)

plt.figure(figsize=(10, 6), dpi=150)

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18 changes: 12 additions & 6 deletions tools/stm/stm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -156,8 +156,6 @@ def linescan(self, bias, current, p1, p2, npoints=50, z0=None):
def pointcurrent(self, bias, x, y, z):
"""Current for a single x, y, z position for a given bias."""

self.read_ldos(bias)

nx = self.ldos.shape[0]
ny = self.ldos.shape[1]
nz = self.ldos.shape[2]
Expand Down Expand Up @@ -193,6 +191,7 @@ def sts(self, x, y, z, bias0, bias1, biasstep):

for b in np.arange(len(biases)):
print(b, biases[b])
self.read_ldos(biases[b])
current[b] = self.pointcurrent(biases[b], x, y, z)

dIdV = np.gradient(current, biasstep)
Expand All @@ -209,14 +208,21 @@ def line_sts(self, bias0, bias1, biasstep, p1, p2, npoints=50):
d = p2 - p1
s = np.dot(d, d)**0.5
biases = np.arange(bias0, bias1 + biasstep, biasstep)
current = np.zeros((npoints, len(biases)))

dIdV = np.zeros((npoints, len(biases)))
for b in np.arange(len(biases)):
print(b, biases[b])
self.read_ldos(biases[b])

for i in range(npoints):
x, y, z = p1 + i * d / (npoints - 1)
current[i, b] = self.pointcurrent(biases[b], x, y, z)

dIdV = np.zeros((npoints, len(biases)))
for i in range(npoints):
x, y, z = p1 + i * d / (npoints - 1)
biases, current, dIdV[i, :] = self.sts(x, y, z, bias0, bias1, biasstep)
dIdV[i, :] = np.gradient(current[i, :], biasstep)

return biases, np.linspace(0, s, npoints), dIdV
return biases, np.linspace(0, s, npoints), current, dIdV


def find_current(self, ldos, z):
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