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Diff for: GBFS.py

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Diff for: Jupyter/1. Elastic Properties/1. Featurize - moduli.ipynb

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Diff for: Jupyter/1. Elastic Properties/2. GBFS - shear_modulus.ipynb

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Diff for: Jupyter/1. Elastic Properties/3. GBFS - bulk_modulus.ipynb

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Diff for: Jupyter/2. Electronic Transport/1a. Featurize - ricci_boltztrap_mp_tabular.ipynb

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Diff for: Jupyter/2. Electronic Transport/1b. Featurize - ricci_boltztrap_mp_tabular_missing_data.ipynb

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Diff for: Jupyter/2. Electronic Transport/2. GBFS - metal.ipynb

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Diff for: Jupyter/2. Electronic Transport/3. GBFS - bandgap.ipynb

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Diff for: Jupyter/2. Electronic Transport/4. GBFS - conductivity_ntype.ipynb

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Diff for: Jupyter/3. Metallicity/1a. Featurize part 1 - metal.ipynb

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Diff for: Jupyter/4. Dielectric Constant/1. Featurize - refractive_index.ipynb

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Diff for: Jupyter/4. Dielectric Constant/2. GBFS - refractive_index.ipynb

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Diff for: Jupyter/5. Magnetic Order/0. Data gathering - magnetism.ipynb

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Diff for: Jupyter/5. Magnetic Order/1a. Featurize - part_1.ipynb

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Diff for: Jupyter/5. Magnetic Order/2. GBFS - mag_order.ipynb

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Diff for: Jupyter/6. Perovskites/1. Featurize - perovskites.ipynb

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Diff for: Jupyter/6. Perovskites/2. GBFS - direct_or_indirect_bandgap.ipynb

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Diff for: Jupyter/6. Perovskites/3. GBFS - fermi_level.ipynb

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Diff for: Jupyter/7. Thermal Electric/1. Featurize - thermal_electric.ipynb

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Diff for: Jupyter/7. Thermal Electric/2. GBFS - thermal_electric (n-type).ipynb

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Diff for: Jupyter/8. Ferroelectric/1. Featurize - dielectric_constant.ipynb

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Diff for: Jupyter/9. Custom Dataset/1. data_acquisition_and_featurization/featurize_cif_testing.ipynb

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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Module for creating custom features ('featurize_custom.py')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import featurize_custom as fcus"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Initialize module\n",
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"feature = fcus.use_custom_descriptors('AB3C4D6', csv = False)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Create custom features\n",
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"feature.featurize()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Join custom features with CFID features\n",
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"feature.join()"
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]
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},
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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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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.6.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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