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63 changes: 41 additions & 22 deletions docs/papers.md
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Please email [email protected] if you have used py4DSTEM for analysis and your paper is not listed below!

### 2022 (9)
### 2023 (0)

[Correlative image learning of chemo-mechanics in phase-transforming solids](https://www.nature.com/articles/s41563-021-01191-0), Nature Materials (2022)

[Correlative analysis of structure and chemistry of LixFePO4 platelets using 4D-STEM and X-ray ptychography](https://doi.org/10.1016/j.mattod.2021.10.031), Materials Today 52, 102 (2022).

[Visualizing Grain Statistics in MOCVD WSe2 through Four-Dimensional Scanning Transmission Electron Microscopy](https://doi.org/10.1021/acs.nanolett.1c04315), Nano Letters 22, 2578 (2022).
### 2022 (16)

[Electric field control of chirality](https://doi.org/10.1126/sciadv.abj8030), Science Advances 8 (2022).

[Real-Time Interactive 4D-STEM Phase-Contrast Imaging From Electron Event Representation Data: Less computation with the right representation](https://doi.org/10.1109/MSP.2021.3120981), IEEE Signal Processing Magazine 39, 25 (2022).
[Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns](https://doi.org/10.1038/s41524-022-00939-9), J Munshi*, A Rakowski*, et al., npj Computational Materials 8, 254 (2022)

[Microstructural dependence of defect formation in iron-oxide thin films](https://doi.org/10.1016/j.apsusc.2022.152844), Applied Surface Science 589, 152844 (2022).
[Flexible CO2 Sensor Architecture with Selective Nitrogen Functionalities by One-Step Laser-Induced Conversion of Versatile Organic Ink](https://doi.org/10.1002/adfm.202207406), H Wang et al., Advanced Functional Materials 32, 2207406 (2022)

[Chemical and Structural Alterations in the Amorphous Structure of Obsidian due to Nanolites](https://doi.org/10.1017/S1431927621013957), Microscopy and Microanalysis 28, 289 (2022).
[Defect Contrast with 4D-STEM: Understanding Crystalline Order with Virtual Detectors and Beam Modification](https://doi.org/10.1093/micmic/ozad045) SM Ribet et al., Microscopy and Microanalysis 29, 1087 (2023).

[Nanoscale characterization of crystalline and amorphous phases in silicon oxycarbide ceramics using 4D-STEM](https://doi.org/10.1016/j.matchar.2021.111512), Materials Characterization 181, 111512 (2021).
[Structural heterogeneity in non-crystalline TexSe1−x thin films](https://doi.org/10.1063/5.0094600), B Sari et al., Applied Physics Letters 121, 012101 (2022)

[Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns](https://arxiv.org/abs/2202.00204), arXiv:2202.00204 (2022).
[Cryogenic 4D-STEM analysis of an amorphouscrystalline polymer blend: Combined nanocrystalline and amorphous phase mapping](https://doi.org/10.1016/j.isci.2022.103882), J Donohue et al., iScience 25, 103882 (2022)

[Hydrogen-assisted decohesion associated with nanosized grain boundary κ-carbides in a high-Mn lightweight steel](https://doi.org/10.1016/j.actamat.2022.118392), MN Elkot et al., Acta Materialia
241, 118392 (2022)

[4D-STEM Ptychography for Electron-Beam-Sensitive Materials](https://doi.org/10.1021/acscentsci.2c01137), G Li et al., ACS Central Science 8, 1579 (2022)

[Developing a Chemical and Structural Understanding of the Surface Oxide in a Niobium Superconducting Qubit](https://doi.org/10.1021/acsnano.2c07913), AA Murthy et al., ACS Nano 16, 17257 (2022)

[Correlative image learning of chemo-mechanics in phase-transforming solids](https://www.nature.com/articles/s41563-021-01191-0), HD Deng et al., Nature Materials (2022)

[Correlative analysis of structure and chemistry of LixFePO4 platelets using 4D-STEM and X-ray ptychography](https://doi.org/10.1016/j.mattod.2021.10.031), LA Hughes*, BH Savitzky, et al., Materials Today 52, 102 (2022)

[Visualizing Grain Statistics in MOCVD WSe2 through Four-Dimensional Scanning Transmission Electron Microscopy](https://doi.org/10.1021/acs.nanolett.1c04315), A Londoño-Calderon et al., Nano Letters 22, 2578 (2022)

[Electric field control of chirality](https://doi.org/10.1126/sciadv.abj8030), P Behera et al., Science Advances 8 (2022)

[Real-Time Interactive 4D-STEM Phase-Contrast Imaging From Electron Event Representation Data: Less computation with the right representation](https://doi.org/10.1109/MSP.2021.3120981), P Pelz et al., IEEE Signal Processing Magazine 39, 25 (2022)

[Microstructural dependence of defect formation in iron-oxide thin films](https://doi.org/10.1016/j.apsusc.2022.152844), BK Derby et al., Applied Surface Science 589, 152844 (2022)

[Chemical and Structural Alterations in the Amorphous Structure of Obsidian due to Nanolites](https://doi.org/10.1017/S1431927621013957), E Kennedy et al., Microscopy and Microanalysis 28, 289 (2022)

[Nanoscale characterization of crystalline and amorphous phases in silicon oxycarbide ceramics using 4D-STEM](https://doi.org/10.1016/j.matchar.2021.111512), Ni Yang et al., Materials Characterization 181, 111512 (2021)



### 2021 (10)

[Cryoforged nanotwinned titanium with ultrahigh strength and ductility](https://doi.org/10.1126/science.abe7252), Science 16, 373, 1363 (2021).
[Cryoforged nanotwinned titanium with ultrahigh strength and ductility](https://doi.org/10.1126/science.abe7252), Science 16, 373, 1363 (2021)

[Strain fields in twisted bilayer graphene](https://doi.org/10.1038/s41563-021-00973-w), Nature Materials 20, 956 (2021).
[Strain fields in twisted bilayer graphene](https://doi.org/10.1038/s41563-021-00973-w), Nature Materials 20, 956 (2021)

[Determination of Grain-Boundary Structure and Electrostatic Characteristics in a SrTiO3 Bicrystal by Four-Dimensional Electron Microscopy](https://doi.org/10.1021/acs.nanolett.1c02960), Nanoletters 21, 9138 (2021).
[Determination of Grain-Boundary Structure and Electrostatic Characteristics in a SrTiO3 Bicrystal by Four-Dimensional Electron Microscopy](https://doi.org/10.1021/acs.nanolett.1c02960), Nanoletters 21, 9138 (2021)

[Local Lattice Deformation of Tellurene Grain Boundaries by Four-Dimensional Electron Microscopy](https://pubs.acs.org/doi/10.1021/acs.jpcc.1c00308), Journal of Physical Chemistry C 125, 3396 (2021).

[Extreme mixing in nanoscale transition metal alloys](https://doi.org/10.1016/j.matt.2021.04.014), Matter 4, 2340 (2021).
[Extreme mixing in nanoscale transition metal alloys](https://doi.org/10.1016/j.matt.2021.04.014), Matter 4, 2340 (2021)

[Multibeam Electron Diffraction](https://doi.org/10.1017/S1431927620024770), Microscopy and Microanalysis 27, 129 (2021).
[Multibeam Electron Diffraction](https://doi.org/10.1017/S1431927620024770), Microscopy and Microanalysis 27, 129 (2021)

[A Fast Algorithm for Scanning Transmission Electron Microscopy Imaging and 4D-STEM Diffraction Simulations](https://doi.org/10.1017/S1431927621012083), Microscopy and Microanalysis 27, 835 (2021).
[A Fast Algorithm for Scanning Transmission Electron Microscopy Imaging and 4D-STEM Diffraction Simulations](https://doi.org/10.1017/S1431927621012083), Microscopy and Microanalysis 27, 835 (2021)

[Fast Grain Mapping with Sub-Nanometer Resolution Using 4D-STEM with Grain Classification by Principal Component Analysis and Non-Negative Matrix Factorization](https://doi.org/10.1017/S1431927621011946), Microscopy and Microanalysis 27, 794
[Fast Grain Mapping with Sub-Nanometer Resolution Using 4D-STEM with Grain Classification by Principal Component Analysis and Non-Negative Matrix Factorization](https://doi.org/10.1017/S1431927621011946), Microscopy and Microanalysis 27, 794 (2021)

[Prismatic 2.0 – Simulation software for scanning and high resolution transmission electron microscopy (STEM and HRTEM)](https://doi.org/10.1016/j.micron.2021.103141), Micron 151, 103141 (2021).
[Prismatic 2.0 – Simulation software for scanning and high resolution transmission electron microscopy (STEM and HRTEM)](https://doi.org/10.1016/j.micron.2021.103141), Micron 151, 103141 (2021)

[4D-STEM of Beam-Sensitive Materials](https://doi.org/10.1021/acs.accounts.1c00073), Accounts of Chemical Research 54, 2543 (2021).
[4D-STEM of Beam-Sensitive Materials](https://doi.org/10.1021/acs.accounts.1c00073), Accounts of Chemical Research 54, 2543 (2021)


### 2020 (3)

[Patterned probes for high precision 4D-STEM bragg measurements](https://doi.org/10.1063/5.0015532), Ultramicroscopy 209, 112890 (2020).

[Patterned probes for high precision 4D-STEM bragg measurements](https://doi.org/10.1063/5.0015532), Ultramicroscopy 209, 112890 (2020)

[Tilted fluctuation electron microscopy](https://doi.org/10.1063/5.0015532), Applied Physics Letters 117, 091903 (2020).
[Tilted fluctuation electron microscopy](https://doi.org/10.1063/5.0015532), Applied Physics Letters 117, 091903 (2020)

[4D-STEM elastic stress state characterisation of a TWIP steel nanotwin](https://arxiv.org/abs/2004.03982), arXiv:2004.03982

2 changes: 1 addition & 1 deletion py4DSTEM/datacube/datacube.py
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Expand Up @@ -516,7 +516,7 @@ def get_vacuum_probe(
ROI=None,
align=True,
mask=None,
threshold=0.2,
threshold=0.0,
expansion=12,
opening=3,
verbose=False,
Expand Down
65 changes: 61 additions & 4 deletions py4DSTEM/process/polar/polar_fits.py
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Expand Up @@ -3,22 +3,26 @@

# from scipy.optimize import leastsq
from scipy.optimize import curve_fit
from emdfile import tqdmnd


def fit_amorphous_ring(
im,
im=None,
datacube=None,
center=None,
radial_range=None,
coefs=None,
mask_dp=None,
show_fit_mask=False,
fit_all_images=False,
maxfev=None,
verbose=False,
plot_result=True,
plot_log_scale=False,
plot_int_scale=(-3, 3),
figsize=(8, 8),
return_all_coefs=True,
progress_bar=None,
):
"""
Fit an amorphous halo with a two-sided Gaussian model, plus a background
Expand All @@ -28,6 +32,8 @@ def fit_amorphous_ring(
--------
im: np.array
2D image array to perform fitting on
datacube: py4DSTEM.DataCube
datacube to perform the fitting on
center: np.array
(x,y) center coordinates for fitting mask. If not specified
by the user, we will assume the center coordinate is (im.shape-1)/2.
Expand All @@ -40,6 +46,8 @@ def fit_amorphous_ring(
Dark field mask for fitting, in addition to the radial range specified above.
show_fit_mask: bool
Set to true to preview the fitting mask and initial guess for the ellipse params
fit_all_images: bool
Fit the elliptic parameters to all images
maxfev: int
Max number of fitting evaluations for curve_fit.
verbose: bool
Expand All @@ -63,6 +71,12 @@ def fit_amorphous_ring(
11 parameter elliptic fit coefficients
"""

# If passing in a DataCube, use mean diffraction pattern for initial guess
if im is None:
im = datacube.get_dp_mean()
if progress_bar is None:
progress_bar = True

# Default values
if center is None:
center = np.array(((im.shape[0] - 1) / 2, (im.shape[1] - 1) / 2))
Expand Down Expand Up @@ -193,7 +207,44 @@ def fit_amorphous_ring(
)[0]
coefs[4] = np.mod(coefs[4], 2 * np.pi)
coefs[5:8] *= int_mean
# bounds=bounds

# Perform the fit on each individual diffration pattern
if fit_all_images:
coefs_all = np.zeros((datacube.shape[0], datacube.shape[1], coefs.size))

for rx, ry in tqdmnd(
datacube.shape[0],
datacube.shape[1],
desc="Radial statistics",
unit=" probe positions",
disable=not progress_bar,
):
vals = datacube.data[rx, ry][mask]
int_mean = np.mean(vals)

if maxfev is None:
coefs_single = curve_fit(
amorphous_model,
basis,
vals / int_mean,
p0=coefs,
xtol=1e-8,
bounds=(lb, ub),
)[0]
else:
coefs_single = curve_fit(
amorphous_model,
basis,
vals / int_mean,
p0=coefs,
xtol=1e-8,
bounds=(lb, ub),
maxfev=maxfev,
)[0]
coefs_single[4] = np.mod(coefs_single[4], 2 * np.pi)
coefs_single[5:8] *= int_mean

coefs_all[rx, ry] = coefs_single

if verbose:
print("x0 = " + str(np.round(coefs[0], 3)) + " px")
Expand All @@ -214,9 +265,15 @@ def fit_amorphous_ring(

# Return fit parameters
if return_all_coefs:
return coefs
if fit_all_images:
return coefs_all
else:
return coefs
else:
return coefs[:5]
if fit_all_images:
return coefs_all[:, :, :5]
else:
return coefs[:5]


def plot_amorphous_ring(
Expand Down
29 changes: 0 additions & 29 deletions py4DSTEM/process/utils/utils.py
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Expand Up @@ -11,16 +11,6 @@
import matplotlib.font_manager as fm

from emdfile import tqdmnd
from py4DSTEM.process.utils.multicorr import upsampled_correlation
from py4DSTEM.preprocess.utils import make_Fourier_coords2D

try:
from IPython.display import clear_output
except ImportError:

def clear_output(wait=True):
pass


try:
import cupy as cp
Expand Down Expand Up @@ -173,25 +163,6 @@ def get_qx_qy_1d(M, dx=[1, 1], fft_shifted=False):
return qxa, qya


def make_Fourier_coords2D(Nx, Ny, pixelSize=1):
"""
Generates Fourier coordinates for a (Nx,Ny)-shaped 2D array.
Specifying the pixelSize argument sets a unit size.
"""
if hasattr(pixelSize, "__len__"):
assert len(pixelSize) == 2, "pixelSize must either be a scalar or have length 2"
pixelSize_x = pixelSize[0]
pixelSize_y = pixelSize[1]
else:
pixelSize_x = pixelSize
pixelSize_y = pixelSize

qx = np.fft.fftfreq(Nx, pixelSize_x)
qy = np.fft.fftfreq(Ny, pixelSize_y)
qy, qx = np.meshgrid(qy, qx)
return qx, qy


def get_CoM(ar, device="cpu", corner_centered=False):
"""
Finds and returns the center of mass of array ar.
Expand Down
2 changes: 1 addition & 1 deletion setup.py
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Expand Up @@ -34,7 +34,7 @@
"scikit-optimize >= 0.9.0",
"tqdm >= 4.46.1",
"dill >= 0.3.3",
"gdown >= 4.7.1",
"gdown >= 5.1.0",
"dask >= 2.3.0",
"distributed >= 2.3.0",
"emdfile >= 0.0.14",
Expand Down

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