.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "user-guide\11-imod5-files.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_user-guide_11-imod5-files.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_user-guide_11-imod5-files.py:


Reading and writing iMOD5 files in Python
=========================================

This example demonstrates how to work with iMOD5 files in Python using the
`imod` package. It shows how to save, read, and manipulate iMOD5 files,
including handling temporary directories and glob patterns for file selection.

For a full explanation of the iMOD5 file formats, see the `iMOD5 documentation
<https://oss.deltares.nl/documents/d/imod/imod_user_manual_v5_6_1#page=747>`_.

For a full overview of the supported iMOD5 features in iMOD Python, see
:doc:`../faq/imod5_backwards_compatibility`.

.. GENERATED FROM PYTHON SOURCE LINES 16-18

.. code-block:: Python
   :dedent: 1










.. GENERATED FROM PYTHON SOURCE LINES 20-30

Raster data (IDF)
-----------------

Raster data in iMOD5 is stored in IDF files, which is a binary format for
raster data. The `imod.idf` module provides functions to read and write IDF
files. One IDF can only store data in two dimensions: y and x. It is similar
to GeoTIFF in this regard.

We'll start off with some example data to work with. Let's load a layer model
with geological layers.

.. GENERATED FROM PYTHON SOURCE LINES 31-37

.. code-block:: Python


    import imod

    layermodel = imod.data.hondsrug_layermodel()
    layermodel






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    </style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 21MB
    Dimensions:  (layer: 13, y: 200, x: 500)
    Coordinates:
      * x        (x) float64 4kB 2.375e+05 2.375e+05 2.376e+05 ... 2.5e+05 2.5e+05
      * y        (y) float64 2kB 5.64e+05 5.64e+05 5.639e+05 ... 5.59e+05 5.59e+05
        dx       float64 8B ...
        dy       float64 8B ...
      * layer    (layer) int32 52B 1 2 3 4 5 6 7 8 9 10 11 12 13
    Data variables:
        top      (layer, y, x) float32 5MB ...
        bottom   (layer, y, x) float32 5MB ...
        k        (layer, y, x) float32 5MB ...
        idomain  (layer, y, x) float32 5MB ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-abd8b06d-7ac2-42b9-9ee9-f91d043d460a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-abd8b06d-7ac2-42b9-9ee9-f91d043d460a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>layer</span>: 13</li><li><span class='xr-has-index'>y</span>: 200</li><li><span class='xr-has-index'>x</span>: 500</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-59d1c8d6-c11d-480b-b0ac-233a17834180' class='xr-section-summary-in' type='checkbox'  checked><label for='section-59d1c8d6-c11d-480b-b0ac-233a17834180' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.375e+05 2.375e+05 ... 2.5e+05</div><input id='attrs-6e8aa477-34da-49d1-9175-844564bfe3dd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e8aa477-34da-49d1-9175-844564bfe3dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4d10a3e-51a8-4949-814c-6394212d39e9' class='xr-var-data-in' type='checkbox'><label for='data-d4d10a3e-51a8-4949-814c-6394212d39e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([237512.5, 237537.5, 237562.5, ..., 249937.5, 249962.5, 249987.5],
          shape=(500,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.64e+05 5.64e+05 ... 5.59e+05</div><input id='attrs-ee2c5ac6-98df-4d21-82f2-51f1d0ebd584' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee2c5ac6-98df-4d21-82f2-51f1d0ebd584' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52aa184a-edce-486a-b445-de221d772d74' class='xr-var-data-in' type='checkbox'><label for='data-52aa184a-edce-486a-b445-de221d772d74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([563987.5, 563962.5, 563937.5, 563912.5, 563887.5, 563862.5, 563837.5,
           563812.5, 563787.5, 563762.5, 563737.5, 563712.5, 563687.5, 563662.5,
           563637.5, 563612.5, 563587.5, 563562.5, 563537.5, 563512.5, 563487.5,
           563462.5, 563437.5, 563412.5, 563387.5, 563362.5, 563337.5, 563312.5,
           563287.5, 563262.5, 563237.5, 563212.5, 563187.5, 563162.5, 563137.5,
           563112.5, 563087.5, 563062.5, 563037.5, 563012.5, 562987.5, 562962.5,
           562937.5, 562912.5, 562887.5, 562862.5, 562837.5, 562812.5, 562787.5,
           562762.5, 562737.5, 562712.5, 562687.5, 562662.5, 562637.5, 562612.5,
           562587.5, 562562.5, 562537.5, 562512.5, 562487.5, 562462.5, 562437.5,
           562412.5, 562387.5, 562362.5, 562337.5, 562312.5, 562287.5, 562262.5,
           562237.5, 562212.5, 562187.5, 562162.5, 562137.5, 562112.5, 562087.5,
           562062.5, 562037.5, 562012.5, 561987.5, 561962.5, 561937.5, 561912.5,
           561887.5, 561862.5, 561837.5, 561812.5, 561787.5, 561762.5, 561737.5,
           561712.5, 561687.5, 561662.5, 561637.5, 561612.5, 561587.5, 561562.5,
           561537.5, 561512.5, 561487.5, 561462.5, 561437.5, 561412.5, 561387.5,
           561362.5, 561337.5, 561312.5, 561287.5, 561262.5, 561237.5, 561212.5,
           561187.5, 561162.5, 561137.5, 561112.5, 561087.5, 561062.5, 561037.5,
           561012.5, 560987.5, 560962.5, 560937.5, 560912.5, 560887.5, 560862.5,
           560837.5, 560812.5, 560787.5, 560762.5, 560737.5, 560712.5, 560687.5,
           560662.5, 560637.5, 560612.5, 560587.5, 560562.5, 560537.5, 560512.5,
           560487.5, 560462.5, 560437.5, 560412.5, 560387.5, 560362.5, 560337.5,
           560312.5, 560287.5, 560262.5, 560237.5, 560212.5, 560187.5, 560162.5,
           560137.5, 560112.5, 560087.5, 560062.5, 560037.5, 560012.5, 559987.5,
           559962.5, 559937.5, 559912.5, 559887.5, 559862.5, 559837.5, 559812.5,
           559787.5, 559762.5, 559737.5, 559712.5, 559687.5, 559662.5, 559637.5,
           559612.5, 559587.5, 559562.5, 559537.5, 559512.5, 559487.5, 559462.5,
           559437.5, 559412.5, 559387.5, 559362.5, 559337.5, 559312.5, 559287.5,
           559262.5, 559237.5, 559212.5, 559187.5, 559162.5, 559137.5, 559112.5,
           559087.5, 559062.5, 559037.5, 559012.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-864d455b-736a-4782-96ba-15f2a5d93603' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-864d455b-736a-4782-96ba-15f2a5d93603' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a19e9c8-b3c1-4425-b82e-2e2311ba7e7b' class='xr-var-data-in' type='checkbox'><label for='data-9a19e9c8-b3c1-4425-b82e-2e2311ba7e7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-717943a6-d216-4f14-b14e-864a92989349' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-717943a6-d216-4f14-b14e-864a92989349' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dec37ed-0fa1-4ee3-83a5-b4aac65c126e' class='xr-var-data-in' type='checkbox'><label for='data-8dec37ed-0fa1-4ee3-83a5-b4aac65c126e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer</span></div><div class='xr-var-dims'>(layer)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12 13</div><input id='attrs-3c818ad0-a68b-4cbf-b418-8fcb19bfaf27' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3c818ad0-a68b-4cbf-b418-8fcb19bfaf27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56ffad19-80d5-4947-85a4-6ae2e1baa3b5' class='xr-var-data-in' type='checkbox'><label for='data-56ffad19-80d5-4947-85a4-6ae2e1baa3b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92a67aff-8ff4-4ea9-82d3-69de46b3a184' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92a67aff-8ff4-4ea9-82d3-69de46b3a184' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>top</span></div><div class='xr-var-dims'>(layer, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-78316d1b-8cc0-432b-8f86-1922a0d38bf6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78316d1b-8cc0-432b-8f86-1922a0d38bf6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f347a60b-08d0-4d69-b561-f93713f72695' class='xr-var-data-in' type='checkbox'><label for='data-f347a60b-08d0-4d69-b561-f93713f72695' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1300000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bottom</span></div><div class='xr-var-dims'>(layer, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-75fc30aa-1ec9-4471-9e6f-8f4261eed931' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-75fc30aa-1ec9-4471-9e6f-8f4261eed931' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea2e390f-f64a-4614-84ff-9d42a8c96657' class='xr-var-data-in' type='checkbox'><label for='data-ea2e390f-f64a-4614-84ff-9d42a8c96657' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1300000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>k</span></div><div class='xr-var-dims'>(layer, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6188d113-15b0-4adb-acae-8cf8e1b576e5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6188d113-15b0-4adb-acae-8cf8e1b576e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5f86abe-72cb-4ce4-86eb-2ce72dca557b' class='xr-var-data-in' type='checkbox'><label for='data-b5f86abe-72cb-4ce4-86eb-2ce72dca557b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1300000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>idomain</span></div><div class='xr-var-dims'>(layer, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd773b79-1e75-4adc-a24a-f53e1a62f285' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd773b79-1e75-4adc-a24a-f53e1a62f285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b434278f-9b3a-4c56-b76c-9d0a683ea29e' class='xr-var-data-in' type='checkbox'><label for='data-b434278f-9b3a-4c56-b76c-9d0a683ea29e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1300000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f76e3c81-076c-4ce9-b1e0-0374fa495ff6' class='xr-section-summary-in' type='checkbox'  ><label for='section-f76e3c81-076c-4ce9-b1e0-0374fa495ff6' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-af93d304-c8a5-4d34-95dd-c3f93ec0ad29' class='xr-index-data-in' type='checkbox'/><label for='index-af93d304-c8a5-4d34-95dd-c3f93ec0ad29' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([237512.5, 237537.5, 237562.5, 237587.5, 237612.5, 237637.5, 237662.5,
           237687.5, 237712.5, 237737.5,
           ...
           249762.5, 249787.5, 249812.5, 249837.5, 249862.5, 249887.5, 249912.5,
           249937.5, 249962.5, 249987.5],
          dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-6e3f69e5-1146-4236-a83c-4e11658be274' class='xr-index-data-in' type='checkbox'/><label for='index-6e3f69e5-1146-4236-a83c-4e11658be274' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([563987.5, 563962.5, 563937.5, 563912.5, 563887.5, 563862.5, 563837.5,
           563812.5, 563787.5, 563762.5,
           ...
           559237.5, 559212.5, 559187.5, 559162.5, 559137.5, 559112.5, 559087.5,
           559062.5, 559037.5, 559012.5],
          dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>layer</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9780e28f-1ebc-4c41-bd84-c942dd9ad1a0' class='xr-index-data-in' type='checkbox'/><label for='index-9780e28f-1ebc-4c41-bd84-c942dd9ad1a0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], dtype=&#x27;int32&#x27;, name=&#x27;layer&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ed65f6fd-2514-47d8-adb0-896b25a6d75d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ed65f6fd-2514-47d8-adb0-896b25a6d75d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 38-40

This dataset contains multiple variables. We can take a closer look at the
the "top" variable, which represents the top of every layer.

.. GENERATED FROM PYTHON SOURCE LINES 40-44

.. code-block:: Python


    top = layermodel["top"]
    top






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    .xr-attrs dt {
      white-space: nowrap;
      overflow: hidden;
      text-overflow: ellipsis;
      padding-right: 10px;
    }

    .xr-var-name:hover,
    .xr-var-dims:hover,
    .xr-var-dtype:hover,
    .xr-attrs dt:hover {
      overflow: visible;
      width: auto;
      z-index: 1;
    }

    .xr-var-attrs,
    .xr-var-data,
    .xr-index-data {
      display: none;
      border-top: 2px dotted var(--xr-background-color);
      padding-bottom: 20px !important;
      padding-top: 10px !important;
    }

    .xr-var-attrs-in + label,
    .xr-var-data-in + label,
    .xr-index-data-in + label {
      padding: 0 1px;
    }

    .xr-var-attrs-in:checked ~ .xr-var-attrs,
    .xr-var-data-in:checked ~ .xr-var-data,
    .xr-index-data-in:checked ~ .xr-index-data {
      display: block;
    }

    .xr-var-data > table {
      float: right;
    }

    .xr-var-data > pre,
    .xr-index-data > pre,
    .xr-var-data > table > tbody > tr {
      background-color: transparent !important;
    }

    .xr-var-name span,
    .xr-var-data,
    .xr-index-name div,
    .xr-index-data,
    .xr-attrs {
      padding-left: 25px !important;
    }

    .xr-attrs,
    .xr-var-attrs,
    .xr-var-data,
    .xr-index-data {
      grid-column: 1 / -1;
    }

    dl.xr-attrs {
      padding: 0;
      margin: 0;
      display: grid;
      grid-template-columns: 125px auto;
    }

    .xr-attrs dt,
    .xr-attrs dd {
      padding: 0;
      margin: 0;
      float: left;
      padding-right: 10px;
      width: auto;
    }

    .xr-attrs dt {
      font-weight: normal;
      grid-column: 1;
    }

    .xr-attrs dt:hover span {
      display: inline-block;
      background: var(--xr-background-color);
      padding-right: 10px;
    }

    .xr-attrs dd {
      grid-column: 2;
      white-space: pre-wrap;
      word-break: break-all;
    }

    .xr-icon-database,
    .xr-icon-file-text2,
    .xr-no-icon {
      display: inline-block;
      vertical-align: middle;
      width: 1em;
      height: 1.5em !important;
      stroke-width: 0;
      stroke: currentColor;
      fill: currentColor;
    }

    .xr-var-attrs-in:checked + label > .xr-icon-file-text2,
    .xr-var-data-in:checked + label > .xr-icon-database,
    .xr-index-data-in:checked + label > .xr-icon-database {
      color: var(--xr-font-color0);
      filter: drop-shadow(1px 1px 5px var(--xr-font-color2));
      stroke-width: 0.8px;
    }
    </style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;top&#x27; (layer: 13, y: 200, x: 500)&gt; Size: 5MB
    [1300000 values with dtype=float32]
    Coordinates:
      * x        (x) float64 4kB 2.375e+05 2.375e+05 2.376e+05 ... 2.5e+05 2.5e+05
      * y        (y) float64 2kB 5.64e+05 5.64e+05 5.639e+05 ... 5.59e+05 5.59e+05
        dx       float64 8B ...
        dy       float64 8B ...
      * layer    (layer) int32 52B 1 2 3 4 5 6 7 8 9 10 11 12 13</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'top'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>layer</span>: 13</li><li><span class='xr-has-index'>y</span>: 200</li><li><span class='xr-has-index'>x</span>: 500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ccb6e9a4-a65d-49ed-bb01-6c9af81bd514' class='xr-array-in' type='checkbox' checked><label for='section-ccb6e9a4-a65d-49ed-bb01-6c9af81bd514' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[1300000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-b3813068-050c-4d52-97cd-a85dbd780261' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b3813068-050c-4d52-97cd-a85dbd780261' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.375e+05 2.375e+05 ... 2.5e+05</div><input id='attrs-863eac3b-c4af-43e0-b60c-8456911fbc0d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-863eac3b-c4af-43e0-b60c-8456911fbc0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2582ef3-d062-4fd2-b62e-e5629195da54' class='xr-var-data-in' type='checkbox'><label for='data-c2582ef3-d062-4fd2-b62e-e5629195da54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([237512.5, 237537.5, 237562.5, ..., 249937.5, 249962.5, 249987.5],
          shape=(500,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.64e+05 5.64e+05 ... 5.59e+05</div><input id='attrs-ed761789-e8ac-4684-8124-4da4a5afc308' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed761789-e8ac-4684-8124-4da4a5afc308' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78822c73-6c71-4efa-ae22-ea5cdcb681cc' class='xr-var-data-in' type='checkbox'><label for='data-78822c73-6c71-4efa-ae22-ea5cdcb681cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([563987.5, 563962.5, 563937.5, 563912.5, 563887.5, 563862.5, 563837.5,
           563812.5, 563787.5, 563762.5, 563737.5, 563712.5, 563687.5, 563662.5,
           563637.5, 563612.5, 563587.5, 563562.5, 563537.5, 563512.5, 563487.5,
           563462.5, 563437.5, 563412.5, 563387.5, 563362.5, 563337.5, 563312.5,
           563287.5, 563262.5, 563237.5, 563212.5, 563187.5, 563162.5, 563137.5,
           563112.5, 563087.5, 563062.5, 563037.5, 563012.5, 562987.5, 562962.5,
           562937.5, 562912.5, 562887.5, 562862.5, 562837.5, 562812.5, 562787.5,
           562762.5, 562737.5, 562712.5, 562687.5, 562662.5, 562637.5, 562612.5,
           562587.5, 562562.5, 562537.5, 562512.5, 562487.5, 562462.5, 562437.5,
           562412.5, 562387.5, 562362.5, 562337.5, 562312.5, 562287.5, 562262.5,
           562237.5, 562212.5, 562187.5, 562162.5, 562137.5, 562112.5, 562087.5,
           562062.5, 562037.5, 562012.5, 561987.5, 561962.5, 561937.5, 561912.5,
           561887.5, 561862.5, 561837.5, 561812.5, 561787.5, 561762.5, 561737.5,
           561712.5, 561687.5, 561662.5, 561637.5, 561612.5, 561587.5, 561562.5,
           561537.5, 561512.5, 561487.5, 561462.5, 561437.5, 561412.5, 561387.5,
           561362.5, 561337.5, 561312.5, 561287.5, 561262.5, 561237.5, 561212.5,
           561187.5, 561162.5, 561137.5, 561112.5, 561087.5, 561062.5, 561037.5,
           561012.5, 560987.5, 560962.5, 560937.5, 560912.5, 560887.5, 560862.5,
           560837.5, 560812.5, 560787.5, 560762.5, 560737.5, 560712.5, 560687.5,
           560662.5, 560637.5, 560612.5, 560587.5, 560562.5, 560537.5, 560512.5,
           560487.5, 560462.5, 560437.5, 560412.5, 560387.5, 560362.5, 560337.5,
           560312.5, 560287.5, 560262.5, 560237.5, 560212.5, 560187.5, 560162.5,
           560137.5, 560112.5, 560087.5, 560062.5, 560037.5, 560012.5, 559987.5,
           559962.5, 559937.5, 559912.5, 559887.5, 559862.5, 559837.5, 559812.5,
           559787.5, 559762.5, 559737.5, 559712.5, 559687.5, 559662.5, 559637.5,
           559612.5, 559587.5, 559562.5, 559537.5, 559512.5, 559487.5, 559462.5,
           559437.5, 559412.5, 559387.5, 559362.5, 559337.5, 559312.5, 559287.5,
           559262.5, 559237.5, 559212.5, 559187.5, 559162.5, 559137.5, 559112.5,
           559087.5, 559062.5, 559037.5, 559012.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9df7398b-9af9-4ea8-8ce8-e8da9d687595' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9df7398b-9af9-4ea8-8ce8-e8da9d687595' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e65e42a-116f-404d-b8bc-84ed268a5345' class='xr-var-data-in' type='checkbox'><label for='data-9e65e42a-116f-404d-b8bc-84ed268a5345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4ed562b8-7357-46f5-aa8f-1657fec5740b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ed562b8-7357-46f5-aa8f-1657fec5740b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-183a66a7-3101-4d0a-86f3-67a00ae65e17' class='xr-var-data-in' type='checkbox'><label for='data-183a66a7-3101-4d0a-86f3-67a00ae65e17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer</span></div><div class='xr-var-dims'>(layer)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12 13</div><input id='attrs-77f00248-ce98-4168-b50f-c382970a0d9d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-77f00248-ce98-4168-b50f-c382970a0d9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e5e47cd-baaf-4c07-97b4-5d1b91161e3f' class='xr-var-data-in' type='checkbox'><label for='data-0e5e47cd-baaf-4c07-97b4-5d1b91161e3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6068950d-61e7-4894-bffd-4f0ad419dbfe' class='xr-section-summary-in' type='checkbox'  ><label for='section-6068950d-61e7-4894-bffd-4f0ad419dbfe' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e2864d2f-8d95-418f-84a9-6ffdbe76ea38' class='xr-index-data-in' type='checkbox'/><label for='index-e2864d2f-8d95-418f-84a9-6ffdbe76ea38' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([237512.5, 237537.5, 237562.5, 237587.5, 237612.5, 237637.5, 237662.5,
           237687.5, 237712.5, 237737.5,
           ...
           249762.5, 249787.5, 249812.5, 249837.5, 249862.5, 249887.5, 249912.5,
           249937.5, 249962.5, 249987.5],
          dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0a7e970f-f6f1-4cd9-9290-614b64f250b2' class='xr-index-data-in' type='checkbox'/><label for='index-0a7e970f-f6f1-4cd9-9290-614b64f250b2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([563987.5, 563962.5, 563937.5, 563912.5, 563887.5, 563862.5, 563837.5,
           563812.5, 563787.5, 563762.5,
           ...
           559237.5, 559212.5, 559187.5, 559162.5, 559137.5, 559112.5, 559087.5,
           559062.5, 559037.5, 559012.5],
          dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>layer</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-44c7f3af-6289-48c6-b24c-c313d44a3b44' class='xr-index-data-in' type='checkbox'/><label for='index-44c7f3af-6289-48c6-b24c-c313d44a3b44' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], dtype=&#x27;int32&#x27;, name=&#x27;layer&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-acf8277c-9682-4222-9559-650a03f1e680' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-acf8277c-9682-4222-9559-650a03f1e680' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 45-48

Note that this DataArray has three dimensions: layer, y, x.

Let's create a temporary directory to store our IDF files.

.. GENERATED FROM PYTHON SOURCE LINES 49-52

.. code-block:: Python


    tmpdir = imod.util.temporary_directory()








.. GENERATED FROM PYTHON SOURCE LINES 53-58

As mentioned before, one IDF can only store data in two dimensions: y and x.
iMOD Python therefore will save a 3D dataset as multiple IDF files. The layer
index is stored in the file name, as the ``_l*`` suffix. iMOD Python will take
the last part of the provided path as the name. We therefore end our path with
``top``. This will result in files named ``top_l1.idf``, ``top_l2.idf``, etc.

.. GENERATED FROM PYTHON SOURCE LINES 59-63

.. code-block:: Python


    idf_dir = tmpdir / "idf"
    imod.idf.save(idf_dir / "top", top)








.. GENERATED FROM PYTHON SOURCE LINES 64-66

The IDF files are now stored in the temporary directory. We can list them
using the `glob` method, which allows us to use wildcards to match file names

.. GENERATED FROM PYTHON SOURCE LINES 66-71

.. code-block:: Python

    from pprint import pprint

    idf_files = list(idf_dir.glob("*"))
    pprint(idf_files)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    [WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l1.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l10.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l11.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l12.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l13.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l2.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l3.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l4.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l5.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l6.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l7.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l8.idf'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/idf/top_l9.idf')]




.. GENERATED FROM PYTHON SOURCE LINES 72-78

We can also read the IDF files back into a DataArray, we can either do that by
directly providing a list of filenames (``idf_files``) to open, or by
providing a path with a wildcard pattern (``idf_dir / "top*"``). The latter is
more convenient, as it will automatically match all files that start with
``"top"`` in ``idf_dir``. This means we can easily open the data without
having to specify each file individually.

.. GENERATED FROM PYTHON SOURCE LINES 79-83

.. code-block:: Python


    reloaded_top = imod.idf.open(idf_dir / "top*")
    reloaded_top






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    <div class="output_subarea output_html rendered_html output_result">
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    </style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;top&#x27; (layer: 13, y: 200, x: 500)&gt; Size: 5MB
    dask.array&lt;stack, shape=(13, 200, 500), dtype=float32, chunksize=(1, 200, 500), chunktype=numpy.ndarray&gt;
    Coordinates:
      * x        (x) float64 4kB 2.375e+05 2.375e+05 2.376e+05 ... 2.5e+05 2.5e+05
      * y        (y) float64 2kB 5.64e+05 5.64e+05 5.639e+05 ... 5.59e+05 5.59e+05
        dx       float64 8B 25.0
        dy       float64 8B -25.0
      * layer    (layer) int64 104B 1 2 3 4 5 6 7 8 9 10 11 12 13</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'top'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>layer</span>: 13</li><li><span class='xr-has-index'>y</span>: 200</li><li><span class='xr-has-index'>x</span>: 500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0182ad76-9b44-45fb-82d1-182ec3c4b456' class='xr-array-in' type='checkbox' checked><label for='section-0182ad76-9b44-45fb-82d1-182ec3c4b456' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 200, 500), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
        <tr>
            <td>
                <table style="border-collapse: collapse;">
                    <thead>
                        <tr>
                            <td> </td>
                            <th> Array </th>
                            <th> Chunk </th>
                        </tr>
                    </thead>
                    <tbody>
                    
                        <tr>
                            <th> Bytes </th>
                            <td> 4.96 MiB </td>
                            <td> 390.62 kiB </td>
                        </tr>
                    
                        <tr>
                            <th> Shape </th>
                            <td> (13, 200, 500) </td>
                            <td> (1, 200, 500) </td>
                        </tr>
                        <tr>
                            <th> Dask graph </th>
                            <td colspan="2"> 13 chunks in 27 graph layers </td>
                        </tr>
                        <tr>
                            <th> Data type </th>
                            <td colspan="2"> float32 numpy.ndarray </td>
                        </tr>
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          shape=(500,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.64e+05 5.64e+05 ... 5.59e+05</div><input id='attrs-7ecce9c2-5a65-4c51-9e36-d6430b7ac5e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ecce9c2-5a65-4c51-9e36-d6430b7ac5e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f31b3d96-cb22-4b5d-ae6c-b8ad48722302' class='xr-var-data-in' type='checkbox'><label for='data-f31b3d96-cb22-4b5d-ae6c-b8ad48722302' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([563987.5, 563962.5, 563937.5, 563912.5, 563887.5, 563862.5, 563837.5,
           563812.5, 563787.5, 563762.5, 563737.5, 563712.5, 563687.5, 563662.5,
           563637.5, 563612.5, 563587.5, 563562.5, 563537.5, 563512.5, 563487.5,
           563462.5, 563437.5, 563412.5, 563387.5, 563362.5, 563337.5, 563312.5,
           563287.5, 563262.5, 563237.5, 563212.5, 563187.5, 563162.5, 563137.5,
           563112.5, 563087.5, 563062.5, 563037.5, 563012.5, 562987.5, 562962.5,
           562937.5, 562912.5, 562887.5, 562862.5, 562837.5, 562812.5, 562787.5,
           562762.5, 562737.5, 562712.5, 562687.5, 562662.5, 562637.5, 562612.5,
           562587.5, 562562.5, 562537.5, 562512.5, 562487.5, 562462.5, 562437.5,
           562412.5, 562387.5, 562362.5, 562337.5, 562312.5, 562287.5, 562262.5,
           562237.5, 562212.5, 562187.5, 562162.5, 562137.5, 562112.5, 562087.5,
           562062.5, 562037.5, 562012.5, 561987.5, 561962.5, 561937.5, 561912.5,
           561887.5, 561862.5, 561837.5, 561812.5, 561787.5, 561762.5, 561737.5,
           561712.5, 561687.5, 561662.5, 561637.5, 561612.5, 561587.5, 561562.5,
           561537.5, 561512.5, 561487.5, 561462.5, 561437.5, 561412.5, 561387.5,
           561362.5, 561337.5, 561312.5, 561287.5, 561262.5, 561237.5, 561212.5,
           561187.5, 561162.5, 561137.5, 561112.5, 561087.5, 561062.5, 561037.5,
           561012.5, 560987.5, 560962.5, 560937.5, 560912.5, 560887.5, 560862.5,
           560837.5, 560812.5, 560787.5, 560762.5, 560737.5, 560712.5, 560687.5,
           560662.5, 560637.5, 560612.5, 560587.5, 560562.5, 560537.5, 560512.5,
           560487.5, 560462.5, 560437.5, 560412.5, 560387.5, 560362.5, 560337.5,
           560312.5, 560287.5, 560262.5, 560237.5, 560212.5, 560187.5, 560162.5,
           560137.5, 560112.5, 560087.5, 560062.5, 560037.5, 560012.5, 559987.5,
           559962.5, 559937.5, 559912.5, 559887.5, 559862.5, 559837.5, 559812.5,
           559787.5, 559762.5, 559737.5, 559712.5, 559687.5, 559662.5, 559637.5,
           559612.5, 559587.5, 559562.5, 559537.5, 559512.5, 559487.5, 559462.5,
           559437.5, 559412.5, 559387.5, 559362.5, 559337.5, 559312.5, 559287.5,
           559262.5, 559237.5, 559212.5, 559187.5, 559162.5, 559137.5, 559112.5,
           559087.5, 559062.5, 559037.5, 559012.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dx</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.0</div><input id='attrs-cf4d6b51-8d45-4d7a-a737-bb80f07415ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf4d6b51-8d45-4d7a-a737-bb80f07415ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a508edb6-290d-40d6-a087-700c4ea162d9' class='xr-var-data-in' type='checkbox'><label for='data-a508edb6-290d-40d6-a087-700c4ea162d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(25.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dy</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-25.0</div><input id='attrs-cffe0149-c0b8-4cb4-9ae1-3868957abffb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cffe0149-c0b8-4cb4-9ae1-3868957abffb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed09cbba-964c-4f85-b528-babdb61e9a81' class='xr-var-data-in' type='checkbox'><label for='data-ed09cbba-964c-4f85-b528-babdb61e9a81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(-25.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer</span></div><div class='xr-var-dims'>(layer)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12 13</div><input id='attrs-5d723d9f-b0f5-4ba4-9c22-e0069a803c8e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5d723d9f-b0f5-4ba4-9c22-e0069a803c8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22d82153-3455-4d02-bd28-6fcf9d911ca4' class='xr-var-data-in' type='checkbox'><label for='data-22d82153-3455-4d02-bd28-6fcf9d911ca4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cb2dd3c4-e04a-4665-be9b-58bff040020d' class='xr-section-summary-in' type='checkbox'  ><label for='section-cb2dd3c4-e04a-4665-be9b-58bff040020d' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-545fc907-bf25-4c97-81d4-28cc86a8facf' class='xr-index-data-in' type='checkbox'/><label for='index-545fc907-bf25-4c97-81d4-28cc86a8facf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([237512.5, 237537.5, 237562.5, 237587.5, 237612.5, 237637.5, 237662.5,
           237687.5, 237712.5, 237737.5,
           ...
           249762.5, 249787.5, 249812.5, 249837.5, 249862.5, 249887.5, 249912.5,
           249937.5, 249962.5, 249987.5],
          dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-aea95607-2b60-48f5-bb0b-cb5e84f3e32c' class='xr-index-data-in' type='checkbox'/><label for='index-aea95607-2b60-48f5-bb0b-cb5e84f3e32c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([563987.5, 563962.5, 563937.5, 563912.5, 563887.5, 563862.5, 563837.5,
           563812.5, 563787.5, 563762.5,
           ...
           559237.5, 559212.5, 559187.5, 559162.5, 559137.5, 559112.5, 559087.5,
           559062.5, 559037.5, 559012.5],
          dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>layer</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-313cb3bc-499c-48e2-8305-6dc91999a7a3' class='xr-index-data-in' type='checkbox'/><label for='index-313cb3bc-499c-48e2-8305-6dc91999a7a3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], dtype=&#x27;int64&#x27;, name=&#x27;layer&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b42106ad-ef70-4418-bb85-6b7e0d3a7d97' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b42106ad-ef70-4418-bb85-6b7e0d3a7d97' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 84-92

Note that the reloaded DataArray is represented differently than the original
DataArray. This is because the DataArray is lazily loaded as a dask array,
which means that the data is not actually loaded into memory until it is
accessed. For example when plotting or saving data. This allows for more
efficient memory usage, especially when working with large datasets. See the
:doc:`06-lazy-evaluation` for more information.

Let's plot the top layer:

.. GENERATED FROM PYTHON SOURCE LINES 93-96

.. code-block:: Python


    reloaded_top.sel(layer=1).plot()




.. image-sg:: /user-guide/images/sphx_glr_11-imod5-files_001.png
   :alt: dx = 25.0, dy = -25.0, layer = 1
   :srcset: /user-guide/images/sphx_glr_11-imod5-files_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <matplotlib.collections.QuadMesh object at 0x00000251C8F5C770>



.. GENERATED FROM PYTHON SOURCE LINES 97-107

Point data (IPF)
----------------

iMOD Stores point data in iMOD Point Format (IPF) files, which is a text
format for point data. The `imod.ipf` module provides functions to read and
write IPF files. Point data can be used to store timeseries of point
observations, such as groundwater heads, as well as borelogs. In this example,
we will focus on timeseries.

Let's load some example point data.

.. GENERATED FROM PYTHON SOURCE LINES 108-112

.. code-block:: Python


    heads = imod.data.head_observations()
    heads






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>Unnamed: 0</th>
          <th>id</th>
          <th>Filternummer</th>
          <th>time</th>
          <th>head</th>
          <th>filt_top</th>
          <th>filt_bot</th>
          <th>Meetpunt tov m NAP</th>
          <th>x</th>
          <th>y</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>0</td>
          <td>B12A1745001</td>
          <td>1</td>
          <td>2007-12-28</td>
          <td>NaN</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2</td>
          <td>B12A1745001</td>
          <td>1</td>
          <td>2008-01-28</td>
          <td>9.03</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
        </tr>
        <tr>
          <th>2</th>
          <td>3</td>
          <td>B12A1745001</td>
          <td>1</td>
          <td>2008-02-14</td>
          <td>8.70</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
        </tr>
        <tr>
          <th>3</th>
          <td>4</td>
          <td>B12A1745001</td>
          <td>1</td>
          <td>2008-02-28</td>
          <td>8.53</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
        </tr>
        <tr>
          <th>4</th>
          <td>5</td>
          <td>B12A1745001</td>
          <td>1</td>
          <td>2008-03-17</td>
          <td>8.63</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
        </tr>
        <tr>
          <th>...</th>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
        </tr>
        <tr>
          <th>60374</th>
          <td>92</td>
          <td>B17E2244001</td>
          <td>1</td>
          <td>2019-05-14</td>
          <td>15.44</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
        </tr>
        <tr>
          <th>60375</th>
          <td>93</td>
          <td>B17E2244001</td>
          <td>1</td>
          <td>2019-05-28</td>
          <td>15.28</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
        </tr>
        <tr>
          <th>60376</th>
          <td>94</td>
          <td>B17E2244001</td>
          <td>1</td>
          <td>2019-06-14</td>
          <td>15.13</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
        </tr>
        <tr>
          <th>60377</th>
          <td>95</td>
          <td>B17E2244001</td>
          <td>1</td>
          <td>2019-06-28</td>
          <td>14.88</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
        </tr>
        <tr>
          <th>60378</th>
          <td>98</td>
          <td>B17E2244001</td>
          <td>1</td>
          <td>2019-08-14</td>
          <td>14.53</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
        </tr>
      </tbody>
    </table>
    <p>60379 rows × 10 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 113-115

Let's plot a timeseries for one specific observation point, for example the
observation point with ID "B12A1745001".

.. GENERATED FROM PYTHON SOURCE LINES 116-120

.. code-block:: Python


    head_selected = heads.loc[heads["id"] == "B12A1745001"]
    head_selected.sort_values("time").plot(x="time", y="head")




.. image-sg:: /user-guide/images/sphx_glr_11-imod5-files_002.png
   :alt: 11 imod5 files
   :srcset: /user-guide/images/sphx_glr_11-imod5-files_002.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <Axes: xlabel='time'>



.. GENERATED FROM PYTHON SOURCE LINES 121-126

We can save this point data to an IPF file. The `imod.ipf.save` function
allows us to save the point data to a file. We can specify the path where we
want to save the file, as well as the data to save. Make sure to specify itype
as 1, which is the type for timeseries data. The path should end with the name
you want to give to your IPF.

.. GENERATED FROM PYTHON SOURCE LINES 127-131

.. code-block:: Python


    ipf_dir = tmpdir / "ipf"
    imod.ipf.save(ipf_dir / "heads", heads, itype=1)








.. GENERATED FROM PYTHON SOURCE LINES 132-134

The IPF files are now stored in the temporary directory. Let's print a list of
files:

.. GENERATED FROM PYTHON SOURCE LINES 135-139

.. code-block:: Python


    ipf_files = list(ipf_dir.glob("*"))
    pprint(ipf_files)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    [WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1745001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1745002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1747001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1747002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1748001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1749001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1750001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1750002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1751001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1752001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1752002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1753001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1754001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1754002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1755001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1756001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1756002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1757001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1762001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1762002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1763001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1763002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1765001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1766001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1766002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1767001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1767002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1792001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1793001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1793002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1805001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1805002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1806001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1806002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1820001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1822001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1822002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1822003.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1898001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1898002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1899001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1900001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1901001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1902001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1903001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1903002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1904001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1905001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1906001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1906002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1907001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1907002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1908001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1909001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1909002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B12A1910001.txt'),
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     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0877001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0885001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0886001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0887001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0888001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0889001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0890001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0891001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0892001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0893001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0894001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B13C0895001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A0276001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1520001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1521001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1522001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1522002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1523001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1523002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1579001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1579002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17A1579003.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0095001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0095002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0095003.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0096002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0096003.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0267001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0267002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0267003.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0268001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0268002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0269001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0269002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0270001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0270002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0271001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0271002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0272001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0272002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0273001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0273002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0274001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0275001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0276001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0277001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0277002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0278001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0278002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0279001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B0279002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1887001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1887002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1888001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1888002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1889001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1890001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1891001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1892001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17B1892002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E1510001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E1510002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E1511001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E1512001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2221001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2221002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2221003.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2221004.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2222001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2222002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2223001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2223002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2224001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2224002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2225001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2225002.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2225003.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2225004.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/B17E2244001.txt'),
     WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/ipf/heads.ipf')]




.. GENERATED FROM PYTHON SOURCE LINES 140-142

Notice that timeseries are stored in a single textfile per observation point.
We can read the IPF file and accompanying text files back into a DataFrame.

.. GENERATED FROM PYTHON SOURCE LINES 143-147

.. code-block:: Python


    reloaded_heads = imod.ipf.read(ipf_dir / "heads.ipf")
    reloaded_heads






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>time</th>
          <th>unnamed: 0</th>
          <th>filternummer</th>
          <th>head</th>
          <th>filt_top</th>
          <th>filt_bot</th>
          <th>meetpunt tov m nap</th>
          <th>x</th>
          <th>y</th>
          <th>id</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>2007-12-28</td>
          <td>0</td>
          <td>1</td>
          <td>NaN</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
          <td>B12A1745001</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2008-01-28</td>
          <td>2</td>
          <td>1</td>
          <td>9.03</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
          <td>B12A1745001</td>
        </tr>
        <tr>
          <th>2</th>
          <td>2008-02-14</td>
          <td>3</td>
          <td>1</td>
          <td>8.70</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
          <td>B12A1745001</td>
        </tr>
        <tr>
          <th>3</th>
          <td>2008-02-28</td>
          <td>4</td>
          <td>1</td>
          <td>8.53</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
          <td>B12A1745001</td>
        </tr>
        <tr>
          <th>4</th>
          <td>2008-03-17</td>
          <td>5</td>
          <td>1</td>
          <td>8.63</td>
          <td>9.29</td>
          <td>8.29</td>
          <td>9.86</td>
          <td>226410</td>
          <td>563800</td>
          <td>B12A1745001</td>
        </tr>
        <tr>
          <th>...</th>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
          <td>...</td>
        </tr>
        <tr>
          <th>60374</th>
          <td>2019-05-14</td>
          <td>92</td>
          <td>1</td>
          <td>15.44</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
          <td>B17E2244001</td>
        </tr>
        <tr>
          <th>60375</th>
          <td>2019-05-28</td>
          <td>93</td>
          <td>1</td>
          <td>15.28</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
          <td>B17E2244001</td>
        </tr>
        <tr>
          <th>60376</th>
          <td>2019-06-14</td>
          <td>94</td>
          <td>1</td>
          <td>15.13</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
          <td>B17E2244001</td>
        </tr>
        <tr>
          <th>60377</th>
          <td>2019-06-28</td>
          <td>95</td>
          <td>1</td>
          <td>14.88</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
          <td>B17E2244001</td>
        </tr>
        <tr>
          <th>60378</th>
          <td>2019-08-14</td>
          <td>98</td>
          <td>1</td>
          <td>14.53</td>
          <td>8.64</td>
          <td>7.64</td>
          <td>16.08</td>
          <td>240586</td>
          <td>543605</td>
          <td>B17E2244001</td>
        </tr>
      </tbody>
    </table>
    <p>60379 rows × 10 columns</p>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 148-155

Line data (GEN)
---------------

iMOD stores line data in GEN files, which is a binary format for line data.
The `imod.gen` module provides functions to read and write GEN files. We'll
create some dummy line data to store in a GEN file. iMOD5 primarily uses GEN
to specify Horizontal Flow Barriers (HFB).

.. GENERATED FROM PYTHON SOURCE LINES 156-165

.. code-block:: Python


    import shapely

    x = [0.0, 14.0, 36.0, 50.0, 70.0]
    y = [0.0, 20.0, 10.0, 30.0, 40.0]

    ls = shapely.LineString(zip(x, y))
    ls





.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <LINESTRING (0 0, 14 20, 36 10, 50 30, 70 40)>



.. GENERATED FROM PYTHON SOURCE LINES 166-168

We now have a geometry, but there is no data associated with it yet. Let's
create a GeoDataFrame with some data to associate with the line.

.. GENERATED FROM PYTHON SOURCE LINES 169-174

.. code-block:: Python


    import geopandas as gpd

    gdf = gpd.GeoDataFrame([100.0], geometry=[ls], columns=["resistance"])








.. GENERATED FROM PYTHON SOURCE LINES 175-177

We can save this line data to a GEN file with the
:doc:`/api/generated/io/imod.formats.gen.write` function.

.. GENERATED FROM PYTHON SOURCE LINES 178-188

.. code-block:: Python


    gen_dir = tmpdir / "gen"
    # We'll have to create the directory first, as it does not exist yet.
    gen_dir.mkdir(exist_ok=True)

    imod.gen.write(
        gen_dir / "barrier.gen",
        gdf,
    )








.. GENERATED FROM PYTHON SOURCE LINES 189-190

Let's check that the file is saved in the specified directory.

.. GENERATED FROM PYTHON SOURCE LINES 191-195

.. code-block:: Python


    gen_files = list(gen_dir.glob("*"))
    pprint(gen_files)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    [WindowsPath('C:/BuildAgent/temp/buildTmp/tmpbv347zcx/gen/barrier.gen')]




.. GENERATED FROM PYTHON SOURCE LINES 196-197

We can read the GEN file back into a GeoDataFrame with the `imod.gen.read`

.. GENERATED FROM PYTHON SOURCE LINES 198-202

.. code-block:: Python


    reloaded_gdf = imod.gen.read(gen_dir / "barrier.gen")
    reloaded_gdf






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>resistance</th>
          <th>feature_type</th>
          <th>geometry</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>100.0</td>
          <td>line</td>
          <td>LINESTRING (0 0, 14 20, 36 10, 50 30, 70 40)</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 203-209

The GEN file also supports storing "3D data", which allows you to store
vertically oriented polygons, which you can use to insert
partially-penetrating horizontal flow barriers in iMOD5 and iMOD Python.

Let's create some 3D data first. iMOD Python has a convenience function
to create a 3D polygon conveniently.

.. GENERATED FROM PYTHON SOURCE LINES 210-220

.. code-block:: Python


    ztop = [0.0, 0.0, -10.0, 0.0, 0.0]
    zbottom = [-20.0, -20.0, -20.0, -20.0, -20.0]

    zpolygon = imod.prepare.linestring_to_trapezoid_zpolygons(x, y, ztop, zbottom)

    gdf_polygon = gpd.GeoDataFrame(
        [100.0, 100.0, 100.0, 100.0], geometry=zpolygon, columns=["resistance"]
    )








.. GENERATED FROM PYTHON SOURCE LINES 221-226

.. code-block:: Python

    imod.gen.write(
        gen_dir / "barrier_3d.gen",
        gdf_polygon,
    )








.. GENERATED FROM PYTHON SOURCE LINES 227-243

1D Network (ISG)
----------------

iMOD5 stores store 1D networks in ISG files, which is a binary format
primarily for surface water datasets. It supports all kinds of extra features
such as associated bathymetries and weirs.

Given its complexity, ISG is not yet supported in iMOD Python. The workaround
is to rasterize the ISGfiles to IDF files using the iMOD5 BATCH function
ISGGRID.

Legend files (LEG)
------------------

iMOD5 uses LEG files to store legend information for plotting. For example,
the following LEG file defines a color legend for groundwater surface levels:

.. GENERATED FROM PYTHON SOURCE LINES 244-274

.. code-block:: Python


    legend_str = """\
    24,1,1,1,1,1,1,1
    UPPERBND,LOWERBND,IRED,IGREEN,IBLUE,DOMAIN
    200.0000,10.00000,75,0,0,"> 10.0 m"
    10.00000,6.000000,115,0,0,"6.0-10.0 m"
    6.000000,4.000000,166,0,0,"4.0-6.0 m"
    4.000000,3.800000,191,0,0,"3.8-4.0 m"
    3.800000,3.600000,217,0,0,"3.6-3.8 m"
    3.600000,3.400000,237,0,0,"3.4-3.6 m"
    3.400000,3.200000,255,42,0,"3.2-3.4 m"
    3.200000,3.000000,255,85,0,"3.0-3.2 m"
    3.000000,2.800000,254,115,0,"2.8-3.0 m"
    2.800000,2.600000,254,140,0,"2.6-2.8 m"
    2.600000,2.400000,254,170,0,"2.4-2.6 m"
    2.400000,2.200000,254,191,10,"2.2-2.4 m"
    2.200000,2.000000,254,196,20,"2.0-2.2 m"
    2.000000,1.800000,254,221,51,"1.8-2.0 m"
    1.800000,1.600000,254,255,0,"1.6-1.8 m"
    1.600000,1.400000,254,255,115,"1.4-1.6 m"
    1.400000,1.200000,255,255,190,"1.2-1.4 m"
    1.200000,1.000000,209,255,115,"1.0-1.2 m"
    1.000000,0.8000000,163,255,115,"0.8-1.0 m"
    0.8000000,0.6000000,85,255,0,"0.6-0.8 m"
    0.6000000,0.4000000,76,230,0,"0.4-0.6 m"
    0.4000000,0.2000000,56,168,0,"0.2-0.4 m"
    0.2000000,0.000000,38,115,0,"0.0-0.2 m"
    0.000000,-200.0000,0,77,168,"<0.0 m"
    """








.. GENERATED FROM PYTHON SOURCE LINES 275-276

Let's write this string to a file in our temporary directory.

.. GENERATED FROM PYTHON SOURCE LINES 277-284

.. code-block:: Python


    legend_dir = tmpdir / "leg"
    legend_dir.mkdir(exist_ok=True)
    legend_path = legend_dir / "GWS_surface_level.leg"
    with open(legend_path, "w") as f:
        f.write(legend_str)








.. GENERATED FROM PYTHON SOURCE LINES 285-287

We can read the LEG file using the
:doc:`/api/generated/visualize/imod.visualize.read_imod_legend` function.

.. GENERATED FROM PYTHON SOURCE LINES 288-291

.. code-block:: Python


    colors, levels, labels = imod.visualize.read_imod_legend(legend_path)








.. GENERATED FROM PYTHON SOURCE LINES 292-294

We can now use these colors and levels to plot a surface. In this case, we
will plot the top layer of our layermodel.

.. GENERATED FROM PYTHON SOURCE LINES 294-297

.. code-block:: Python


    imod.visualize.plot_map(top.sel(layer=1), colors=colors, levels=levels)




.. image-sg:: /user-guide/images/sphx_glr_11-imod5-files_003.png
   :alt: 11 imod5 files
   :srcset: /user-guide/images/sphx_glr_11-imod5-files_003.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    (<Figure size 640x480 with 2 Axes>, <Axes: >)



.. GENERATED FROM PYTHON SOURCE LINES 298-306

Project files (PRJ)
-------------------

iMOD5 uses PRJ files to store project information, basically the model
definition. `See the example for a full overview of importing a model from a
projectfile into a MODFLOW6 model <INSERT LINK HERE>`_. We'll show here how to
open a projectfile here and convert the data to a MODFLOW 6 model.



.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 11.375 seconds)


.. _sphx_glr_download_user-guide_11-imod5-files.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: 11-imod5-files.ipynb <11-imod5-files.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: 11-imod5-files.py <11-imod5-files.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: 11-imod5-files.zip <11-imod5-files.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_