@thomasaarholt Hi,
I try to get quantified EDS from a sample with many elements (Al,C,Co,Cu,Cr,Mo,O,Pt,W,Zn) with a strong peak overlap between Cr-L (0.571 eV) and O-K (0.523 eV).
One layer is expected to be CrC but appears as CrO... the quantification output 30% of O in it, which is very unexpected for several reasons. Checking the EDS spectrum manually I can see the peak shift by maybe 1 channel when seeing Cr-L instead of O-K but the model fitting doesn't.
I am using the EDS model fitting and after several hours in the documentation I come here to ask: Is there a solution to this? is there a function somewhere that can for instance estimate Cr-L from the Cr-K intensity and subtract it from the O-K signal before saving the O-K intensity? I hope this question is clear enough!
Regards,
Olivier
18 replies
I am trying to run the following code :
import hyperspy.api as hs
input_filename = "file1.emd"
spim = hs.load(input_filename)[-1]
# the output of the load function is a list in which the last element is an EDSTEM object.
spim.change_dtype("float")
spim.crop(1,70,400)
spim.crop(2,0.3,19.0)
spim.decomposition(True)It ouputs : ValueError: All the data are masked, change the mask.
It seems to me that the crop functions are at the source of this issue since when I comment them everything is fine.
I am asking here to check if I am missing something. But I will post an issue on github if not.
3 replies
Hi, I'm not sure if it's just me missing something. But when I import images from Velox EMD (this particular file has 9538 HAADF frames), only the scaling from the first frame is retained in the axes_manager values. I've copied my code snippet below.
%matplotlib qt
import hyperspy.api as hs
import numpy as np
import matplotlib.pyplot as plt
import scipy
import hyperspy.misc as hsm
#prevent figure opening
plt.ioff()
#load file
s = hs.load("211217/HeatedTEM/HeatedTEM.emd")
print("imported")
print(s.axes_manager)
#format and save image with time stamp
for single_image in s:
####### Failed attempt at scaling
single_image.axes_manager[1].scale
single_image.axes_manager[0].scale
single_image.axes_manager[1].offset
single_image.axes_manager[0].offset
single_image.axes_manager[1].units
single_image.axes_manager[0].units
a = single_image.plot(colorbar=False, scalebar=True, axes_ticks=False)
plt.axis('off')
plt.savefig('test/image %s.png' % str(s.axes_manager.indices), bbox_inches = 'tight', pad_inches = 0.1)
plt.close()
#single_image.save("test/image %s.png" % str(image_stack.axes_manager.indices))But every single_image.axis_manager contains the same value as s.axis_manager (in this case 0.37nm) so the scaling is the same for every image
5 replies
Hello
in Pycharm I had the below code that worked before with giving interactive hyperspy plots with s.plot()
import matplotlib
matplotlib.rcParams["backend"] = "Agg"
import hyperspy.api as hsI am getting the following error and no plots shown. Please help if possible, and let me know if you need more information.
Thank you!
WARNING:hyperspy_gui_traitsui:The agg matplotlib backend is not compatible with the traitsui GUI elements. For more information, read http://hyperspy.readthedocs.io/en/stable/user_guide/getting_started.html#possible-warnings-when-importing-hyperspy.
WARNING:hyperspy_gui_traitsui:The traitsui GUI elements are not available.[<EDSTEMSpectrum, title: EDS, dimensions: (|4096)>,
<EDSTEMSpectrum, title: EDS, dimensions: (|4096)>,
<EDSTEMSpectrum, title: EDS, dimensions: (|4096)>,
<EDSTEMSpectrum, title: EDS, dimensions: (|4096)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: HAADF, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<Signal2D, title: x, dimensions: (|512, 512)>,
<EDSTEMSpectrum, title: EDS, dimensions: (512, 512|4096)>]
1 reply
from scipy.misc import face
img = face(gray=True)
plt.figure()
plt.imshow(img, cmap=cmap)
plt.colorbar()
Hey all, I am trying to get the decomposition of a sum of a section of the frames of a EDS signal.
When I load the entire signal with sum_frames=True, the decomposition works fine. But when I load it with sum_frames=False and then sum all the frames using .sum('Time'), the resulting signal looks differently (lower intensity) and the decomposition works but the result is different (worse). What is the difference between the sum_frames=True argument and summing the frames after loading using .sum('Time')?
Also, when I try to sum a section of the frames in time (e.g. the first 20) I get the error message: ValueError: All the data are masked, change the mask.
Is there a way to avoid this error and get the decomposition over a range of time?
Thank you!
1 reply
1 reply
When I replace the test files with actual files I have on my device (same extensions), and I run the test script I get the following messages:
WARNING:hyperspy.io:Unable to infer file type from extension 'ASW'. Will attempt to load the file with the Python imaging library.
ERROR:hyperspy.io:If this file format is supported, please report this error to the HyperSpy developers.
2 replies
Hi, I am using EDS models and have trouble to restore the stored ones.
I create a model m, fit it and store it, and also copy it to a EDS_model variable
#create a model using all selected elements:
m = si.create_model()
m.fit()
m.fit_background()
#Reduce the element selection to the one of interest and quantify
kfactors = Assign_elements2Quant()
xray_lines_selected=si.metadata.Sample.xray_lines
m_int_fit = m.get_lines_intensity(xray_lines_selected)
m.store()
EDS_model = mAfter this, the "si" is saved to a .hspy file.
If i look at the EDS_model, it is fine, I can plot it and so on.
EDS_model
Out[80]: <EDSTEMModel, title: EDX>But then I try to load the .hspy file again, I see the model is there, with the components, but cannot restore it or plot it... why?
l = hs.load(signal_type="EDS_TEM", escape_square_brackets=(True))
l.models
Out[82]:
└── a
├── components
│ ├── Al_Ka
│ ├── Al_Kb
│ ├── C_Ka
│ ├── Co_Ka
│ ├── Co_Kb
│ ├── Co_La
│ ├── Co_Lb3
│ ├── Co_Ll
│ ├── Co_Ln
│ ├── Cr_Ka
│ ├── Cr_Kb
│ ├── Cr_La
│ ├── Cr_Lb3
│ ├── Cr_Ll
│ ├── Cr_Ln
│ ├── Mo_Ka
│ ├── Mo_Kb
│ ├── Mo_La
│ ├── Mo_Lb1
│ ├── Mo_Lb2
│ ├── Mo_Lb3
│ ├── Mo_Lg1
│ ├── Mo_Lg3
│ ├── Mo_Ll
│ ├── Mo_Ln
│ ├── O_Ka
│ ├── W_La
│ ├── W_Lb1
│ ├── W_Lb2
│ ├── W_Lb3
│ ├── W_Lb4
│ ├── W_Lg1
│ ├── W_Lg3
│ ├── W_Ll
│ ├── W_Ln
│ ├── W_M2N4
│ ├── W_M3O4
│ ├── W_M3O5
│ ├── W_Ma
│ ├── W_Mb
│ ├── W_Mg
│ ├── W_Mz
│ ├── Zn_Ka
│ ├── Zn_Kb
│ ├── Zn_La
│ ├── Zn_Lb1
│ ├── Zn_Lb3
│ ├── Zn_Ll
│ ├── Zn_Ln
│ └── background_order_6
├── date = 2022-02-08 12:09:22
└── dimensions = (96, 89|2048)
Mymodel = l.models.a.restore()
Traceback (most recent call last):
File "C:\Users\oldo\AppData\Local\Temp/ipykernel_14272/3459143043.py", line 1, in <module>
Mymodel = l.models.a.restore()
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\signal.py", line 82, in <lambda>
self.restore = lambda: mm.restore(self._name)
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\signal.py", line 241, in restore
return self._signal.create_model(dictionary=copy.deepcopy(d))
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\_signals\eds_tem.py", line 745, in create_model
model = EDSTEMModel(self,
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\models\edstemmodel.py", line 45, in __init__
EDSModel.__init__(self, spectrum, auto_background, auto_add_lines,
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\models\edsmodel.py", line 131, in __init__
Model1D.__init__(self, spectrum, *args, **kwargs)
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\models\model1d.py", line 279, in __init__
self._load_dictionary(dictionary)
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\model.py", line 306, in _load_dictionary
id_dict.update(self[-1]._load_dictionary(comp))
File "C:\Users\oldo\.conda\envs\hspy_env\lib\site-packages\hyperspy\component.py", line 1223, in _load_dictionary
raise ValueError(
ValueError: _id_name of parameters in component and dictionary do not match
environment.yml file. However, for my analysis I need to use nonlinear functionality, which isn't included in hyperspy v1.6.5 - but cloning RELEASE_next_minor is something which can't be tracked using an environment.yml file. Does anyone have a suggestion for how to get nonlinear functionality in a reproducible way? @LMSC-NTappy proposed forking RELEASE_next_minor to my own GitHub, pip installing the fork, and then leaving that fork unchanged - this is what I'll do for now. But I'm always grateful for other suggestions - thanks!
5 replies
the line2D interactive ROI raises an error when I try to integrate over a width "linewidth is not supported for axis with different scale", however the axes_manager says that the scale is the same for both axes... is it a rounding problem? can I correct it?
the EDS map is from Velox (.emd)
line1=line_roi.interactive(data,color='yellow')
ValueError: linewidth is not supported for axis with different scale.
data.axes_manager
Out[53]:
<Axes manager, axes: (|118, 81)>
Name | size | index | offset | scale | units
================ | ====== | ====== | ======= | ======= | ======
---------------- | ------ | ------ | ------- | ------- | ------
x | 118 | | 0.043 | 0.14 | nm
y | 81 | | -2.8 | 0.14 | nm
Hi everyone,
I am using Velox to acquire EM images and I am looking to use HyperSpy to help with the analysis. I do not have access to Velox on my personal computer, so I am using HyperSpy to load the EMD files. I am recording videos on Velox, however, to my knowledge it does not appear that I can save each individual frame of the video as a TIF in the Velox software itself (for single images I can easily export the data as a TIF on Velox). Using HyperSpy I am trying to convert the EMD files to TIF. However, I noticed that my scalebar is missing in the TIF when I open it later. Is there a way to save the scalebar information from the metadata using HyperSpy? I could come up with other solutions but I am looking for something more elegant since I know that HyperSpy can access the metadata. I see that there is a module for drawing scalebars in HyperSpy but I have not found a way to implement this correctly.
Here is some very basic code that I have written in Python to save the EMD images to TIF:
import hyperspy.api as hs
import tkinter as tk
from tkinter import filedialog
root = tk.Tk()
root.withdraw()
file_path = filedialog.askopenfilename()
s = hs.load(file_path)
s.plot() # I can see the scalebar from the metadata
save_input = input("Would you like to save? (Y/N)? ")
if save_input == "Y" or save_input == "Yes" or save_input == "yes" or save_input == "y":
save_path = filedialog.asksaveasfilename()
s.save(save_path) # I can no longer see the scalebar here, how can I flatten the overlay?
else:
print("END OF PROGRAM.")
Thanks for any help that you can provide!
1 reply
I was wondering if hyperspy interactive functions work with Google Colab. I saw a comment from a few years ago on how
%matplotlib notebook does not work for the hyperspy plotting functions.I have currently tried both
notebook and widget backends, none of which seem to give a plot.Any advice/workarounds?
Thanks
- sklearn_fastica provides very instalbe results. Each run gives completely different solution. Is it normal?
3 replies
3 replies
Hi everyone, I have recorded a HAADF-STEM video in Velox with 500 image frames. During recording, I changed the magnification, zoomed in and out. I am already able to export each individual frame. However, the scalebar is the same for each frame (whereas in Velox it shows different scale bars for each individual frame). Do you have any solution for that? What did NOT work:
single_image=complete_dataset.inav[frame_number]
print(single_image.axes_manager[0].scale)
(The type of the complete_dataset is signal2D). Thanks a lot for your help! :)
4 replies
Hi everyone, I am having trouble saving a signal or multiple signals loaded from .emd format to nexus format using the following command:
file_writer("test.nxs",s)
I got the following error :
AttributeError: 'dict' object has no attribute 'dtype'
it works fine using the following command , but the original metadata would be not saved:
file_writer("test.nxs",s,save_original_metadata=False)
Can someone help please, i need to save the metadata also .
Hi all,
I am new to hyperspy and still a bit lost getting the thickness out of an EEL spectrum.
I have tried this:
s_ll = hs.load("20220315/data.dm3")
s_ll.set_microscope_parameters(beam_energy = 200, collection_angle=6.0, convergence_angle=0.021)
s.set_microscope_parameters(beam_energy = 200, collection_angle=6.0, convergence_angle=0.021)
s_ll.plot()
s_ll.align_zero_loss_peak(subpixel=True, also_align=[s])
th = s_ll.estimate_elastic_scattering_threshold(window=10)
density = 5.515
s_ll_thick = s_ll.estimate_thickness(threshold=th, density=density)
and as a result I obtain this:
s_ll_thick
<BaseSignal, title: E8-FeNiO-PS71-T_0043 thickness (nm), dimensions: (1|)>
What does it mean? I would like to obtain a value and not a signal. Sorry, if this is an obvious answer. ;-)
Thank you for your help!
2 replies
9 replies
4 replies
m = s_fit.create_model()
g1 = hs.model.components1D.GaussianHF()
g2 = hs.model.components1D.GaussianHF()
g3 = hs.model.components1D.GaussianHF()
m.extend([g1, g2, g3])
m00 = m.inav[0]
m00.fit()
How can I get the fitted data for each component after running m00.fit() (including the sum) so I can plot them myself rather than using the s.plot()? Do I have to compute them myself? Thanks very much.
23 replies
Hi all, greetings from LiberTEM! With the latest release we implemented full Dask array integration. That means LiberTEM and HyperSpy (lazy) signals can now interoperate. That opens a range of opportunities:
- Share the same file readers for both projects. See our supported formats. In particular, support for K2IS raw, FRMS6 and Direct Electron SEQ could be added to HyperSpy with little effort.
- Simplify implementing routines in HyperSpy that would require Dask’s
map_blocks()interface by using the LiberTEM UDF interface instead. - Use the same implementation for scientific algorithms in both projects. As an example, fast ptychography could be offered in HyperSpy, or strain, phase and orientation mapping in pyxem could be applied to live data streams.
This message is to start a discussion on what could be useful and what steps to take in that direction. 😊
6 replies
1 reply
I know i can find out by contacting the TEM technician I'm working with but I'd quite like to have a self-contained bit of code which can automate things as much as possible, so it should automatically get the pixel size from the data I have
4 replies