diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml index 9335cd17b..9b74271d5 100644 --- a/.github/workflows/lint.yml +++ b/.github/workflows/lint.yml @@ -4,34 +4,42 @@ on: [push, pull_request] jobs: build: + # prevent this action from running on forks runs-on: ubuntu-latest strategy: max-parallel: 1 matrix: python-version: [3.9] steps: - - uses: actions/checkout@v2 - with: - fetch-depth: 0 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 - with: - python-version: ${{ matrix.python-version }} - - name: Install dependencies - run: | - python -m pip install --upgrade pip - pip install -r requirements-dev.txt --quiet - - name: black - run: | - - # Black step should fail if there are any errors - black --version - black --check --diff --color matminer - - name: pylint - run: | - pylint --fail-under=9 matminer - - name: flake8 - run: | - flake8 --version - # exit-zero treats all errors as warnings. - flake8 --count --exit-zero --max-complexity=20 --statistics matminer + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v3 + with: + python-version: ${{ matrix.python-version }} + cache: pip + cache-dependency-path: requirements-dev.txt + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -r requirements-dev.txt --quiet +# - name: mypy +# run: | +# mypy --version +# rm -rf .mypy_cache +# mypy matminer +# - name: pydocstyle +# run: | +# pydocstyle --count matminer +# - name: pylint +# run: | +# pylint matminer + - name: black + run: | + black --version + black --check --diff --color matminer + - name: flake8 + run: | + flake8 --version + flake8 --count --show-source --statistics matminer + # exit-zero treats all errors as warnings. + flake8 --count --exit-zero --max-complexity=20 --statistics matminer diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 000000000..b0a3b902c --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,70 @@ +exclude: ^(docs|.*test_files|cmd_line|dev_scripts) + +default_language_version: + python: python3 + +ci: + autoupdate_schedule: monthly + skip: [flake8, mypy, pylint] + +repos: + + - repo: https://github.com/myint/autoflake + rev: v1.4 + hooks: + - id: autoflake + args: + - --in-place + - --remove-unused-variables + - --remove-all-unused-imports + - --expand-star-imports + - --ignore-init-module-imports + + - repo: https://github.com/asottile/pyupgrade + rev: v2.32.0 + hooks: + - id: pyupgrade + args: [--py38-plus] + + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.2.0 + hooks: + - id: check-yaml + exclude: pymatgen/analysis/vesta_cutoffs.yaml + - id: end-of-file-fixer + - id: trailing-whitespace + + - repo: https://github.com/PyCQA/isort + rev: 5.10.1 + hooks: + - id: isort + args: ["--profile", "black"] + + - repo: https://github.com/psf/black + rev: 22.3.0 + hooks: + - id: black + + - repo: https://github.com/PyCQA/flake8 + rev: 4.0.1 + hooks: + - id: flake8 + + - repo: https://github.com/pre-commit/mirrors-mypy + rev: v0.950 + hooks: + - id: mypy + + - repo: local + hooks: + - id: pylint + name: pylint + entry: pylint + language: python + types: [python] + args: + [ + "-sn", + "--rcfile=pylintrc", + ] + additional_dependencies: [pylint] diff --git a/docs/_sources/dataset_summary.rst.txt b/docs/_sources/dataset_summary.rst.txt index ad34c84bc..40f219249 100644 --- a/docs/_sources/dataset_summary.rst.txt +++ b/docs/_sources/dataset_summary.rst.txt @@ -1,7 +1,7 @@ ================= Table of Datasets ================= -Find a table of all 43 datasets available in matminer here. +Find a table of all 45 datasets available in matminer here. .. list-table:: :align: left @@ -137,6 +137,12 @@ Find a table of all 43 datasets available in matminer here. * - :code:`superconductivity2018` - Dataset of ~16,000 experimental superconductivity records (critical temperatures) from Stanev et al., originally from the Japanese National Institute for Materials Science - 16414 + * - :code:`tholander_nitrides` + - A challenging data set for quantum machine learning containing a diverse set of 12.8k polymorphs in the Zn-Ti-N, Zn-Zr-N and Zn-Hf-N chemical systems + - 12815 + * - :code:`ucsb_thermoelectrics` + - Database of ~1,100 experimental thermoelectric materials from UCSB aggregated from 108 source publications and personal communications + - 1093 * - :code:`wolverton_oxides` - 4,914 perovskite oxides containing composition data, lattice constants, and formation + vacancy formation energies - 4914 @@ -2324,6 +2330,110 @@ https://doi.org/10.1038/s41524-018-0085-8 +------------------ +tholander_nitrides +------------------ +A challenging data set for quantum machine learning containing a diverse set of 12.8k polymorphs in the Zn-Ti-N, Zn-Zr-N and Zn-Hf-N chemical systems. The phase diagrams of the Ti-Zn-N, Zr-Zn-N, and Hf-Zn-N systems are determined using large-scale high-throughput density functional calculations (DFT-GGA) (PBE). In total 12,815 relaxed structures are shared alongside their energy calculated using the VASP DFT code. The High-Throughput Toolkit was used to manage the calculations. Data adapted and deduplicated from the original data on Zenodo at https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ, published under MIT licence. Collated from separate files of chemical systems and deduplicated according to identical structures matching ht_ids. Prepared in collaboration with Rhys Goodall. + +**Number of entries:** 12815 + +.. list-table:: + :align: left + :widths: 20 80 + :header-rows: 1 + + * - Column + - Description + * - :code:`material_id` + - Human readable identifier for each material. + * - :code:`ht_id` + - Unique identifier to track the calculation in httk + * - :code:`initial_structure` + - A pymatgen structure object representing the structure before relaxation. + * - :code:`final_structure` + - A pymatgen structure object representing the structure after relaxation. + * - :code:`E_vasp_per_atom` + - The VASP calculated energy per atom for the final structure, in eV/atom + * - :code:`chemical_system` + - The chemical system represented by the atoms actually contained in the structure + + + +**Reference** + +https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ + + + +**Bibtex Formatted Citations** + +.. code-block:: text + + + @article{tholander2016strong, title={Strong piezoelectric response in stable TiZnN2, ZrZnN2, and HfZnN2 found by ab initio high-throughput approach}, author={Tholander, Christopher and Andersson, CBA and Armiento, Rickard and Tasnadi, Ferenc and Alling, Bj{\"o}rn}, journal={Journal of Applied Physics}, volume={120}, number={22}, pages={225102}, year={2016}, publisher={AIP Publishing LLC} } + + + + +-------------------- +ucsb_thermoelectrics +-------------------- +Database of ~1,100 experimental thermoelectric materials from UCSB aggregated from 108 source publications and personal communications. Downloaded from Citrine. Source UCSB webpage is http://www.mrl.ucsb.edu:8080/datamine/thermoelectric.jsp. See reference for more information on original data aggregation. No duplicate entries are present, but each src may result in multiple measurements of the same materials' properties at different temperatures or conditions. + +**Number of entries:** 1093 + +.. list-table:: + :align: left + :widths: 20 80 + :header-rows: 1 + + * - Column + - Description + * - :code:`composition` + - Chemical formula. + * - :code:`crystallinity` + - Either single crystal, polycrystalline, or nanoparticles. + * - :code:`synthesis` + - Brief string describing the synthesis method + * - :code:`spacegroup` + - Spacegroup number, if available + * - :code:`rho (ohm.cm)` + - Electrical resistivity, in ohm.cm + * - :code:`S [muV/K]` + - Seebeck coefficient, in microVolts/K, if available + * - :code:`PF [W/mK^2]` + - Thermoelectric power factor, conductivity * Seebeck^2, in [W/mK^2] if available + * - :code:`zT` + - Thermoelectric figure of merit, PF * T/K, unitless, if available + * - :code:`kappa [W/mK]` + - Thermal conductivity in Watt/ meter * Kelvin, if available + * - :code:`sigma [S/cm]` + - Electrical conductivity, in Siemens/cm, if available + * - :code:`T [K]` + - Temperature in Kelvin at which these properties were obtained, if available + * - :code:`src` + - Original source of the recording. To cite the aggregator of the data, see the bibtext_refs section of this metadata. + + + +**Reference** + +https://citrination.com/datasets/150557/ + + + +**Bibtex Formatted Citations** + +.. code-block:: text + + + @article{Gaultois2013, doi = {10.1021/cm400893e}, url = {https://doi.org/10.1021/cm400893e}, year = {2013}, month = may, publisher = {American Chemical Society ({ACS})}, volume = {25}, number = {15}, pages = {2911--2920}, author = {Michael W. Gaultois and Taylor D. Sparks and Christopher K. H. Borg and Ram Seshadri and William D. Bonificio and David R. Clarke}, title = {Data-Driven Review of Thermoelectric Materials: Performance and Resource Considerations}, journal = {Chemistry of Materials} } + + @misc{Citrine Informatics, title = {UCSB Thermoelectrics Database}, howpublished = {\url{https://citrination.com/datasets/150557/}, } + + + + ---------------- wolverton_oxides ---------------- diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js index 8eb2f5e42..ad801d555 100644 --- a/docs/_static/documentation_options.js +++ b/docs/_static/documentation_options.js @@ -1,6 +1,6 @@ var DOCUMENTATION_OPTIONS = { URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'), - VERSION: '0.7.6', + VERSION: '0.7.8', LANGUAGE: 'None', COLLAPSE_INDEX: false, BUILDER: 'html', diff --git a/docs/changelog.html b/docs/changelog.html index 36953da53..a09a4f637 100644 --- a/docs/changelog.html +++ b/docs/changelog.html @@ -5,7 +5,7 @@ - MatMiner Changelog — matminer 0.7.6 documentation + MatMiner Changelog — matminer 0.7.8 documentation @@ -28,7 +28,7 @@

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    Table of Datasets

    -

    Find a table of all 43 datasets available in matminer here.

    +

    Find a table of all 45 datasets available in matminer here.

    @@ -222,6 +222,14 @@

    Table of Datasets

    + + + + + + + @@ -2361,6 +2369,110 @@

    superconductivity2018 +
    +

    tholander_nitrides

    +

    A challenging data set for quantum machine learning containing a diverse set of 12.8k polymorphs in the Zn-Ti-N, Zn-Zr-N and Zn-Hf-N chemical systems. The phase diagrams of the Ti-Zn-N, Zr-Zn-N, and Hf-Zn-N systems are determined using large-scale high-throughput density functional calculations (DFT-GGA) (PBE). In total 12,815 relaxed structures are shared alongside their energy calculated using the VASP DFT code. The High-Throughput Toolkit was used to manage the calculations. Data adapted and deduplicated from the original data on Zenodo at https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ, published under MIT licence. Collated from separate files of chemical systems and deduplicated according to identical structures matching ht_ids. Prepared in collaboration with Rhys Goodall.

    +

    Number of entries: 12815

    +

    tholander_nitrides

    A challenging data set for quantum machine learning containing a diverse set of 12.8k polymorphs in the Zn-Ti-N, Zn-Zr-N and Zn-Hf-N chemical systems

    12815

    ucsb_thermoelectrics

    Database of ~1,100 experimental thermoelectric materials from UCSB aggregated from 108 source publications and personal communications

    1093

    wolverton_oxides

    4,914 perovskite oxides containing composition data, lattice constants, and formation + vacancy formation energies

    4914

    ++++ + + + + + + + + + + + + + + + + + + + + + + + + + +

    Column

    Description

    material_id

    Human readable identifier for each material.

    ht_id

    Unique identifier to track the calculation in httk

    initial_structure

    A pymatgen structure object representing the structure before relaxation.

    final_structure

    A pymatgen structure object representing the structure after relaxation.

    E_vasp_per_atom

    The VASP calculated energy per atom for the final structure, in eV/atom

    chemical_system

    The chemical system represented by the atoms actually contained in the structure

    +

    Reference

    +

    https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ

    +

    Bibtex Formatted Citations

    +
    @article{tholander2016strong,   title={Strong piezoelectric response in stable TiZnN2, ZrZnN2, and HfZnN2 found by ab initio high-throughput approach},   author={Tholander, Christopher and Andersson, CBA and Armiento, Rickard and Tasnadi, Ferenc and Alling, Bj{\"o}rn},   journal={Journal of Applied Physics},   volume={120},   number={22},   pages={225102},   year={2016},   publisher={AIP Publishing LLC} }
+
    +
    +
    +
    +

    ucsb_thermoelectrics

    +

    Database of ~1,100 experimental thermoelectric materials from UCSB aggregated from 108 source publications and personal communications. Downloaded from Citrine. Source UCSB webpage is http://www.mrl.ucsb.edu:8080/datamine/thermoelectric.jsp. See reference for more information on original data aggregation. No duplicate entries are present, but each src may result in multiple measurements of the same materials’ properties at different temperatures or conditions.

    +

    Number of entries: 1093

    + ++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    Column

    Description

    composition

    Chemical formula.

    crystallinity

    Either single crystal, polycrystalline, or nanoparticles.

    synthesis

    Brief string describing the synthesis method

    spacegroup

    Spacegroup number, if available

    rho (ohm.cm)

    Electrical resistivity, in ohm.cm

    S [muV/K]

    Seebeck coefficient, in microVolts/K, if available

    PF [W/mK^2]

    Thermoelectric power factor, conductivity * Seebeck^2, in [W/mK^2] if available

    zT

    Thermoelectric figure of merit, PF * T/K, unitless, if available

    kappa [W/mK]

    Thermal conductivity in Watt/ meter * Kelvin, if available

    sigma [S/cm]

    Electrical conductivity, in Siemens/cm, if available

    T [K]

    Temperature in Kelvin at which these properties were obtained, if available

    src

    Original source of the recording. To cite the aggregator of the data, see the bibtext_refs section of this metadata.

    +

    Reference

    +

    https://citrination.com/datasets/150557/

    +

    Bibtex Formatted Citations

    +
    @article{Gaultois2013,   doi = {10.1021/cm400893e},   url = {https://doi.org/10.1021/cm400893e},   year = {2013},   month = may,   publisher = {American Chemical Society ({ACS})},   volume = {25},   number = {15},   pages = {2911--2920},   author = {Michael W. Gaultois and Taylor D. Sparks and Christopher K. H. Borg and Ram Seshadri and William D. Bonificio and David R. Clarke},   title = {Data-Driven Review of Thermoelectric Materials: Performance and Resource Considerations},   journal = {Chemistry of Materials} }
+
+@misc{Citrine Informatics, title = {UCSB Thermoelectrics Database}, howpublished = {\url{https://citrination.com/datasets/150557/}, }
+
    +
    +

    wolverton_oxides

    4,914 perovskite oxides containing composition data, lattice constants, and formation + vacancy formation energies. All perovskites are of the form ABO3. Adapted from a dataset presented by Emery and Wolverton.

    @@ -2491,6 +2603,8 @@

    Table of Contents

  • ricci_boltztrap_mp_tabular
  • steel_strength
  • superconductivity2018
    • +
  • tholander_nitrides
    • +
  • ucsb_thermoelectrics
  • wolverton_oxides
    • @@ -2526,7 +2640,7 @@

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    T

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    • @@ -296,6 +296,16 @@

    Submodulestest_superconductivity2018()
    +
    +
    +test_tholander_nitrides_e_form()
    +
    + +
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    +test_ucsb_thermoelectrics()
    +
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    test_wolverton_oxides()
    @@ -399,7 +409,7 @@

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Changelog","MatMiner Contributors","Guide to adding datasets to matminer","Table of Datasets","Predicting bulk moduli with matminer","bandstructure","matminer (Materials Data Mining)","Installing matminer","matminer package","matminer.data_retrieval package","matminer.data_retrieval.tests package","matminer.datasets package","matminer.datasets.tests package","matminer.featurizers package","matminer.featurizers.composition package","matminer.featurizers.composition.tests package","matminer.featurizers.site package","matminer.featurizers.site.tests package","matminer.featurizers.structure package","matminer.featurizers.structure.tests package","matminer.featurizers.tests package","matminer.featurizers.utils package","matminer.featurizers.utils.tests package","matminer.figrecipes package","matminer.figrecipes.tests package","matminer.utils package","matminer.utils.data_files package","matminer.utils.tests 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\ No newline at end of file diff --git a/docs_rst/dataset_summary.rst b/docs_rst/dataset_summary.rst index ad34c84bc..40f219249 100644 --- a/docs_rst/dataset_summary.rst +++ b/docs_rst/dataset_summary.rst @@ -1,7 +1,7 @@ ================= Table of Datasets ================= -Find a table of all 43 datasets available in matminer here. +Find a table of all 45 datasets available in matminer here. .. list-table:: :align: left @@ -137,6 +137,12 @@ Find a table of all 43 datasets available in matminer here. * - :code:`superconductivity2018` - Dataset of ~16,000 experimental superconductivity records (critical temperatures) from Stanev et al., originally from the Japanese National Institute for Materials Science - 16414 + * - :code:`tholander_nitrides` + - A challenging data set for quantum machine learning containing a diverse set of 12.8k polymorphs in the Zn-Ti-N, Zn-Zr-N and Zn-Hf-N chemical systems + - 12815 + * - :code:`ucsb_thermoelectrics` + - Database of ~1,100 experimental thermoelectric materials from UCSB aggregated from 108 source publications and personal communications + - 1093 * - :code:`wolverton_oxides` - 4,914 perovskite oxides containing composition data, lattice constants, and formation + vacancy formation energies - 4914 @@ -2324,6 +2330,110 @@ https://doi.org/10.1038/s41524-018-0085-8 +------------------ +tholander_nitrides +------------------ +A challenging data set for quantum machine learning containing a diverse set of 12.8k polymorphs in the Zn-Ti-N, Zn-Zr-N and Zn-Hf-N chemical systems. The phase diagrams of the Ti-Zn-N, Zr-Zn-N, and Hf-Zn-N systems are determined using large-scale high-throughput density functional calculations (DFT-GGA) (PBE). In total 12,815 relaxed structures are shared alongside their energy calculated using the VASP DFT code. The High-Throughput Toolkit was used to manage the calculations. Data adapted and deduplicated from the original data on Zenodo at https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ, published under MIT licence. Collated from separate files of chemical systems and deduplicated according to identical structures matching ht_ids. Prepared in collaboration with Rhys Goodall. + +**Number of entries:** 12815 + +.. list-table:: + :align: left + :widths: 20 80 + :header-rows: 1 + + * - Column + - Description + * - :code:`material_id` + - Human readable identifier for each material. + * - :code:`ht_id` + - Unique identifier to track the calculation in httk + * - :code:`initial_structure` + - A pymatgen structure object representing the structure before relaxation. + * - :code:`final_structure` + - A pymatgen structure object representing the structure after relaxation. + * - :code:`E_vasp_per_atom` + - The VASP calculated energy per atom for the final structure, in eV/atom + * - :code:`chemical_system` + - The chemical system represented by the atoms actually contained in the structure + + + +**Reference** + +https://zenodo.org/record/5530535#.YjJ3ZhDMJLQ + + + +**Bibtex Formatted Citations** + +.. code-block:: text + + + @article{tholander2016strong, title={Strong piezoelectric response in stable TiZnN2, ZrZnN2, and HfZnN2 found by ab initio high-throughput approach}, author={Tholander, Christopher and Andersson, CBA and Armiento, Rickard and Tasnadi, Ferenc and Alling, Bj{\"o}rn}, journal={Journal of Applied Physics}, volume={120}, number={22}, pages={225102}, year={2016}, publisher={AIP Publishing LLC} } + + + + +-------------------- +ucsb_thermoelectrics +-------------------- +Database of ~1,100 experimental thermoelectric materials from UCSB aggregated from 108 source publications and personal communications. Downloaded from Citrine. Source UCSB webpage is http://www.mrl.ucsb.edu:8080/datamine/thermoelectric.jsp. See reference for more information on original data aggregation. No duplicate entries are present, but each src may result in multiple measurements of the same materials' properties at different temperatures or conditions. + +**Number of entries:** 1093 + +.. list-table:: + :align: left + :widths: 20 80 + :header-rows: 1 + + * - Column + - Description + * - :code:`composition` + - Chemical formula. + * - :code:`crystallinity` + - Either single crystal, polycrystalline, or nanoparticles. + * - :code:`synthesis` + - Brief string describing the synthesis method + * - :code:`spacegroup` + - Spacegroup number, if available + * - :code:`rho (ohm.cm)` + - Electrical resistivity, in ohm.cm + * - :code:`S [muV/K]` + - Seebeck coefficient, in microVolts/K, if available + * - :code:`PF [W/mK^2]` + - Thermoelectric power factor, conductivity * Seebeck^2, in [W/mK^2] if available + * - :code:`zT` + - Thermoelectric figure of merit, PF * T/K, unitless, if available + * - :code:`kappa [W/mK]` + - Thermal conductivity in Watt/ meter * Kelvin, if available + * - :code:`sigma [S/cm]` + - Electrical conductivity, in Siemens/cm, if available + * - :code:`T [K]` + - Temperature in Kelvin at which these properties were obtained, if available + * - :code:`src` + - Original source of the recording. To cite the aggregator of the data, see the bibtext_refs section of this metadata. + + + +**Reference** + +https://citrination.com/datasets/150557/ + + + +**Bibtex Formatted Citations** + +.. code-block:: text + + + @article{Gaultois2013, doi = {10.1021/cm400893e}, url = {https://doi.org/10.1021/cm400893e}, year = {2013}, month = may, publisher = {American Chemical Society ({ACS})}, volume = {25}, number = {15}, pages = {2911--2920}, author = {Michael W. Gaultois and Taylor D. Sparks and Christopher K. H. Borg and Ram Seshadri and William D. Bonificio and David R. Clarke}, title = {Data-Driven Review of Thermoelectric Materials: Performance and Resource Considerations}, journal = {Chemistry of Materials} } + + @misc{Citrine Informatics, title = {UCSB Thermoelectrics Database}, howpublished = {\url{https://citrination.com/datasets/150557/}, } + + + + ---------------- wolverton_oxides ---------------- diff --git a/matminer/__init__.py b/matminer/__init__.py index aed57348c..894cebca0 100644 --- a/matminer/__init__.py +++ b/matminer/__init__.py @@ -1 +1 @@ -__version__ = "0.7.6" +__version__ = "0.7.8" diff --git a/matminer/data_retrieval/retrieve_MPDS.py b/matminer/data_retrieval/retrieve_MPDS.py index 54e467768..18daa4792 100755 --- a/matminer/data_retrieval/retrieve_MPDS.py +++ b/matminer/data_retrieval/retrieve_MPDS.py @@ -9,9 +9,9 @@ import sys import time import warnings +from urllib.parse import urlencode import httplib2 -from six.moves.urllib_parse import urlencode from matminer.data_retrieval.retrieve_base import BaseDataRetrieval diff --git a/matminer/featurizers/composition/alloy.py b/matminer/featurizers/composition/alloy.py index 9179762c7..e30073f86 100644 --- a/matminer/featurizers/composition/alloy.py +++ b/matminer/featurizers/composition/alloy.py @@ -766,7 +766,7 @@ def compute_lambda(yang_delta, entropy): float """ if yang_delta != 0: - return entropy / yang_delta ** 2 + return entropy / yang_delta**2 else: return 0 @@ -791,8 +791,8 @@ def compute_gamma_radii(miracle_radius_stats): mrmin = miracle_radius_stats["min"] mrmax = miracle_radius_stats["max"] - numerator = 1 - np.sqrt((mrmean * mrmin + mrmin ** 2) / (mrmean + mrmin) ** 2) - denominator = 1 - np.sqrt((mrmean * mrmax + mrmax ** 2) / (mrmean + mrmax) ** 2) + numerator = 1 - np.sqrt((mrmean * mrmin + mrmin**2) / (mrmean + mrmin) ** 2) + denominator = 1 - np.sqrt((mrmean * mrmax + mrmax**2) / (mrmean + mrmax) ** 2) return numerator / denominator @staticmethod diff --git a/matminer/featurizers/site/fingerprint.py b/matminer/featurizers/site/fingerprint.py index 52b8f017f..47db90107 100644 --- a/matminer/featurizers/site/fingerprint.py +++ b/matminer/featurizers/site/fingerprint.py @@ -261,7 +261,7 @@ def featurize(self, struct, idx): site_list.append(n) this_av_inv_drel += 1.0 / (neigh_dist[j][1]) this_av_inv_drel = this_av_inv_drel / float(this_cn) - d_fac = this_av_inv_drel ** self.dist_exp + d_fac = this_av_inv_drel**self.dist_exp for cn in range(max(2, prev_cn + 1), min(this_cn + 1, 13)): # Set all OPs of non-CN-complying neighbor environments # to zero if applicable. diff --git a/matminer/featurizers/site/rdf.py b/matminer/featurizers/site/rdf.py index c4dd5820f..5b4ff743b 100644 --- a/matminer/featurizers/site/rdf.py +++ b/matminer/featurizers/site/rdf.py @@ -74,7 +74,7 @@ def g2(eta, rs, cutoff): Returns: (float) Gaussian radial symmetry function. """ - ridge = np.exp(-eta * (rs ** 2.0) / (cutoff ** 2.0)) * GaussianSymmFunc.cosine_cutoff(rs, cutoff) + ridge = np.exp(-eta * (rs**2.0) / (cutoff**2.0)) * GaussianSymmFunc.cosine_cutoff(rs, cutoff) return ridge.sum() @staticmethod @@ -118,7 +118,7 @@ def g4(etas, zetas, gammas, neigh_dist, neigh_coords, cutoff): ind = 0 for eta in etas: # Compute the eta term - eta_term = np.exp(-eta * (r_ij ** 2.0 + r_ik ** 2.0 + r_jk ** 2.0) / (cutoff ** 2.0)) * cutoff_fun + eta_term = np.exp(-eta * (r_ij**2.0 + r_ik**2.0 + r_jk**2.0) / (cutoff**2.0)) * cutoff_fun for zeta in zetas: for gamma in gammas: term = (1.0 + gamma * cos_theta) ** zeta * eta_term diff --git a/matminer/featurizers/site/tests/test_fingerprint.py b/matminer/featurizers/site/tests/test_fingerprint.py index 598e9c9e2..7b648dbf6 100644 --- a/matminer/featurizers/site/tests/test_fingerprint.py +++ b/matminer/featurizers/site/tests/test_fingerprint.py @@ -68,9 +68,9 @@ def test_off_center_cscl(self): self.assertArrayAlmostEqual(-1 * site1[8:], site2[8:]) # Make sure the site-ones are as expected. - right_dist = 4.209 * np.sqrt(0.45 ** 2 + 2 * 0.5 ** 2) + right_dist = 4.209 * np.sqrt(0.45**2 + 2 * 0.5**2) right_xdist = 4.209 * 0.45 - left_dist = 4.209 * np.sqrt(0.55 ** 2 + 2 * 0.5 ** 2) + left_dist = 4.209 * np.sqrt(0.55**2 + 2 * 0.5**2) left_xdist = 4.209 * 0.55 self.assertAlmostEqual( 4 diff --git a/matminer/featurizers/structure/bonding.py b/matminer/featurizers/structure/bonding.py index 2e0527396..3c4499ecb 100644 --- a/matminer/featurizers/structure/bonding.py +++ b/matminer/featurizers/structure/bonding.py @@ -421,7 +421,7 @@ def _approximate_bonds(self, local_bonds): d0 = u_mends[0] - l_mends[0] d1 = u_mends[1] - l_mends[1] - d = (d0 ** 2.0 + d1 ** 2.0) ** 0.5 + d = (d0**2.0 + d1**2.0) ** 0.5 if not d_min: d_min = d nearest = [abss] diff --git a/matminer/featurizers/structure/order.py b/matminer/featurizers/structure/order.py index 04f1c26da..b3349b7e8 100644 --- a/matminer/featurizers/structure/order.py +++ b/matminer/featurizers/structure/order.py @@ -62,7 +62,7 @@ def featurize(self, s): raise ValueError("Disordered structure support not built yet.") total_rad = 0 for site in s: - total_rad += site.specie.atomic_radius ** 3 + total_rad += site.specie.atomic_radius**3 output.append(4 * math.pi * total_rad / (3 * s.volume)) return output diff --git a/matminer/featurizers/structure/tests/test_composite.py b/matminer/featurizers/structure/tests/test_composite.py index 10aec7000..d2015fea4 100644 --- a/matminer/featurizers/structure/tests/test_composite.py +++ b/matminer/featurizers/structure/tests/test_composite.py @@ -1,5 +1,5 @@ -import unittest import os +import unittest from monty.serialization import loadfn diff --git a/matminer/featurizers/utils/grdf.py b/matminer/featurizers/utils/grdf.py index 7433f07d4..04f9e5aba 100644 --- a/matminer/featurizers/utils/grdf.py +++ b/matminer/featurizers/utils/grdf.py @@ -65,7 +65,7 @@ def volume(self, cutoff): (float): Volume of bin """ - results = integrate.quad(lambda x: 4.0 * pi * self(x) * x ** 2.0, 0, cutoff) + results = integrate.quad(lambda x: 4.0 * pi * self(x) * x**2.0, 0, cutoff) if results[1] > 1e-5: raise ValueError("Numerical integration fails for this function." " Please implement analytic integral") return results[0] @@ -92,7 +92,7 @@ def __call__(self, r_ij): ) def volume(self, cutoff): - return 4.0 / 3 * np.pi * (min(self.start + self.width, cutoff) ** 3 - self.start ** 3) + return 4.0 / 3 * np.pi * (min(self.start + self.width, cutoff) ** 3 - self.start**3) class Gaussian(AbstractPairwise): @@ -117,7 +117,7 @@ def volume(self, cutoff): * self.width * ( np.sqrt(pi) - * (2 * self.center ** 2 + self.width ** 2) + * (2 * self.center**2 + self.width**2) * (erf((cutoff - self.center) / self.width) + erf(self.center / self.width)) + 2 * self.width * (self.center * self(0) - (self.center + cutoff) * self(cutoff)) ) @@ -143,7 +143,7 @@ def volume(self, cutoff): 4 * pi * (((self.a * cutoff) ** 2 - 2) * np.sin(self.a * cutoff) + 2 * self.a * cutoff * np.cos(self.a * cutoff)) - / self.a ** 3 + / self.a**3 ) @@ -170,7 +170,7 @@ def volume(self, cutoff): + 2 * self.a * cutoff * np.sin(self.a * cutoff) - 2 ) - / self.a ** 3 + / self.a**3 ) diff --git a/matminer/featurizers/utils/stats.py b/matminer/featurizers/utils/stats.py index 70080c184..5a8617137 100644 --- a/matminer/featurizers/utils/stats.py +++ b/matminer/featurizers/utils/stats.py @@ -173,7 +173,7 @@ def skewness(data_lst, weights=None): u2 = np.dot(weights, np.power(diff, 2)) / total_weight if np.isclose(u3, 0): return 0 - return u3 / u2 ** 1.5 + return u3 / u2**1.5 @staticmethod def kurtosis(data_lst, weights=None): @@ -203,7 +203,7 @@ def kurtosis(data_lst, weights=None): u2 = np.dot(weights, diff_sq) if np.isclose(u4, 0): return 0 - return u4 / u2 ** 2 * total_weight + return u4 / u2**2 * total_weight @staticmethod def geom_std_dev(data_lst, weights=None): diff --git a/matminer/featurizers/utils/tests/test_grdf.py b/matminer/featurizers/utils/tests/test_grdf.py index dd8089017..3b04a9ccb 100644 --- a/matminer/featurizers/utils/tests/test_grdf.py +++ b/matminer/featurizers/utils/tests/test_grdf.py @@ -35,7 +35,7 @@ def test_gaussian(self): def test_histogram(self): h = Histogram(1, 4) self.assertArrayAlmostEqual([0, 1, 0], h([0.5, 2, 5])) - self.assertAlmostEqual(h.volume(10), 4 / 3.0 * np.pi * (5 ** 3 - 1 ** 3)) + self.assertAlmostEqual(h.volume(10), 4 / 3.0 * np.pi * (5**3 - 1**3)) def test_cosine(self): c = Cosine(2) diff --git a/matminer/utils/kernels.py b/matminer/utils/kernels.py index 60a34bebc..2face5e25 100644 --- a/matminer/utils/kernels.py +++ b/matminer/utils/kernels.py @@ -18,4 +18,4 @@ def gaussian_kernel(arr0, arr1, SIGMA): kernel trick. """ diff = arr0 - arr1 - return np.exp(-np.linalg.norm(diff.A1, ord=2) ** 2 / 2 / SIGMA ** 2) + return np.exp(-np.linalg.norm(diff.A1, ord=2) ** 2 / 2 / SIGMA**2) diff --git a/requirements-dev.txt b/requirements-dev.txt index 6017685ce..0e7c9a599 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -1,7 +1,7 @@ -pytest==7.1.0 +pytest==7.1.2 pytest-cov==3.0.0 -coverage==6.2 +coverage==6.3.3 coveralls==3.3.1 -flake8==4.0.1 -black==21.12b0 -pylint==2.12.2 +flake8 +black +pylint \ No newline at end of file diff --git a/requirements-optional.txt b/requirements-optional.txt index 898ead77c..60b25e4c4 100644 --- a/requirements-optional.txt +++ b/requirements-optional.txt @@ -5,16 +5,16 @@ # Generally, don't mess with this file unless you know what you are doing. ## MPDS -ujson==5.1.0 -jmespath==0.10.0 -httplib2==0.20.2 +ujson==5.2.0 +jmespath==1.0.0 +httplib2==0.20.4 ase==3.22.1 ## dscribe dscribe==1.2.1 ## MDF-forge -mdf-forge==0.7.7 +mdf-forge==0.8.0 ## AFLOW aflow==0.0.11 diff --git a/requirements.txt b/requirements.txt index 286e73adb..c766b70b3 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,12 +1,11 @@ numpy==1.22.3 requests==2.27.1 -pandas==1.4.1 -tqdm==4.63.0 -pymongo==4.0.2 -six==1.16.0 +pandas==1.4.2 +tqdm==4.64.0 +pymongo==4.1.1 future==0.18.2 -scikit_learn==1.0.1 -sympy==1.10 -monty==2022.1.12.1 -pymatgen==2022.3.7 -jsonschema==4.4.0 +scikit_learn==1.1.0 +sympy==1.10.1 +monty==2022.4.26 +pymatgen==2022.5.17 +jsonschema==4.5.1 \ No newline at end of file diff --git a/setup.py b/setup.py index 36bd87429..a99349193 100644 --- a/setup.py +++ b/setup.py @@ -28,7 +28,7 @@ if __name__ == "__main__": setup( name='matminer', - version='0.7.6', + version='0.7.8', description='matminer is a library that contains tools for data ' 'mining in Materials Science', long_description=open(os.path.join(module_dir, 'README.md')).read(), @@ -42,9 +42,8 @@ install_requires=reqs_list, extras_require=extras_dict, classifiers=[ - 'Programming Language :: Python :: 3.6', - 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', + 'Programming Language :: Python :: 3.9', 'Development Status :: 4 - Beta', 'Intended Audience :: Science/Research', 'Intended Audience :: System Administrators',