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Sciglass
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| include *.txt | ||
| recursive-include doc *.txt | ||
| recursive-include doc * | ||
| include glasspy/data/datafiles/* |
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| ODC Open Database License (ODbL) | ||
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| Copyright (c) 2019 EPAM Systems | ||
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| Permission is hereby granted, free of charge, to any person obtaining a copy | ||
| of this software and associated documentation files (the "Software"), to deal | ||
| in the Software without restriction, including without limitation the rights | ||
| to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
| copies of the Software, and to permit persons to whom the Software is | ||
| furnished to do so, subject to the following conditions: | ||
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| The above copyright notice and this permission notice shall be included in all | ||
| copies or substantial portions of the Software. | ||
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| THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
| IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
| FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
| AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
| LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
| OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
| SOFTWARE. |
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| #!/usr/bin/env python3 | ||
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| import pandas as pd | ||
| import numpy as np | ||
| import os | ||
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| from .manipulate import removeColumnsWithOnlyZerosMultiIndex | ||
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| __cur_path = os.path.dirname(__file__) | ||
| SCIGLASS_DATABASE_PATH = os.path.join(__cur_path, 'datafiles/sciglass.csv.xz') | ||
| SCIGLASS_COMP_DATABASE_PATH = os.path.join(__cur_path, 'datafiles/sciglass_comp.csv.xz') | ||
| SCIGLASS_ATFRAC_DATABASE_PATH = os.path.join(__cur_path, 'datafiles/sciglass_atfrac.csv.xz') | ||
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| def sciglass(load_compounds=False, load_atomic_fraction=True): | ||
| """Load SciGlass data into a pandas DataFrame | ||
| SciGlass is a database of glass properties Copyright (c) 2019 EPAM Systems | ||
| and licensed under ODC Open Database License (ODbL). The database is hosted | ||
| on GitHub [1]. A portion of the SciGlass database is shipped with GlassPy, | ||
| so no additional downloads are necessary. | ||
| This function returns a MultiIndex pandas DataFrame. The first-level | ||
| indexes are: | ||
| at_frac : relative to the atomic fraction of the chemical elements that | ||
| make the glass. Only available if "load_atomic_fraction" is True. | ||
| comp : relative to the chemical compounds that make the glass. Only | ||
| available if "load_compounds" is True. | ||
| meta : metadata. | ||
| prop : properties. | ||
| The property column names are: | ||
| RefractiveIndex : refractive index measured at wavelenght of 589.3 nm. | ||
| Dimensionless. | ||
| AbbeNumber : Abbe number. Dimensionless. | ||
| CTE : linear coefficient of thermal expansion below the glass transition | ||
| temperature. Unit: K^{-1}. | ||
| ElasticModulus : Elastic of Young's Modulus. Unit: GPa. | ||
| Tg : glass transition temperature. Unit: K. | ||
| Tliquidus: liquidus temperature. Unit: K. | ||
| T0 to T12 : "Tn" is the temperature where the base-10 logarithm of | ||
| viscosity (in Pa.s) is "n". Example: T4 is the temperature where | ||
| log10(viscosity) = 4. Unit: K. | ||
| ViscosityAt773K to ViscosityAt2473K : value of base-10 logarithm of | ||
| viscosity (in Pa.s) at a certain temperature. Example: | ||
| ViscosityAt1073K is the log10(viscosity) at 1073 Kelvin. | ||
| Dimensionless. | ||
| Parameters | ||
| ---------- | ||
| load_compounds : bool, False | ||
| If True then chemical compounds are loaded and added to the DataFrame | ||
| load_atomic_fraction : bool, True | ||
| If True then the atomic fractions are loaded and added to the DataFrame | ||
| Returns | ||
| ------- | ||
| data : pandas DataFrame | ||
| MultiIndex DataFrame containing a portion of the SciGlass database. | ||
| References | ||
| ---------- | ||
| [1] Epam/SciGlass. 2019. EPAM Systems, 2019. | ||
| https://github.com/epam/SciGlass. | ||
| """ | ||
| data = pd.read_csv(SCIGLASS_DATABASE_PATH, index_col=0) | ||
| metadata_index = ['ChemicalAnalysis', 'Author', 'Year'] | ||
| property_index = np.array(sorted(set(data.columns) - set(metadata_index))) | ||
| d = {} | ||
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| if load_atomic_fraction: | ||
| data_af = pd.read_csv(SCIGLASS_ATFRAC_DATABASE_PATH, index_col=0) | ||
| data['NumberChemicalElements'] = data_af.astype('bool').sum(axis=1) | ||
| metadata_index.append('NumberChemicalElements') | ||
| d['at_frac'] = data_af | ||
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| if load_compounds: | ||
| data_c = pd.read_csv(SCIGLASS_COMP_DATABASE_PATH, index_col=0) | ||
| data['NumberCompounds'] = data_c.astype('bool').sum(axis=1) | ||
| metadata_index.append('NumberCompounds') | ||
| d['comp'] = data_c | ||
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| d['meta'] = data[metadata_index] | ||
| d['prop'] = data[property_index] | ||
| data = pd.concat(d, axis=1) | ||
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| return data | ||
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| def sciglassOxides( | ||
| minimum_fraction_oxygen=0.3, | ||
| elements_to_remove=['S', 'H', 'C', 'Pt', 'Au', 'F', 'Cl', 'N', 'Br', 'I'], | ||
| load_compounds=False, | ||
| ): | ||
| '''Load only the oxides from SciGlass database into a pandas DataFrame | ||
| The default settings of this function follow the definion of an oxide glass | ||
| used in [1]. These can be changed with the parameters of the function. | ||
| SciGlass is a database of glass properties Copyright (c) 2019 EPAM Systems | ||
| and licensed under ODC Open Database License (ODbL). The database is hosted | ||
| on GitHub [1]. A portion of the SciGlass database is shipped with GlassPy, | ||
| so no additional downloads are necessary. | ||
| This function returns a MultiIndex pandas DataFrame. The first-level | ||
| indexes are: | ||
| at_frac : relative to the atomic fraction of the chemical elements that | ||
| make the glass. Only available if "load_atomic_fraction" is True. | ||
| comp : relative to the chemical compounds that make the glass. Only | ||
| available if "load_compounds" is True. | ||
| meta : metadata. | ||
| prop : properties. | ||
| The property column names are: | ||
| RefractiveIndex : refractive index measured at wavelenght of 589.3 nm. | ||
| Dimensionless. | ||
| AbbeNumber : Abbe number. Dimensionless. | ||
| CTE : linear coefficient of thermal expansion below the glass transition | ||
| temperature. Unit: K^{-1}. | ||
| ElasticModulus : Elastic of Young's Modulus. Unit: GPa. | ||
| Tg : glass transition temperature. Unit: K. | ||
| Tliquidus: liquidus temperature. Unit: K. | ||
| T0 to T12 : "Tn" is the temperature where the base-10 logarithm of | ||
| viscosity (in Pa.s) is "n". Example: T4 is the temperature where | ||
| log10(viscosity) = 4. Unit: K. | ||
| ViscosityAt773K to ViscosityAt2473K : value of base-10 logarithm of | ||
| viscosity (in Pa.s) at a certain temperature. Example: | ||
| ViscosityAt1073K is the log10(viscosity) at 1073 Kelvin. | ||
| Dimensionless. | ||
| Parameters | ||
| ---------- | ||
| minimum_fraction_oxygen : float | ||
| Minimum atomic fraction of oxygen for the glass to be considered an | ||
| oxide. A value between 0 and 1 is expected. | ||
| elements_to_remove : list or 1-d array or False | ||
| Iterable with the chemical elements (strings) that must not be present | ||
| in the glass in. If None then no chemical element is removed. Default | ||
| value is ['S', 'H', 'C', 'Pt', 'Au', 'F', 'Cl', 'N', 'Br', 'I']. | ||
| load_compounds : bool | ||
| If True then chemical compounds are loaded and added to the DataFrame. | ||
| Default value is False | ||
| Returns | ||
| ------- | ||
| data : pandas DataFrame | ||
| MultiIndex DataFrame containing a portion of the SciGlass database. | ||
| References | ||
| ---------- | ||
| [1] Alcobaça, E., Mastelini, S.M., Botari, T., Pimentel, B.A., Cassar, D.R., | ||
| de Carvalho, A.C.P. de L.F., and Zanotto, E.D. (2020). Explainable | ||
| Machine Learning Algorithms For Predicting Glass Transition | ||
| Temperatures. Acta Materialia 188, 92–100. | ||
| [2] Epam/SciGlass. 2019. EPAM Systems, 2019. | ||
| https://github.com/epam/SciGlass. | ||
| ''' | ||
| data = sciglass(load_compounds, load_atomic_fraction=True) | ||
| logic = data['at_frac']['O'] >= minimum_fraction_oxygen | ||
| data = data.loc[data[logic].index] | ||
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| if elements_to_remove: | ||
| for el in elements_to_remove: | ||
| logic = data['at_frac'][el] == 0 | ||
| data = data.loc[data[logic].index] | ||
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| data = removeColumnsWithOnlyZerosMultiIndex(data, 'at_frac') | ||
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| if load_compounds: | ||
| data = removeColumnsWithOnlyZerosMultiIndex(data, 'comp') | ||
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| return data |
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| Original file line number | Diff line number | Diff line change |
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| #!/usr/bin/env python3 | ||
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| def removeColumnsWithOnlyZerosMultiIndex(data, first_index): | ||
| '''Remove columns with only zeros in MultiIndex pandas DataFrames | ||
| Parameters | ||
| ---------- | ||
| data : DataFrame | ||
| MultiIndex dataframe | ||
| first_index : string | ||
| Name of the first level index to search for columns with only zeroes. | ||
| Returns | ||
| ------- | ||
| data_clean : DataFrame | ||
| DataFrame with columns with only zeroes removed. | ||
| ''' | ||
| nonzero_cols_bool = data[first_index].sum(axis=0).astype(bool) | ||
| zero_cols = data[first_index].columns.values[~nonzero_cols_bool] | ||
| drop_cols = [(first_index, col) for col in zero_cols] | ||
| data_clean = data.drop(drop_cols, axis=1) | ||
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| return data_clean |
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