check_augment_no_data

Call this function to perform tests. If a tests fails, an informative error
will be thrown. Otherwise silent.
Test when <code>strict = FALSE</code>:<ul>
<li>None</li>
</ul>Additional tests when <code>strict = TRUE</code>:<ul>
<li><code>aug(model)</code> either returns an informative error or produces output
that passes <code>check_tibble()</code>.</li>
<li>If the output passes <code>check_tibble</code>, will issue warning when:<ul>
<li>Augmented data is missing rows from original data.</li>
<li>Augmented data is missing columns from original data.</li>
<li>Original data has rownames but ugmented data is missing <code>.rownames</code>
column.</li>
</ul></li>
</ul>

Provides a number of testthat tests that can be
used to verify that tidy(), glance() and augment() methods meet
consistent specifications. This allows methods for the same generic to
be spread across multiple packages, since all of those packages can
make the same guarantees to users about returned objects.

Alex Hayes

modeltests

Testing Infrastructure for Broom Model Generics

Simon Couch

check_augment_no_data function

<dl><dt>aug</dt>
<dd>An augment method. For example, <code>augment.betareg</code>.</dd>
<dt>model</dt>
<dd>A fit model object to call the augment method on.</dd>
<dt>passed_data</dt>
<dd>The dataset that <code>model</code> was original fit on that
<code>aug</code> should try to reconstruct when neither <code>data</code> nor <code>newdata</code> is
specified.</dd>
<dt>strict</dt>
<dd>Logical indicating whether the strict version of tests should be used. Defaults
to <code>TRUE</code>.</dd></dl>

Arguments

Call this function to perform tests. If a tests fails, an informative error
will be thrown. Otherwise silent.
Test when <code>strict = FALSE</code>:<ul>
<li>None</li>
</ul>

Additional tests when <code>strict = TRUE</code>:<ul>
<li><code>aug(model)</code> either returns an informative error or produces output
that passes <code>check_tibble()</code>.</li>
<li>If the output passes <code>check_tibble</code>, will issue warning when:<ul>
<li>Augmented data is missing rows from original data.</li>
<li>Augmented data is missing columns from original data.</li>
<li>Original data has rownames but ugmented data is missing <code>.rownames</code>
column.</li>
</ul></li>
</ul>

Check an augment method when no data or newdata is passed — check_augment_no_data

<dl>

<dt>aug</dt>
<dd>An augment method. For example, <code>augment.betareg</code>.</dd>


<dt>model</dt>
<dd>A fit model object to call the augment method on.</dd>


<dt>passed_data</dt>
<dd>The dataset that <code>model</code> was original fit on that
<code>aug</code> should try to reconstruct when neither <code>data</code> nor <code>newdata</code> is
specified.</dd>


<dt>strict</dt>
<dd>Logical indicating whether the strict version of tests should be used. Defaults
to <code>TRUE</code>.</dd>

</dl>

check_augment_no_data: Check an augment method when no data or newdata is passed

Description

Usage

Value

Arguments