thomasaarholt

%matplotlib widget
import hyperspy.api as hs
import matplotlib.pyplot as plt
import numpy as np
ll_sum = hs.load('ll_sum.hspy')
s_sum = hs.load('s_sum.hspy')

s_sum.metadata.Acquisition_instrument.TEM.beam_energy=200
s_sum.metadata.Acquisition_instrument.TEM.convergence_angle=22.5
s_sum.metadata.Acquisition_instrument.TEM.Detector.EELS.collection_angle=37.9

thomasaarholt

def fit_Zr_L(sZr, ll=None):
    "Returns the model only"
    print("Will produce 10 progress bars")
    mZr = sZr.create_model(ll = ll, GOS="Hartree-Slater", auto_add_edges=False)
    mZr.fit_component(mZr["PowerLaw"], bounded=True, signal_range=[2150.,2210.], fit_independent=True, only_current=True)
    mZr.assign_current_values_to_all()
    mZr.fit_component(mZr["PowerLaw"], bounded=True, signal_range=[2150.,2210.], fit_independent=True, only_current=False)
    #mZr["PowerLaw"].set_parameters_not_free()

thomasaarholt

%matplotlib widget
import hyperspy.api as hs
import numpy as np
import matplotlib.pyplot as plt

s = hs.datasets.example_signals.object_hologram()
ax0 = s.axes_manager[0]
ax1 = s.axes_manager[1]
ax0.scale=2
ax1.scale=1

thomasaarholt

import numpy as np
import matplotlib.pyplot as plt
import scipy.interpolate

from concurrent.futures import ThreadPoolExecutor
from os import cpu_count
executor = ThreadPoolExecutor(max_workers=cpu_count())
print(f"Processors available: {cpu_count()}")

# parallel=True uses the following map function

thomasaarholt

"""Another way, note this one will load the whole array into memory ."""
from keras.preprocessing.image import ImageDataGenerator
import h5py
from keras.utils.io_utils import HDF5Matrix
seed=0
batch_size=32

# we create two instances with the same arguments
data_gen_args = dict( 
    rotation_range=90.,

thomasaarholt

import hyperspy.api as hs
import numpy as np
from ipywidgets.widgets import HBox, VBox, Label, IntSlider, Output, IntRangeSlider
import matplotlib.pyplot as plt
from IPython.display import display

def plot_polar(s, clim=(10000, 100000), clim_max=(0, 250000)):
    """
    Plot a 4D hyperspy dataset with the signal in polar coordinates
    Arguments:

thomasaarholt

%matplotlib widget
import hyperspy.api as hs
import matplotlib.pyplot as plt
from ipywidgets.widgets import HBox, Label, Dropdown

# Optional, for notebook only, not lab
# from IPython.core.display import display, HTML
# display(HTML("<style>.container { width:100% !important; }</style>"))

def plot(s):

thomasaarholt

from ipywidgets.widgets import HBox, VBox
import matplotlib.pyplot as plt

def plot(s, orientation='horizontal'):
    """
    Plot hyperspy signals horizontally using the %matplotlib widget interface.
    Can also plot vertically using orientation='vertical'
    """
    
    # if 1D signal, just plot normal

thomasaarholt

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
~\.conda\envs\py5\lib\site-packages\matplotlib\backend_bases.py in _wait_cursor_for_draw_cm(self)
   2772             try:
-> 2773                 self.set_cursor(cursors.WAIT)
   2774                 yield

~\.conda\envs\py5\lib\site-packages\matplotlib\backends\backend_webagg_core.py in set_cursor(self, cursor)
    380         if cursor != self.cursor:
--> 381             self.canvas.send_event("cursor", cursor=cursor)

thomasaarholt

import numpy as np
import matplotlib.pyplot as plt

# get electropy from thomasaarholt github
from electropy.units import eV_to_wavelength

# get colour by pip install colour-science
from colour.utilities import first_item, normalise_maximum
from colour.plotting import filter_cmfs, XYZ_to_plotting_colourspace, COLOUR_STYLE_CONSTANTS
from colour.colorimetry import wavelength_to_XYZ, ILLUMINANTS