From 098d22a55893d0936c992b1d95359772f6868cce Mon Sep 17 00:00:00 2001 From: "Kacper Kowalik (Xarthisius)" Date: Tue, 31 Oct 2023 12:37:07 -0500 Subject: [PATCH] ENH: fix notebook links --- .../analyzing/Particle_Trajectories.ipynb | 103 +++++++++--- doc/source/analyzing/astropy_integrations.rst | 4 +- .../domain_analysis/XrayEmissionFields.ipynb | 33 ++-- .../analyzing/domain_analysis/index.rst | 2 +- .../domain_analysis/xray_emission_fields.rst | 6 - doc/source/analyzing/filtering.rst | 6 +- doc/source/analyzing/index.rst | 2 +- doc/source/analyzing/mesh_filter.ipynb | 7 + doc/source/analyzing/particle_filter.ipynb | 1 + .../analyzing/particle_trajectories.rst | 6 - doc/source/cookbook/fits_radio_cubes.ipynb | 7 + doc/source/cookbook/fits_xray_images.ipynb | 7 + doc/source/cookbook/index.rst | 4 +- doc/source/cookbook/tipsy_and_yt.ipynb | 2 +- doc/source/cookbook/yt_gadget_analysis.ipynb | 2 +- .../cookbook/yt_gadget_owls_analysis.ipynb | 2 +- .../Loading_Data_via_Functions.ipynb | 4 +- .../Loading_Generic_Array_Data.ipynb | 153 ++++++++++++++---- .../Loading_Generic_Particle_Data.ipynb | 2 + doc/source/examining/generic_array_data.rst | 6 - .../examining/generic_particle_data.rst | 6 - doc/source/examining/index.rst | 14 +- doc/source/examining/loading_data.rst | 34 ++-- .../examining/loading_via_functions.rst | 6 - doc/source/examining/low_level_inspection.rst | 2 +- doc/source/examining/spherical_data.rst | 6 - doc/source/quickstart/data_inspection.rst | 6 - .../data_objects_and_time_series.rst | 4 - .../derived_fields_and_profiles.rst | 4 - doc/source/quickstart/index.rst | 14 +- doc/source/quickstart/introduction.rst | 6 - .../quickstart/simple_visualization.rst | 4 - doc/source/quickstart/volume_rendering.rst | 4 - doc/source/reference/code_support.rst | 6 +- doc/source/visualizing/FITSImageData.ipynb | 100 ++++++++---- .../TransferFunctionHelper_Tutorial.ipynb | 58 +++++-- .../Volume_Rendering_Tutorial.ipynb | 6 +- .../geographic_projections_and_transforms.rst | 4 +- doc/source/visualizing/index.rst | 2 +- doc/source/visualizing/streamlines.rst | 2 +- .../visualizing/transfer_function_helper.rst | 6 - doc/source/visualizing/volume_rendering.rst | 8 +- .../visualizing/volume_rendering_tutorial.rst | 6 - .../visualizing/writing_fits_images.rst | 6 - 44 files changed, 415 insertions(+), 258 deletions(-) delete mode 100644 doc/source/analyzing/domain_analysis/xray_emission_fields.rst delete mode 100644 doc/source/analyzing/particle_trajectories.rst delete mode 100644 doc/source/examining/generic_array_data.rst delete mode 100644 doc/source/examining/generic_particle_data.rst delete mode 100644 doc/source/examining/loading_via_functions.rst delete mode 100644 doc/source/examining/spherical_data.rst delete mode 100644 doc/source/quickstart/data_inspection.rst delete mode 100644 doc/source/quickstart/data_objects_and_time_series.rst delete mode 100644 doc/source/quickstart/derived_fields_and_profiles.rst delete mode 100644 doc/source/quickstart/introduction.rst delete mode 100644 doc/source/quickstart/simple_visualization.rst delete mode 100644 doc/source/quickstart/volume_rendering.rst delete mode 100644 doc/source/visualizing/transfer_function_helper.rst delete mode 100644 doc/source/visualizing/volume_rendering_tutorial.rst delete mode 100644 doc/source/visualizing/writing_fits_images.rst diff --git a/doc/source/analyzing/Particle_Trajectories.ipynb b/doc/source/analyzing/Particle_Trajectories.ipynb index d4ce9e9b6a0..8fdb2e4a19d 100644 --- a/doc/source/analyzing/Particle_Trajectories.ipynb +++ b/doc/source/analyzing/Particle_Trajectories.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Particle Trajectories" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -11,7 +18,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -37,7 +47,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -56,7 +69,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -74,7 +90,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -95,7 +114,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -115,7 +137,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -134,7 +159,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -154,7 +182,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -174,7 +205,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -194,7 +228,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -215,7 +252,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -241,7 +281,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -260,7 +303,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -281,7 +327,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -315,7 +364,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -336,7 +388,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -354,7 +409,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -376,7 +434,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -392,7 +453,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [default]", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -406,9 +467,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.10.12" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 4 } diff --git a/doc/source/analyzing/astropy_integrations.rst b/doc/source/analyzing/astropy_integrations.rst index f7ac4e0c49d..71c4b09a376 100644 --- a/doc/source/analyzing/astropy_integrations.rst +++ b/doc/source/analyzing/astropy_integrations.rst @@ -33,8 +33,8 @@ Fixed-resolution two-dimensional images generated from datasets using yt (such a slices or projections) and fixed-resolution three-dimensional grids can be written to FITS files using yt's :class:`~yt.visualization.fits_image.FITSImageData` class and its subclasses. Multiple images can be combined into a single file, operations -can be performed on the images and their coordinates, etc. See :ref:`writing_fits_images` -for more information. +can be performed on the images and their coordinates, etc. See +:doc:`../visualizing/FITSImageData` for more information. Converting Field Container and 1D Profile Data to AstroPy Tables ---------------------------------------------------------------- diff --git a/doc/source/analyzing/domain_analysis/XrayEmissionFields.ipynb b/doc/source/analyzing/domain_analysis/XrayEmissionFields.ipynb index 90d7947d7d1..4c46e36f768 100644 --- a/doc/source/analyzing/domain_analysis/XrayEmissionFields.ipynb +++ b/doc/source/analyzing/domain_analysis/XrayEmissionFields.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# X-ray Emission Fields" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -34,9 +41,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "import yt\n", @@ -103,9 +108,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "slc = yt.SlicePlot(\n", @@ -132,9 +135,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "ds2 = yt.load(\"D9p_500/10MpcBox_HartGal_csf_a0.500.d\", default_species_fields=\"ionized\")\n", @@ -178,9 +179,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "prj = yt.ProjectionPlot(\n", @@ -228,9 +227,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "prj = yt.ProjectionPlot(\n", @@ -248,7 +245,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -262,9 +259,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.10.12" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/doc/source/analyzing/domain_analysis/index.rst b/doc/source/analyzing/domain_analysis/index.rst index 65336a978af..ffcde228c6d 100644 --- a/doc/source/analyzing/domain_analysis/index.rst +++ b/doc/source/analyzing/domain_analysis/index.rst @@ -24,7 +24,7 @@ These modules exist within yt itself. cosmology_calculator clump_finding - xray_emission_fields + XrayEmissionFields xray_data_README External Analysis Modules diff --git a/doc/source/analyzing/domain_analysis/xray_emission_fields.rst b/doc/source/analyzing/domain_analysis/xray_emission_fields.rst deleted file mode 100644 index c551b413f50..00000000000 --- a/doc/source/analyzing/domain_analysis/xray_emission_fields.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _xray_emission_fields: - -X-ray Emission Fields -===================== - -.. notebook:: XrayEmissionFields.ipynb diff --git a/doc/source/analyzing/filtering.rst b/doc/source/analyzing/filtering.rst index 3e5ded476cd..156cfd695ef 100644 --- a/doc/source/analyzing/filtering.rst +++ b/doc/source/analyzing/filtering.rst @@ -96,9 +96,7 @@ Cut Regions Cut regions are a more general solution to filtering mesh fields. The output of a cut region is an entirely new data object, which can be treated like any -other data object to generate images, examine its values, etc. - -.. notebook:: mesh_filter.ipynb +other data object to generate images, examine its values, etc. See `this `_. In addition to inputting string parameters into cut_region to specify filters, wrapper functions exist that allow the user to use a simplified syntax for @@ -252,7 +250,7 @@ to the dataset, it will also add ``stars`` filter to the dataset. ds.add_particle_filter("young_stars") -.. notebook:: particle_filter.ipynb +Additional example of particle filters can be found in the `notebook `_. .. _particle-unions: diff --git a/doc/source/analyzing/index.rst b/doc/source/analyzing/index.rst index 6bd56f6cf16..46911c16f83 100644 --- a/doc/source/analyzing/index.rst +++ b/doc/source/analyzing/index.rst @@ -22,6 +22,6 @@ multiple processors to accomplish tasks faster. generating_processed_data saving_data time_series_analysis - particle_trajectories + Particle_Trajectories parallel_computation astropy_integrations diff --git a/doc/source/analyzing/mesh_filter.ipynb b/doc/source/analyzing/mesh_filter.ipynb index abfc14b25ba..ae67120e7c9 100644 --- a/doc/source/analyzing/mesh_filter.ipynb +++ b/doc/source/analyzing/mesh_filter.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Filtering Grid Data" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/doc/source/analyzing/particle_filter.ipynb b/doc/source/analyzing/particle_filter.ipynb index c66ed85c894..aafb2e8f46e 100644 --- a/doc/source/analyzing/particle_filter.ipynb +++ b/doc/source/analyzing/particle_filter.ipynb @@ -4,6 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ + "# Filtering Particle Data\n", "Let us go through a full worked example. Here we have a Tipsy SPH dataset. By general\n", "inspection, we see that there are stars present in the dataset, since\n", "there are fields with field type: `Stars` in the `ds.field_list`. Let's look \n", diff --git a/doc/source/analyzing/particle_trajectories.rst b/doc/source/analyzing/particle_trajectories.rst deleted file mode 100644 index 6fd726fbd93..00000000000 --- a/doc/source/analyzing/particle_trajectories.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _particle-trajectories: - -Particle Trajectories ---------------------- - -.. notebook:: Particle_Trajectories.ipynb diff --git a/doc/source/cookbook/fits_radio_cubes.ipynb b/doc/source/cookbook/fits_radio_cubes.ipynb index bd5c1badf85..af0b780804e 100644 --- a/doc/source/cookbook/fits_radio_cubes.ipynb +++ b/doc/source/cookbook/fits_radio_cubes.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Analyzing FITS Radio Cubes" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/doc/source/cookbook/fits_xray_images.ipynb b/doc/source/cookbook/fits_xray_images.ipynb index 8a44b3f3ab9..c77fcd899a4 100644 --- a/doc/source/cookbook/fits_xray_images.ipynb +++ b/doc/source/cookbook/fits_xray_images.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# X-ray FITS Images" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/doc/source/cookbook/index.rst b/doc/source/cookbook/index.rst index a8bc99b7e42..7838f150932 100644 --- a/doc/source/cookbook/index.rst +++ b/doc/source/cookbook/index.rst @@ -42,9 +42,9 @@ Example Notebooks custom_colorbar_tickmarks yt_gadget_analysis yt_gadget_owls_analysis - ../visualizing/transfer_function_helper + ../visualizing/TransferFunctionHelper_Tutorial fits_radio_cubes fits_xray_images geographic_xforms_and_projections tipsy_and_yt - ../visualizing/volume_rendering_tutorial + ../visualizing/Volume_Rendering_Tutorial diff --git a/doc/source/cookbook/tipsy_and_yt.ipynb b/doc/source/cookbook/tipsy_and_yt.ipynb index d080c6127fa..f1d0299929c 100644 --- a/doc/source/cookbook/tipsy_and_yt.ipynb +++ b/doc/source/cookbook/tipsy_and_yt.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Loading Files" + "# Loading Tipsy Data" ] }, { diff --git a/doc/source/cookbook/yt_gadget_analysis.ipynb b/doc/source/cookbook/yt_gadget_analysis.ipynb index c386bdda7e7..ac24aa87022 100644 --- a/doc/source/cookbook/yt_gadget_analysis.ipynb +++ b/doc/source/cookbook/yt_gadget_analysis.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Loading the data" + "# Loading Gadget data" ] }, { diff --git a/doc/source/cookbook/yt_gadget_owls_analysis.ipynb b/doc/source/cookbook/yt_gadget_owls_analysis.ipynb index 617951d8c30..a8e5965492b 100644 --- a/doc/source/cookbook/yt_gadget_owls_analysis.ipynb +++ b/doc/source/cookbook/yt_gadget_owls_analysis.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# OWLS Examples" + "# Loading Gadget OWLS Data" ] }, { diff --git a/doc/source/examining/Loading_Data_via_Functions.ipynb b/doc/source/examining/Loading_Data_via_Functions.ipynb index 242e225fc5c..ecbaad8201e 100644 --- a/doc/source/examining/Loading_Data_via_Functions.ipynb +++ b/doc/source/examining/Loading_Data_via_Functions.ipynb @@ -257,7 +257,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -271,7 +271,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.5" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/doc/source/examining/Loading_Generic_Array_Data.ipynb b/doc/source/examining/Loading_Generic_Array_Data.ipynb index 44c3b7e089d..00e13e844ed 100644 --- a/doc/source/examining/Loading_Generic_Array_Data.ipynb +++ b/doc/source/examining/Loading_Generic_Array_Data.ipynb @@ -4,6 +4,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ + "# Loading Generic Array Data\n", + "\n", "Even if your data is not strictly related to fields commonly used in\n", "astrophysical codes or your code is not supported yet, you can still feed it to\n", "yt to use its advanced visualization and analysis facilities. The only\n", @@ -42,7 +44,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -65,7 +70,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -83,7 +91,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -135,7 +146,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -157,7 +171,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -192,7 +209,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -220,7 +240,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -249,7 +272,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -267,7 +293,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -298,7 +327,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -310,7 +342,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -335,7 +370,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -365,7 +403,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -387,7 +428,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -412,7 +456,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -441,7 +488,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -466,7 +516,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -484,7 +537,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -503,7 +559,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -525,7 +584,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -545,7 +607,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -577,7 +642,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -608,7 +676,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -627,7 +698,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -662,7 +736,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -680,7 +757,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -692,7 +772,10 @@ { "cell_type": "markdown", "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "source": [ "## Species fields" @@ -701,7 +784,10 @@ { "cell_type": "markdown", "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "source": [ "One can also supply species fields to a stream dataset, in the form of mass fractions. These will then be used to generate derived fields for mass, number, and nuclei densities of the separate species. The naming conventions for the mass fractions should correspond to the format specified in [the yt documentation for species fields](https://yt-project.org/doc/analyzing/fields.html#species-fields)." @@ -711,7 +797,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -818,7 +907,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -832,9 +921,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.10.12" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 4 } diff --git a/doc/source/examining/Loading_Generic_Particle_Data.ipynb b/doc/source/examining/Loading_Generic_Particle_Data.ipynb index fa471d39771..a98dddedd38 100644 --- a/doc/source/examining/Loading_Generic_Particle_Data.ipynb +++ b/doc/source/examining/Loading_Generic_Particle_Data.ipynb @@ -4,6 +4,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ + "# Loading Generic Particle Data\n", + "\n", "This example creates a fake in-memory particle dataset and then loads it as a yt dataset using the `load_particles` function.\n", "\n", "Our \"fake\" dataset will be numpy arrays filled with normally distributed randoml particle positions and uniform particle masses. Since real data is often scaled, I arbitrarily multiply by 1e6 to show how to deal with scaled data." diff --git a/doc/source/examining/generic_array_data.rst b/doc/source/examining/generic_array_data.rst deleted file mode 100644 index f68c99bf2cc..00000000000 --- a/doc/source/examining/generic_array_data.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _loading-numpy-array: - -Loading Generic Array Data -========================== - -.. notebook:: Loading_Generic_Array_Data.ipynb diff --git a/doc/source/examining/generic_particle_data.rst b/doc/source/examining/generic_particle_data.rst deleted file mode 100644 index a5b83c640b7..00000000000 --- a/doc/source/examining/generic_particle_data.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _generic-particle-data: - -Loading Generic Particle Data ------------------------------ - -.. notebook:: Loading_Generic_Particle_Data.ipynb diff --git a/doc/source/examining/index.rst b/doc/source/examining/index.rst index da0cac0186e..055d1077d16 100644 --- a/doc/source/examining/index.rst +++ b/doc/source/examining/index.rst @@ -6,17 +6,17 @@ Loading and Examining Data Nominally, one should just be able to run ``yt.load()`` on a dataset and start computing; however, there may be additional notes associated with different data formats as described below. Furthermore, we provide methods for loading -data from unsupported data formats in :ref:`loading-numpy-array`, -:ref:`generic-particle-data`, and :ref:`loading-spherical-data`. Lastly, if -you want to examine the raw data for your particular dataset, visit +data from unsupported data formats in :doc:`Loading_Generic_Array_Data`, +:doc:`Loading_Generic_Particle_Data`, and :doc:`Loading_Spherical_Data`. +Lastly, if you want to examine the raw data for your particular dataset, visit :ref:`low-level-data-inspection`. .. toctree:: :maxdepth: 2 loading_data - generic_array_data - generic_particle_data - loading_via_functions - spherical_data + Loading_Generic_Array_Data + Loading_Generic_Particle_Data + Loading_Data_via_Functions + Loading_Spherical_Data low_level_inspection diff --git a/doc/source/examining/loading_data.rst b/doc/source/examining/loading_data.rst index c8eaebbb107..50a1bab98db 100644 --- a/doc/source/examining/loading_data.rst +++ b/doc/source/examining/loading_data.rst @@ -70,7 +70,8 @@ Simple HDF5 Data .. note:: This wrapper takes advantage of the functionality described in - :ref:`loading-via-functions` but the basics of setting up function handlers, + :doc:`Loading_Data_via_Functions` + but the basics of setting up function handlers, guessing fields, etc, are handled by yt. Using the function :func:`yt.loaders.load_hdf5_file`, you can load a generic @@ -1014,7 +1015,7 @@ FITS images are fully-describing in that unit, parameter, and coordinate information is passed from the original dataset. These can be created via the :class:`~yt.visualization.fits_image.FITSImageData` class and its subclasses. For information about how to use these special classes, see -:ref:`writing_fits_images`. +:doc:`../visualizing/FITSImageData`. Once you have produced a FITS file in this fashion, you can load it using yt and it will be detected as a ``YTFITSDataset`` object, and it can be analyzed @@ -1056,7 +1057,7 @@ particle fields in yt, but a grid will be constructed from the WCS information in the FITS header. There is a helper function, ``setup_counts_fields``, which may be used to make deposited image fields from the event data for different energy bands (for an example see -:ref:`xray_fits`). +:doc:`../cookbook/fits_xray_images`). Generic FITS Images """"""""""""""""""" @@ -1296,9 +1297,9 @@ Examples of Using FITS Data The following Jupyter notebooks show examples of working with FITS data in yt, which we recommend you look at in the following order: -* :ref:`radio_cubes` -* :ref:`xray_fits` -* :ref:`writing_fits_images` +* :doc:`../cookbook/fits_radio_cubes` +* :doc:`../cookbook/fits_xray_images` +* :doc:`../visualizing/FITSImageData` .. _loading-flash-data: @@ -1385,9 +1386,10 @@ yt has support for reading Gadget data in both raw binary and HDF5 formats. It is able to access the particles as it would any other particle dataset, and it can apply smoothing kernels to the data to produce both quantitative analysis and visualization. See :ref:`loading-sph-data` for more details and -:ref:`gadget-notebook` for a detailed example of loading, analyzing, and -visualizing a Gadget dataset. An example which makes use of a Gadget snapshot -from the OWLS project can be found at :ref:`owls-notebook`. +:doc:`../cookbook/yt_gadget_analysis` for a detailed example +of loading, analyzing, and visualizing a Gadget dataset. An example which +makes use of a Gadget snapshot from the OWLS project can be found in +:doc:`../cookbook/yt_gadget_owls_analysis`. .. note:: @@ -1882,14 +1884,14 @@ to avoid catastrophic cancellations. Generic AMR Data ---------------- -See :ref:`loading-numpy-array` and +See :doc:`Loading_Generic_Array_Data` and :func:`~yt.frontends.stream.data_structures.load_amr_grids` for more detail. .. note:: It is now possible to load data using *only functions*, rather than using the fully-in-memory method presented here. For more information and examples, - see :ref:`loading-via-functions`. + see :doc:`Loading_Data_via_Functions`. It is possible to create native yt dataset from Python's dictionary that describes set of rectangular patches of data of possibly varying @@ -1946,7 +1948,7 @@ Particle fields are supported by adding 1-dimensional arrays to each Generic Array Data ------------------ -See :ref:`loading-numpy-array` and +See :doc:`Loading_Generic_Array_Data` and :func:`~yt.frontends.stream.data_structures.load_uniform_grid` for more detail. Even if your data is not strictly related to fields commonly used in @@ -2010,7 +2012,7 @@ Semi-Structured Grid Data See :ref:`loading-stretched-grids` for more information. -See :ref:`loading-numpy-array`, +See :doc:`Loading_Generic_Array_Data`, :func:`~yt.frontends.stream.data_structures.hexahedral_connectivity`, :func:`~yt.frontends.stream.data_structures.load_hexahedral_mesh` for more detail. @@ -2124,7 +2126,7 @@ fewer) cells. Unstructured Grid Data ---------------------- -See :ref:`loading-numpy-array`, +See :doc:`Loading_Generic_Array_Data`, :func:`~yt.frontends.stream.data_structures.load_unstructured_mesh` for more detail. @@ -2250,7 +2252,7 @@ Generic Particle Data For more information about how yt indexes and reads particle data, set the section :ref:`demeshening`. -See :ref:`generic-particle-data` and +See :doc:`Loading_Generic_Particle_Data` and :func:`~yt.frontends.stream.data_structures.load_particles` for more detail. You can also load generic particle data using the same ``stream`` functionality @@ -3202,7 +3204,7 @@ Tipsy Data For more information about how yt indexes and reads particle data, set the section :ref:`demeshening`. -See :ref:`tipsy-notebook` and :ref:`loading-sph-data` for more details. +See :doc:`../cookbook/tipsy_and_yt` and :ref:`loading-sph-data` for more details. yt also supports loading Tipsy data. Many of its characteristics are similar to how Gadget data is loaded. diff --git a/doc/source/examining/loading_via_functions.rst b/doc/source/examining/loading_via_functions.rst deleted file mode 100644 index 4d929aa8d8b..00000000000 --- a/doc/source/examining/loading_via_functions.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _loading-via-functions: - -Loading Data via Functions -========================== - -.. notebook:: Loading_Data_via_Functions.ipynb diff --git a/doc/source/examining/low_level_inspection.rst b/doc/source/examining/low_level_inspection.rst index f4603e2c05c..1d7f83dc1ab 100644 --- a/doc/source/examining/low_level_inspection.rst +++ b/doc/source/examining/low_level_inspection.rst @@ -13,7 +13,7 @@ access to the raw data. the attendant properties. For a more basic introduction, see :ref:`quickstart` and more specifically -:ref:`data_inspection`. +:doc:`../quickstart/2)_Data_Inspection`. .. _examining-grid-hierarchies: diff --git a/doc/source/examining/spherical_data.rst b/doc/source/examining/spherical_data.rst deleted file mode 100644 index 38bd8e48bcc..00000000000 --- a/doc/source/examining/spherical_data.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _loading-spherical-data: - -Loading Spherical Data -====================== - -.. notebook:: Loading_Spherical_Data.ipynb diff --git a/doc/source/quickstart/data_inspection.rst b/doc/source/quickstart/data_inspection.rst deleted file mode 100644 index 72d93a95aaf..00000000000 --- a/doc/source/quickstart/data_inspection.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _data_inspection: - -Data Inspection ---------------- - -.. notebook:: 2)_Data_Inspection.ipynb diff --git a/doc/source/quickstart/data_objects_and_time_series.rst b/doc/source/quickstart/data_objects_and_time_series.rst deleted file mode 100644 index 9db2caba24d..00000000000 --- a/doc/source/quickstart/data_objects_and_time_series.rst +++ /dev/null @@ -1,4 +0,0 @@ -Data Objects and Time Series ----------------------------- - -.. notebook:: 4)_Data_Objects_and_Time_Series.ipynb diff --git a/doc/source/quickstart/derived_fields_and_profiles.rst b/doc/source/quickstart/derived_fields_and_profiles.rst deleted file mode 100644 index 2278a5930be..00000000000 --- a/doc/source/quickstart/derived_fields_and_profiles.rst +++ /dev/null @@ -1,4 +0,0 @@ -Derived Fields and Profiles ---------------------------- - -.. notebook:: 5)_Derived_Fields_and_Profiles.ipynb diff --git a/doc/source/quickstart/index.rst b/doc/source/quickstart/index.rst index b232f1028e9..4d793f3f349 100644 --- a/doc/source/quickstart/index.rst +++ b/doc/source/quickstart/index.rst @@ -55,17 +55,17 @@ Here are the notebooks, which have been filled in for inspection: .. toctree:: :maxdepth: 1 - introduction - data_inspection - simple_visualization - data_objects_and_time_series - derived_fields_and_profiles - volume_rendering + 1)_Introduction + 2)_Data_Inspection + 3)_Simple_Visualization + 4)_Data_Objects_and_Time_Series + 5)_Derived_Fields_and_Profiles + 6)_Volume_Rendering .. note:: The notebooks use sample datasets that are available for download at - https://yt-project.org/data. See :ref:`quickstart-introduction` for more + https://yt-project.org/data. See :doc:`1)_Introduction` for more details. Let us know if you would like to contribute other example notebooks, or have diff --git a/doc/source/quickstart/introduction.rst b/doc/source/quickstart/introduction.rst deleted file mode 100644 index a37e8b05173..00000000000 --- a/doc/source/quickstart/introduction.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _quickstart-introduction: - -Introduction ------------- - -.. notebook:: 1)_Introduction.ipynb diff --git a/doc/source/quickstart/simple_visualization.rst b/doc/source/quickstart/simple_visualization.rst deleted file mode 100644 index 01ded6ace90..00000000000 --- a/doc/source/quickstart/simple_visualization.rst +++ /dev/null @@ -1,4 +0,0 @@ -Simple Visualization --------------------- - -.. notebook:: 3)_Simple_Visualization.ipynb diff --git a/doc/source/quickstart/volume_rendering.rst b/doc/source/quickstart/volume_rendering.rst deleted file mode 100644 index 847a44fa5a2..00000000000 --- a/doc/source/quickstart/volume_rendering.rst +++ /dev/null @@ -1,4 +0,0 @@ -Volume Rendering ----------------- - -.. notebook:: 6)_Volume_Rendering.ipynb diff --git a/doc/source/reference/code_support.rst b/doc/source/reference/code_support.rst index 558a13fa8d6..1a513732e2b 100644 --- a/doc/source/reference/code_support.rst +++ b/doc/source/reference/code_support.rst @@ -92,6 +92,6 @@ each supported output format using yt. CFRadial coordinates will be gridded on load, see :ref:`loading-cfradial-data`. If you have a dataset that uses an output format not yet supported by yt, you -can either input your data following :ref:`loading-numpy-array` or -:ref:`generic-particle-data`, or help us by :ref:`creating_frontend` for this -new format. +can either input your data following :doc:`../examining/Loading_Generic_Array_Data` or +:doc:`../examining/Loading_Generic_Particle_Data`, or help us by :ref:`creating_frontend` +for this new format. diff --git a/doc/source/visualizing/FITSImageData.ipynb b/doc/source/visualizing/FITSImageData.ipynb index 75526640267..9f5a609476b 100644 --- a/doc/source/visualizing/FITSImageData.ipynb +++ b/doc/source/visualizing/FITSImageData.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Writing FITS Images" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -133,7 +140,10 @@ { "cell_type": "markdown", "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "source": [ "## Making FITS images from Particle Projections" @@ -141,17 +151,26 @@ }, { "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, "source": [ "To create a FITS image from a particle field which is smeared onto the image, we can use\n", "`FITSParticleProjection`:" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", "execution_count": null, + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, "outputs": [], "source": [ "dsp = yt.load(\"gizmo_64/output/snap_N64L16_135.hdf5\")\n", @@ -159,50 +178,62 @@ " dsp, \"x\", (\"PartType1\", \"particle_mass\"), deposition=\"cic\"\n", ")\n", "prjp_fits.writeto(\"prjp.fits\", overwrite=True)" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, "source": [ "Note that we used the \"Cloud-In-Cell\" interpolation method (`\"cic\"`) instead of the default\n", "\"Nearest-Grid-Point\" (`\"ngp\"`) method. \n", "\n", "If you want the projection to be divided by the pixel area (to make a projection of mass density, \n", "for example), supply the ``density`` keyword argument:" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", "execution_count": null, + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, "outputs": [], "source": [ "prjpd_fits = yt.FITSParticleProjection(\n", " dsp, \"x\", (\"PartType1\", \"particle_mass\"), density=True, deposition=\"cic\"\n", ")\n", "prjpd_fits.writeto(\"prjpd.fits\", overwrite=True)" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, "source": [ "`FITSParticleOffAxisProjection` can be used to make a projection along any arbitrary sight line:" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "code", "execution_count": null, + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, "outputs": [], "source": [ "L = [1, -1, 1] # normal or \"line of sight\" vector\n", @@ -211,19 +242,19 @@ " dsp, L, (\"PartType1\", \"particle_mass\"), deposition=\"cic\", north_vector=N\n", ")\n", "poff_fits.writeto(\"poff.fits\", overwrite=True)" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, "source": [ "## Using `HDUList` Methods" - ], - "metadata": { - "collapsed": false - } + ] }, { "cell_type": "markdown", @@ -632,7 +663,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": true + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } }, "outputs": [], "source": [ @@ -777,7 +811,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -791,9 +825,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.10.12" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb b/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb index 30c32ca30ee..8492c07131a 100644 --- a/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb +++ b/doc/source/visualizing/TransferFunctionHelper_Tutorial.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Transfer Function Helper Tutorial" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -13,7 +20,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -46,7 +56,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -64,7 +77,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -82,7 +98,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -107,7 +126,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -125,7 +147,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -160,7 +185,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -184,7 +212,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -219,7 +250,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [], "source": [ @@ -239,7 +273,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -253,9 +287,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.10.12" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 4 } diff --git a/doc/source/visualizing/Volume_Rendering_Tutorial.ipynb b/doc/source/visualizing/Volume_Rendering_Tutorial.ipynb index 531e084234c..8f316effc78 100644 --- a/doc/source/visualizing/Volume_Rendering_Tutorial.ipynb +++ b/doc/source/visualizing/Volume_Rendering_Tutorial.ipynb @@ -362,7 +362,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -376,9 +376,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.3" + "version": "3.10.12" } }, "nbformat": 4, - "nbformat_minor": 1 + "nbformat_minor": 4 } diff --git a/doc/source/visualizing/geographic_projections_and_transforms.rst b/doc/source/visualizing/geographic_projections_and_transforms.rst index 9fe43803ee1..c0481c70694 100644 --- a/doc/source/visualizing/geographic_projections_and_transforms.rst +++ b/doc/source/visualizing/geographic_projections_and_transforms.rst @@ -78,7 +78,7 @@ with this functionality. The next few examples will use a GEOS dataset accessible from the ``yt`` data downloads page. For details about loading this data, please -see :ref:`cookbook-geographic_projections`. +see :doc:`../cookbook/geographic_xforms_and_projections`. If a geographic dataset is loaded without any defined projection the default option of ``Mollweide`` will be displayed. @@ -141,4 +141,4 @@ levels of customization: set_mpl_projection(cartopy.crs.PlateCarree()) Further examples of using the geographic transforms with this dataset -can be found in :ref:`cookbook-geographic_projections`. +can be found in :doc:`../cookbook/geographic_xforms_and_projections`. diff --git a/doc/source/visualizing/index.rst b/doc/source/visualizing/index.rst index 1cf20e35097..3bb6b725bfd 100644 --- a/doc/source/visualizing/index.rst +++ b/doc/source/visualizing/index.rst @@ -23,4 +23,4 @@ interactively. streamlines colormaps/index geographic_projections_and_transforms - writing_fits_images + FITSImageData diff --git a/doc/source/visualizing/streamlines.rst b/doc/source/visualizing/streamlines.rst index 5c81ce94e90..7aea163f6ed 100644 --- a/doc/source/visualizing/streamlines.rst +++ b/doc/source/visualizing/streamlines.rst @@ -9,7 +9,7 @@ velocity flow or magnetic field lines, they can be defined to follow any three-dimensional vector field. Once an initial condition and total length of the streamline are specified, the streamline is uniquely defined. Relatedly, yt also has the ability to follow -:ref:`particle-trajectories`. +:doc:`../analyzing/Particle_Trajectories`. Method ------ diff --git a/doc/source/visualizing/transfer_function_helper.rst b/doc/source/visualizing/transfer_function_helper.rst deleted file mode 100644 index bc408477fa6..00000000000 --- a/doc/source/visualizing/transfer_function_helper.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _transfer-function-helper-tutorial: - -Transfer Function Helper Tutorial -================================= - -.. notebook:: TransferFunctionHelper_Tutorial.ipynb diff --git a/doc/source/visualizing/volume_rendering.rst b/doc/source/visualizing/volume_rendering.rst index 9eaa47a2ff3..25ded20915b 100644 --- a/doc/source/visualizing/volume_rendering.rst +++ b/doc/source/visualizing/volume_rendering.rst @@ -15,8 +15,8 @@ processors are being actively developed. .. note:: - There is a Jupyter notebook containing a volume rendering tutorial available - at :ref:`volume-rendering-tutorial`. + There is a Jupyter notebook containing a volume rendering tutorial: + :doc:`Volume_Rendering_Tutorial`. Volume Rendering Introduction ----------------------------- @@ -237,7 +237,7 @@ For fun, let's make the same volume_rendering, but this time setting sc.save("rendering.png", sigma_clip=4.0) To see a full example on how to use the ``TransferFunctionHelper`` interface, -follow the annotated :ref:`transfer-function-helper-tutorial`. +follow the annotated :doc:`TransferFunctionHelper_Tutorial`. Color Transfer Functions ++++++++++++++++++++++++ @@ -696,7 +696,7 @@ function. Example: sc.save("rendering.png") For an in-depth tutorial on how to create a Scene and modify its contents, -see this annotated :ref:`volume-rendering-tutorial`. +see this annotated :doc:`Volume_Rendering_Tutorial`. .. _volume-rendering-method: diff --git a/doc/source/visualizing/volume_rendering_tutorial.rst b/doc/source/visualizing/volume_rendering_tutorial.rst deleted file mode 100644 index fafb6779c31..00000000000 --- a/doc/source/visualizing/volume_rendering_tutorial.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _volume-rendering-tutorial: - -Volume Rendering Tutorial -========================= - -.. notebook:: Volume_Rendering_Tutorial.ipynb diff --git a/doc/source/visualizing/writing_fits_images.rst b/doc/source/visualizing/writing_fits_images.rst deleted file mode 100644 index f21f6f090f8..00000000000 --- a/doc/source/visualizing/writing_fits_images.rst +++ /dev/null @@ -1,6 +0,0 @@ -.. _writing_fits_images: - -Writing FITS Images -========================== - -.. notebook:: FITSImageData.ipynb