import warnings
import numpy as np
from .smooth import smooth_axis_monotone
[docs]class CannotSplitWarning(UserWarning):
pass
[docs]class IndentationPreprocessor(object):
[docs] @staticmethod
def apply(apret, preproc_names):
"""Perform force-distance preprocessing steps
Parameters
----------
apret: nanite.Indentation
The afm data to preprocess
preproc_names: list
A list of names for static methods in
`IndentationPreprocessor` that will be
applied (in the order given).
Notes
-----
This method is usually called from within the `Indentation`
class instance. If you are using this class directly and
apply it more than once, you might need to call
`apret.reset()` before preprocessing a second time.
"""
for mm in preproc_names:
if hasattr(IndentationPreprocessor, mm):
meth = getattr(IndentationPreprocessor, mm)
meth(apret)
else:
msg = "The preprocessing method '{}' does not exist!"
raise KeyError(msg.format(mm))
[docs] @staticmethod
def available():
"""List available preprocessor names"""
ignore = ["available", "apply"]
funcs = IndentationPreprocessor.__dict__
av = []
for ff in funcs:
if (not ff.startswith("_")
and ff not in ignore
and isinstance(funcs[ff], staticmethod)):
av.append(ff)
return sorted(av)
[docs] @staticmethod
def compute_tip_position(apret):
"""Compute the tip-sample separation
This computation correctly reproduces the column
"Vertical Tip Position" as it is exported by the
JPK analysis software with the checked option
"Use Unsmoothed Height".
"""
has_hm = "height (measured)" in apret
has_fo = "force" in apret
has_sc = "spring constant" in apret.metadata
if "tip position" in apret:
# nothing to do
pass
elif has_hm and has_fo and has_sc:
k = apret.metadata["spring constant"]
force = apret["force"]
zcant = apret["height (measured)"]
apret.data["tip position"] = zcant + force/k
else:
missing = []
if not has_hm:
missing.append("missing data column 'height (measured)'")
if not has_fo:
missing.append("missing data column 'force'")
if not has_sc:
missing.append("missing metadata 'spring constant'")
mt = ", ".join(missing)
raise ValueError("Cannot compute tip position: {}".format(mt))
[docs] @staticmethod
def correct_force_offset(apret):
"""Correct the force offset with an average baseline value
"""
idp = apret.estimate_contact_point_index()
if idp:
apret.data["force"] -= np.average(apret.data["force"][:idp])
else:
apret.data["force"] -= apret.data["force"][0]
[docs] @staticmethod
def correct_tip_offset(apret):
"""Correct the offset of the tip position
An estimate of the tip position is used to compute the
contact point.
"""
cpid = apret.estimate_contact_point_index()
apret.data["tip position"] -= apret.data["tip position"][cpid]
[docs] @staticmethod
def correct_split_approach_retract(apret):
"""Split the approach and retract curves (farthest point method)
Approach and retract curves are defined by the microscope. When the
direction of piezo movement is flipped, the force at the sample tip
is still increasing. This can be either due to a time lag in the AFM
system or due to a residual force acting on the sample due to the
bent cantilever.
To repair this time lag, we append parts of the retract curve to the
approach curve, such that the curves are split at the minimum height.
"""
x = np.array(apret.data["tip position"], copy=True)
y = np.array(apret.data["force"], copy=True)
idp = apret.estimate_contact_point_index()
if idp:
# Flip and normalize tip position so that maximum is at minimum
# z-position (set to 1) which coincides with maximum indentation.
x -= x[idp]
x /= x.min()
x[x < 0] = 0
# Flip and normalize force so that maximum force is set to 1.
y -= np.average(y[:idp])
y /= y.max()
y[y < np.std(y[:idp])] = 0
idmin = np.argmax(x**2+y**2)
segment = np.zeros(len(apret.data), dtype=bool)
segment[idmin:] = True
apret["segment"] = segment
else:
msg = "Cannot correct splitting of approach and retract curve " +\
"because the contact point position could not be estimated."
warnings.warn(msg, CannotSplitWarning)
[docs] @staticmethod
def smooth_height(apret):
"""Smoothen height data
For the columns "height (measured)" and "tip position",
and for the approach and retract data separately, this
method adds the columns "height (measured, smoothed)" and
"tip position (smoothed)" to `self.data`.
"""
orig = ["height (measured)",
"tip position"]
dest = ["height (measured, smoothed)",
"tip position (smoothed)"]
for o, d in zip(orig, dest):
if o not in apret.data.columns:
continue
# Get approach and retract data
app_idx = ~apret.data["segment"]
app = np.array(apret.data[o][app_idx])
ret_idx = apret.data["segment"]
ret = np.array(apret.data[o][ret_idx])
# Apply smoothing
sm_app = smooth_axis_monotone(app)
sm_ret = smooth_axis_monotone(ret)
# Make sure that approach always comes before retract
begin = np.where(app_idx)[0]
end = np.where(ret_idx)[0]
assert(np.all(end-begin > 0)), "Found retract before approach!"
# If everything is ok, we can add the new columns
apret.data[d] = np.concatenate((sm_app, sm_ret))
#: Available preprocessors
available_preprocessors = IndentationPreprocessor.available()