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make release-tag: Merge branch 'master' into stable
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HISTORY.md

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# History
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## v0.7.2 - 2023-05-09
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This release adds support for Pandas 2.0! It also fixes a bug in the `load_demo` function.
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### Bugs Fixed
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* load_demo raises urllib.error.HTTPError: HTTP Error 403: Forbidden - Issue [#284](https://github.com/sdv-dev/CTGAN/issues/284) by @amontanez24
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### Maintenance
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* Remove upper bound for pandas - Issue [#282](https://github.com/sdv-dev/CTGAN/issues/282) by @frances-h
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## v0.7.1 - 2023-02-23
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This release fixes a bug that prevented the `CTGAN` model from being saved after sampling.
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### Bugs Fixed
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* Cannot save CTGANSynthesizer after sampling (TypeError) - Issue [#270](https://github.com/sdv-dev/CTGAN/issues/270) by @pvk-developer
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## v0.7.0 - 2023-01-20
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This release adds support for python 3.10 and drops support for python 3.6. It also fixes a couple of the most common warnings that were surfacing.

ctgan/__init__.py

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__author__ = 'DataCebo, Inc.'
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__email__ = 'info@sdv.dev'
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__version__ = '0.7.1'
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__version__ = '0.7.2.dev2'
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from ctgan.demo import load_demo
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from ctgan.synthesizers.ctgan import CTGAN

ctgan/demo.py

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import pandas as pd
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DEMO_URL = 'http://ctgan-data.s3.amazonaws.com/census.csv.gz'
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DEMO_URL = 'http://ctgan-demo.s3.amazonaws.com/census.csv.gz'
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def load_demo():

setup.cfg

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[bumpversion]
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current_version = 0.7.1
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current_version = 0.7.2.dev2
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commit = True
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tag = True
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parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\.(?P<release>[a-z]+)(?P<candidate>\d+))?

setup.py

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'packaging>=20,<22',
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"numpy>=1.20.0,<2;python_version<'3.10'",
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"numpy>=1.23.3,<2;python_version>='3.10'",
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"pandas>=1.1.3,<2;python_version<'3.10'",
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"pandas>=1.3.4,<2;python_version>='3.10'",
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"pandas>=1.1.3;python_version<'3.10'",
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"pandas>=1.3.4;python_version>='3.10'",
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"scikit-learn>=1.1.3,<2;python_version>='3.10'",
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"torch>=1.8.0,<2;python_version<'3.10'",
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"torch>=1.11.0,<2;python_version>='3.10'",
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test_suite='tests',
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tests_require=tests_require,
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url='https://github.com/sdv-dev/CTGAN',
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version='0.7.1',
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version='0.7.2.dev2',
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zip_safe=False,
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)

tasks.py

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if _validate_python_version(line):
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requirement = re.match(r'[^>]*', line).group(0)
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requirement = re.sub(r"""['",]""", '', requirement)
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version = re.search(r'>=?[^(,|#)]*', line).group(0)
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version = re.search(r'>=?(\d\.?)+', line).group(0)
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if version:
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version = re.sub(r'>=?', '==', version)
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version = re.sub(r"""['",]""", '', version)

tests/integration/__init__.py

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"""Integration testing subpackage."""
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"""Subpackage for integration testing of synthesizers."""

tests/integration/synthesizer/test_ctgan.py

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# - uniform (assert p-value > 0.05)
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# - gaussian (assert p-value > 0.05)
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# - inversely correlated (assert correlation < 0)
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pass
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def test_categorical():
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# - uniform (assert p-value > 0.05)
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# - very skewed / biased? (assert p-value > 0.05)
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# - inversely correlated (assert correlation < 0)
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pass
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def test_categorical_log_frequency():
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# - uniform (assert p-value > 0.05)
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# - very skewed / biased? (assert p-value > 0.05)
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# - inversely correlated (assert correlation < 0)
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pass
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def test_mixed():
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"""Test training the CTGAN synthesizer on a small mixed-type dataset."""
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# assert the distribution of the samples is close to the distribution of the data
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# using a kstest for continuous + a cstest for categorical.
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pass
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def test_conditional():
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"""Test training the CTGAN synthesizer and sampling conditioned on a categorical."""
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# verify that conditioning increases the likelihood of getting a sample with the specified
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# categorical value
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pass
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def test_batch_size_pack_size():
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"""Test that if batch size is not a multiple of pack size, it raises a sane error."""
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pass
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def test_ctgan_save_and_load(tmpdir):

tests/integration/synthesizer/test_tvae.py

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"""Test training the TVAE synthesizer on a small continuous dataset."""
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# verify that the distribution of the samples is close to the distribution of the data
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# using a kstest.
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pass
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def test_categorical():
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"""Test training the TVAE synthesizer on a small categorical dataset."""
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# verify that the distribution of the samples is close to the distribution of the data
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# using a cstest.
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pass
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def test_mixed():
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"""Test training the TVAE synthesizer on a small mixed-type dataset."""
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# verify that the distribution of the samples is close to the distribution of the data
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# using a kstest for continuous + a cstest for categorical.
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pass
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def test__loss_function():

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