In [56]:
%pylab inline
import hyperspy.api as hs
import matplotlib.pylab as pylab
pylab.rcParams['figure.figsize'] = 8, 6  # that's default image size for this interactive session
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
#from ipywidgets.widgets import interactive, fixed, interact
from skimage.exposure import equalize_hist, equalize_adapthist, rescale_intensity
from skimage import filters

import os

StackName = 'Stack.bcf'
BinningFactor = 4

def MakeRGBFromMaps(R,G,B, bits=16, equalize=False, cutnoise=False):
    MaxPixelVal = (2**bits)-1
    
    # Make a Signal2D from the three images and copy over the metadata.
    x = hs.stack([R,G,B])
    x = hs.signals.Signal2D(x).T
    x.metadata = R.metadata
    x.original_metadata = R.original_metadata
    x.metadata.General.title = R.metadata.Sample.xray_lines[0] + '(R) ' + G.metadata.Sample.xray_lines[0] + '(G) ' + B.metadata.Sample.xray_lines[0] + '(B)'
    
    rdata = x.data[:,:,0]
    gdata = x.data[:,:,1]
    bdata = x.data[:,:,2]
            
    if cutnoise==True:
        NoiseCutAggressiveness = 1 # 0 means no cut, 1 means full cut.
        rdata[rdata < filters.threshold_triangle(rdata)*NoiseCutAggressiveness] = 0
        gdata[gdata < filters.threshold_triangle(gdata)*NoiseCutAggressiveness] = 0
        bdata[bdata < filters.threshold_triangle(bdata)*NoiseCutAggressiveness] = 0
 
    if equalize==True:
        rdata = equalize_hist(rdata)
        gdata = equalize_hist(gdata)
        bdata = equalize_hist(bdata)

    rdata = rescale_intensity(rdata)*MaxPixelVal
    gdata = rescale_intensity(gdata)*MaxPixelVal
    bdata = rescale_intensity(bdata)*MaxPixelVal

    x.data[:,:,0] = rdata
    x.data[:,:,1] = gdata
    x.data[:,:,2] = bdata

    # Convert to RGB.
    if bits==16:
        x.change_dtype('uint16')
        x.change_dtype('rgb16')
    else:
        x.change_dtype('uint8')
        x.change_dtype('rgb8')    
    
    # Copy the axes info over from the R map.
    x.axes_manager = R.axes_manager.copy()

    return(x)

def EqualizeAxis(fignum=None):
    # Because of a bug in Hyperspi, I sometimes have to set the axis to equal after we rebin.
    if fignum == None:
        fig=plt.gcf()
    else:
        fig = plt.figure(fignum)
    ax = fig.axes
    if type(ax) != list:
        ax.axis('equal')
    else:
        for a in ax:
            a.axis('equal')
    fig.tight_layout()
    
def RemovePtGaContamination(ElementDict):
    '''Make maps without contamination from Pt and Ga in FIB sections.
    The maps in ElementDict must contain Pt and Ga maps (obviously...)
    '''
    ElementDictNoPtGa = dict()
    for ElName, ElMap in ElementDict.items():
        if ElName in ['Pt', 'Ga']:
            ElementDictNoPtGa[ElName] = ElementDict[ElName].deepcopy()
            continue
        ReducedData = ElementDict[ElName].data.astype(float) - ElementDict['Pt'].data.astype(float) - ElementDict['Ga'].data.astype(float)
        ReducedData[ReducedData < 0] = 0
        ReducedElMap = ElMap.deepcopy()
        ReducedElMap.data = ReducedData
        ElementDictNoPtGa[ElName] = ReducedElMap
    return ElementDictNoPtGa

def PlotAndSaveRGBAndRGBNoPtGa(RGBElements, equalizeRGB=True, cutnoiseRGB=True, equalizeNoPtGa=True, cutnoiseNoPtGa=True):
    Img1 = MakeRGBFromMaps(ElementDict[RGBElements[0]],ElementDict[RGBElements[1]],ElementDict[RGBElements[2]], 
                      equalize=equalizeRGB, cutnoise=cutnoiseRGB)
    #Img1.plot()
    Img1.save(os.path.join(f'Maps_{BinningFactor}bin', RGBElements[0]+RGBElements[1]+RGBElements[2]+'.tif'), overwrite=True)
    Img2 = MakeRGBFromMaps(ElementDictNoPtGa[RGBElements[0]],ElementDictNoPtGa[RGBElements[1]],ElementDictNoPtGa[RGBElements[2]], 
                          equalize=equalizeNoPtGa, cutnoise=cutnoiseNoPtGa)
    #Img2.plot()
    Img2.save(os.path.join(f'MapsNoPtGa_{BinningFactor}bin', RGBElements[0]+RGBElements[1]+RGBElements[2]+'.tif'), overwrite=True)
    hs.plot.plot_images([Img1,Img2], colorbar=None)
    #plt.tight_layout()

Populating the interactive namespace from numpy and matplotlib
In [57]:
HAADF, EDS = hs.load(StackName)
print(f'Stack dimensions are: {EDS.data.shape}.')
if BinningFactor > 1:
    EDS = EDS.rebin(scale=(BinningFactor, BinningFactor, 1))
    print(f'New stack dimensions are: {EDS.data.shape} with binning: {BinningFactor}')
EDS.plot()

HAADF.save(os.path.join(f'Maps_{BinningFactor}bin', 'HAADF.tif'), overwrite=True)
HAADF.save(os.path.join(f'MapsNoPtGa_{BinningFactor}bin', 'HAADF.tif'), overwrite=True)

Stack dimensions are: (512, 512, 2048).
New stack dimensions are: (128, 128, 2048) with binning: 4
In [58]:
print(HAADF.metadata)
print(EDS.metadata)

├── Acquisition_instrument
│   └── TEM
│       ├── beam_energy = 80
│       └── magnification = 7100
├── General
│   ├── original_filename = Stack.bcf
│   └── title = HAADF
├── Sample
│   └── name = 1
└── Signal
    ├── binned = False
    └── signal_type = 

├── Acquisition_instrument
│   └── TEM
│       ├── Detector
│       │   └── EDS
│       │       ├── azimuth_angle = 45.0
│       │       ├── detector_type = SuperX
│       │       ├── elevation_angle = 18.0
│       │       ├── energy_resolution_MnKa = 130.0
│       │       └── real_time = 50591.744
│       ├── Stage
│       │   └── tilt_alpha = 0.0
│       ├── beam_energy = 80
│       └── magnification = 7100
├── General
│   ├── date = 2022-03-18
│   ├── original_filename = Stack.bcf
│   ├── time = 19:50:40
│   └── title = EDX
├── Sample
│   ├── elements = ['Al', 'C', 'Ca', 'Cu', 'Fe', 'Ga', 'Mg', 'O', 'Pt', 'S', 'Si']
│   ├── name = 1
│   └── xray_lines = ['Al_Ka', 'C_Ka', 'Ca_Ka', 'Cu_Ka', 'Fe_Ka', 'Ga_Ka', 'Mg_Ka', 'O_Ka', 'Pt_La', 'S_Ka', 'Si_Ka']
└── Signal
    ├── binned = True
    ├── quantity = X-rays (Counts)
    └── signal_type = EDS_TEM
In [59]:
sumspec = EDS.sum()
sumspec.add_lines()
ElLines = ['C_Ka', 'N_Ka', 'O_Ka', 'Na_Ka', 'Pt_La', 'Mg_Ka', 'Al_Ka', 'Si_Ka', 'P_Ka', 'S_Ka', 'Cl_Ka', 'K_Ka', 'Ca_Ka', 'Ti_Ka', 'Cr_Ka', 'Mn_Ka', 'Fe_Ka', 'Ni_Ka', 'Zn_Ka', 'Cu_Ka', 'Ga_Ka' ]
Elements = EDS.get_lines_intensity(ElLines)
Elements = [El.T for El in Elements]
ElementDict = dict()
for El in Elements:
    El.change_dtype('uint16')
    El.save(os.path.join(f'Maps_{BinningFactor}bin', El.metadata.Sample.xray_lines[0]+'.tif'), overwrite=True)
    ElementDict[El.metadata.Sample.elements[0]] = El
    #print(f'{El.metadata.Sample.elements[0]}')
    
ElementDictNoPtGa = RemovePtGaContamination(ElementDict)
ElementsNoPtGa = [El for El in ElementDictNoPtGa.values()]
for El in Elements:
    El.save(os.path.join(f'MapsNoPtGa_{BinningFactor}bin', El.metadata.Sample.xray_lines[0]+'.tif'), overwrite=True)
In [60]:
fig = plt.figure(figsize=(20,20))
hs.plot.plot_images(Elements, per_row=ceil(sqrt(len(Elements))), colorbar=None, axes_decor='off', fig=fig)
plt.show()
fig.savefig(os.path.join(f'Maps_{BinningFactor}bin', 'Mosaic.png'))

/Users/Zack/opt/anaconda3/envs/conda37/lib/python3.7/site-packages/hyperspy/drawing/utils.py:890: MatplotlibDeprecationWarning: Passing non-integers as three-element position specification is deprecated since 3.3 and will be removed two minor releases later.
  ax = f.add_subplot(rows, per_row, idx + 1)
In [61]:
fig = plt.figure(figsize=(20,20))
hs.plot.plot_images(ElementsNoPtGa, per_row=ceil(sqrt(len(ElementsNoPtGa))), colorbar=None, axes_decor='off', fig=fig)
plt.show()
fig.savefig(os.path.join(f'MapsNoPtGa_{BinningFactor}bin', 'Mosaic.png'))
In [62]:
PlotAndSaveRGBAndRGBNoPtGa(['Fe', 'Mg', 'O'], equalizeRGB=True, cutnoiseRGB=True)

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In [63]:
PlotAndSaveRGBAndRGBNoPtGa(['Fe', 'Si', 'S'])

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In [64]:
PlotAndSaveRGBAndRGBNoPtGa(['Fe', 'Ni', 'S'])

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In [65]:
PlotAndSaveRGBAndRGBNoPtGa(['C', 'N', 'O'])

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In [66]:
PlotAndSaveRGBAndRGBNoPtGa(['C', 'O', 'Si'], equalizeNoPtGa=True, cutnoiseNoPtGa=True)

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In [67]:
PlotAndSaveRGBAndRGBNoPtGa(['Al', 'Mg', 'O'], equalizeNoPtGa=True, cutnoiseNoPtGa=True)

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In [68]:
PlotAndSaveRGBAndRGBNoPtGa(['Al', 'Ca', 'Cr'], equalizeNoPtGa=False, cutnoiseNoPtGa=False)

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In [69]:
PlotAndSaveRGBAndRGBNoPtGa(['Na', 'K', 'Al'], equalizeNoPtGa=False, cutnoiseNoPtGa=False)

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In [ ]:
%%javascript
IPython.notebook.save_notebook()
In [ ]:
!jupyter-nbconvert --to html "Plot Bruker Stack.ipynb"
In [ ]:
%%javascript
IPython.notebook.save_notebook()
In [ ]: