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Fix building of docs with the lastest numpy and sphinx #709

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merged 14 commits into from
Jul 24, 2023
Merged

Fix building of docs with the lastest numpy and sphinx #709

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b52d5fd
Use float instead of np.float
keszybz Jul 17, 2023
b87ba7f
setup: fix git invocation for exlinks, add override
keszybz Jul 17, 2023
8320b2a
Fix CMA tanle miss align and conf modules
fmder Jul 23, 2023
9e0095c
Merge branch 'master' into keszybz-doc-build
fmder Jul 23, 2023
c3e13a9
Remove math warnings and align mathjax left
fmder Jul 24, 2023
7b337b7
Adjust doc to MetaEphemeral
fmder Jul 24, 2023
2e4b9ce
Fix title underscore too short warning
fmder Jul 24, 2023
0f05b73
Fix EDA example references
fmder Jul 24, 2023
9b7b3c8
Fix emphasis line
fmder Jul 24, 2023
9103dc2
Fix include path
fmder Jul 24, 2023
48f2214
Fix keyword
fmder Jul 24, 2023
2a5b6ec
Fixed reference to numpy tutorial
fmder Jul 24, 2023
649e5ee
Fixed reference to GA One Max
fmder Jul 24, 2023
3a764d7
Fix ref to fitness creation part
fmder Jul 24, 2023
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Fix ref to fitness creation part
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@fmder
fmder committed Jul 24, 2023
commit 3a764d71769dd8c630e7c9c086c1ff25be05f3a1
2 changes: 1 addition & 1 deletion doc/tutorials/basic/part2.rst
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Expand Up @@ -35,7 +35,7 @@ Evaluation
The evaluation is the most personal part of an evolutionary algorithm, it is
the only part of the library that you must write yourself. A typical
evaluation function takes one individual as argument and returns its fitness as
a :class:`tuple`. As shown in the :ref:`core` section, a fitness is a list of floating point values and has a
a :class:`tuple`. As shown in the :ref:`creating-types` section, a fitness is a list of floating point values and has a
property :attr:`~deap.base.Fitness.valid` to know if this individual shall be re-evaluated. The
fitness is set by setting the :attr:`~deap.base.Fitness.values` to the
associated :class:`tuple`. For example, the following evaluates the previously created individual ``ind1`` and assigns its fitness to the corresponding values.
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