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Merge pull request #50 from EducationalTestingService/release/0.3.2
Release/0.3.2
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README.rst

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@@ -91,6 +91,9 @@ Performing CFA requires users to specify in advance a model specification
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with the expected factor loading relationships. This can be done using
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the ``ModelSpecificationParser`` class.
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Note that the ``ConfirmatoryFactorAnalyzer`` class is very experimental at this point,
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so use it with caution, especially if your data are highly non-normal.
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Examples
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--------
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conda-recipe/factor_analyzer/meta.yaml

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{% set name = "factor_analyzer" %}
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{% set version = "0.3.1" %}
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{% set version = "0.3.2" %}
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{% set file_ext = "tar.gz" %}
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{% set hash_type = "sha256" %}
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{% set hash_value = "94ea4c7d46e846cc7174787adce47156cf58dc257905c878edc5181b4fa300ed" %}
@@ -13,22 +13,21 @@ source:
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build:
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number: 0
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entry_points:
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- factor_analyzer = factor_analyzer.analyze:main
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noarch: python
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script:
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- cd $SRC_DIR
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- $PYTHON setup.py install
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- "{{ PYTHON }} -m pip install . --no-deps -vv"
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requirements:
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build:
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- python==3.6
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- python >=3.6
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- setuptools
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- pandas
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- scipy
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- numpy
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- scikit-learn
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run:
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- python==3.6
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- python >=3.6
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- pandas
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- scipy
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- numpy

setup.py

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@@ -16,7 +16,7 @@ def requirements():
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setup(name='factor_analyzer',
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version='0.3.1',
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version='0.3.2',
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description='A Factor Analysis class',
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long_description=readme(),
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keywords='factor analysis',
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url="https://github.com/EducationalTestingService/factor_analyzer",
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install_requires=requirements(),
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include_package_data=True,
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entry_points={'console_scripts':
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['factor_analyzer = factor_analyzer.analyze:main']},
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classifiers=['Intended Audience :: Science/Research',
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'Intended Audience :: Developers',
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'Programming Language :: Python',
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'Programming Language :: Python :: 3.4',
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'Programming Language :: Python :: 3.5',
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'Programming Language :: Python :: 3.6',
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'Programming Language :: Python :: 3.7',
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],
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zip_safe=True)

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