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18 | 18 | module_dir = os.path.dirname(__file__)
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19 | 19 |
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20 | 20 |
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21 |
| -# %% 20240214-MatPES-178070-r2SCAN generated in collaboration with Shyue Ping Ong's |
22 |
| -# group and Aaron Kaplan is unpublished data as of 2024-07-10, to be shared |
23 |
| -# MIT-licensed in late 2024 at the earliest |
24 |
| -with gzip.open( |
25 |
| - f"{module_dir}/20240214-MatPES-178070-r2SCAN.json.gz", mode="rt" |
26 |
| -) as file: |
| 21 | +# %% |
| 22 | +r2scan_path = f"{module_dir}/20240214-MatPES-178070-r2SCAN.json.gz" |
| 23 | +pbe_path = f"{module_dir}/20240214-MatPES-183027-PBE.json.gz" |
| 24 | +with gzip.open(r2scan_path, mode="rt") as file: |
27 | 25 | r2scan_data = json.load(file)
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28 |
| -# examples/matpes/20240214-MatPES-183027-PBE.json.gz |
29 |
| -with gzip.open(f"{module_dir}/20240214-MatPES-183027-PBE.json.gz", mode="rt") as file: |
| 26 | +with gzip.open(pbe_path, mode="rt") as file: |
30 | 27 | pbe_data = json.load(file)
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31 | 28 |
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32 | 29 | n_r2scan, n_pbe = 178_070, 183_027
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59 | 56 | fig.show()
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60 | 57 | # pmv.save_fig(fig, "energy-hist.pdf")
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61 | 58 |
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62 |
| -# @janosh 2024-05-15: initially surprised by the difference in r2scan/pbe energy distros |
63 |
| -# how could energy differences between two similar chemistries always be similar across |
64 |
| -# r2SCAN and PBE if the distribution for r2SCAN is so much wider |
65 |
| - |
66 |
| - |
67 |
| -# %% seems fine. parity plot reveals this nice collection of bands which looks like |
68 |
| -# within each chemical system, you indeed get consistent energy differences. just across |
69 |
| -# different systems, the zero-level energies differ wildly |
| 59 | +# @janosh 2024-05-15: initially surprised by the difference in r2SCAN and PBE energy |
| 60 | +# distributions. how could energy differences between two similar chemistries always be |
| 61 | +# similar across r2SCAN and PBE if the distribution for r2SCAN is much wider? |
| 62 | +# Update: Seems fine actually. Parity plot reveals this nice collection of bands which |
| 63 | +# looks like within each chemical system, you indeed get consistent energy differences. |
| 64 | +# just across different systems, the zero-level energies differ wildly |
70 | 65 | fig = go.Figure()
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71 | 66 |
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72 | 67 | fig.add_scatter(
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144 | 139 | df_per_elem[pbe_col] = (df_pbe_frac_comp * df_pbe[col_name].to_numpy()[:, None]).mean()
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145 | 140 |
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146 | 141 |
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147 |
| -# %% cohesive energies should (and do) look nearly identical between r2scan and pbe |
| 142 | +# %% cohesive energies should (and do) look nearly identical between r2SCAN and PBE |
148 | 143 | per_elem_cohesive_energy = {
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149 | 144 | key: list(dct.values()) for key, dct in df_per_elem.to_dict(orient="index").items()
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150 | 145 | }
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156 | 151 | fig.show()
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157 | 152 |
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158 | 153 |
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159 |
| -# %% which elements have a higher share of missing r2scan data |
| 154 | +# %% which elements have a higher share of missing r2SCAN data |
160 | 155 | fig = pmv.ptable_heatmap_plotly(
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161 | 156 | (pbe_elem_counts - r2scan_elem_counts) / pbe_elem_counts,
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162 | 157 | colorbar=dict(
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208 | 203 | # pmv.save_fig(fig, "r2scan-spacegroup-hist.pdf")
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209 | 204 |
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210 | 205 |
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211 |
| -# %% most calcs missing r2SCAN results have 4 sites, almost all 2 or 3-site r2scan calcs |
| 206 | +# %% most calcs missing r2SCAN results have 4 sites, almost all 2 or 3-site r2SCAN calcs |
212 | 207 | # completed
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213 | 208 | fig = go.Figure()
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214 | 209 |
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