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Save notebook with jupyter lab to fix issue with new notebook format in the "classic" notebook. See jupyter/nbformat#161 (comment) 
1 parent 8a92fcf commit 81b46a8

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-86
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‎02 HyperSpy basics/02 Getting_Started.ipynb‎

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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"version": "3.7.6"
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}
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},
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"nbformat": 4,

‎02 HyperSpy basics/02 Getting_Started_completed.ipynb‎

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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"version": "3.7.6"
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}
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},
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"nbformat": 4,

‎03 Curve fitting/03 Fitting_tutorial.ipynb‎

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{
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"cell_type": "code",
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"execution_count": 32,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [
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{
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"data": {
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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"collapsed": true,
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"jupyter": {
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"outputs_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": true
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"collapsed": true,
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"jupyter": {
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"outputs_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.0"
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"version": "3.7.6"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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"nbformat_minor": 4
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}

‎03 Curve fitting/03 Fitting_tutorial_completed.ipynb‎

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{
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"cell_type": "code",
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"execution_count": 32,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [
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{
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"data": {
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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"collapsed": true,
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"jupyter": {
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"outputs_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": true
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"collapsed": true,
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"jupyter": {
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"outputs_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.0"
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"version": "3.7.6"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎04 EELS/04 EELS_analysis.ipynb‎

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{
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"execution_count": null,
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"metadata": {
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"scrolled": false
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"metadata": {},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.4"
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"version": "3.7.6"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {

‎04 EELS/04 EELS_analysis_complete.ipynb‎

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{
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"cell_type": "code",
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"execution_count": null,
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"scrolled": false
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"metadata": {},
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"outputs": [],
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"source": [
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"s.remove_background()"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"metadata": {},
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"outputs": [],
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"source": [
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"m.plot()"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.4"
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"version": "3.7.6"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {

‎06 Machine learning/06_machine_learning_in_EM.ipynb‎

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{
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"cell_type": "code",
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"execution_count": 40,
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"metadata": {
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"scrolled": false
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"metadata": {},
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"outputs": [
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"data": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.0"
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"version": "3.7.6"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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}
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},
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"nbformat": 4,
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}

‎06 Machine learning/06_machine_learning_in_EM_completed.ipynb‎

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{
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"execution_count": 40,
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"version": "3.7.6"
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"widgets": {
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}
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}

‎07 EDS/07 TEM_EDS_nanoparticles.ipynb‎

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"name": "python",
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"nbformat": 4,
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}

‎07 EDS/07 TEM_EDS_nanoparticles_completed.ipynb‎

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"name": "python",
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"nbconvert_exporter": "python",
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"version": "3.7.0"
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"version": "3.7.6"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {

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