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‎.github/workflows/ci.yml‎

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strategy:
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matrix:
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platform: [ubuntu-latest, macos-latest, windows-latest]
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python-version: ['3.8', '3.10', '3.11', '3.12']
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python-version: ['3.10', '3.11', '3.12', '3.13']
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defaults:
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run:
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shell: bash

‎.github/workflows/publish-pypi.yml‎

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deploy:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v2
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uses: actions/setup-python@v5
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with:
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python-version: '3.8'
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python-version: '3.12'
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- name: Install dependencies
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run: |
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python -m pip install poetry

‎docs/_static/custom.css‎

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:root {
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/* Use softer blue from bootstrap's default info color */
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--pst-color-primary: 0, 108, 133;
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--pst-color-active-navigation: 0, 108, 133;
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--pst-color-navbar-link: 255, 255, 255;
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--pst-color-navbar-link-hover: 200, 255, 255;
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--pst-color-navbar-link-active: 255, 255, 255;
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}
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.navbar-light .navbar-nav>.active>.nav-link {
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font-weight: 800;
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color: rgba(var(--pst-color-navbar-link-active),1);
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}
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dt:target, span.highlighted {
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background-color: rgba(var(--pst-color-primary),1);
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}
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.sig {
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color: #ffffff;
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padding-left: 10px;
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background-color: rgba(var(--pst-color-primary),1);
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}
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color: #ffffff;
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}
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nav.bg-light {
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background-color: rgba(var(--pst-color-primary),1) !important;
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}
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.container-xl{max-width: 1400px }
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.btn-block {
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text-align: left;
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font-weight: 600;
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color: rgba(var(--pst-color-primary),1);
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border-color: rgba(var(--pst-color-primary),1);
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}
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.btn-block[href^="case_studies/index.html"] {
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html {
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/* Use softer blue from bootstrap's default info color */
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--pst-color-primary: 0, 108, 133;
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--pst-color-active-navigation: 0, 108, 133;
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--pst-color-navbar-link: 255, 255, 255;
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--pst-color-navbar-link-hover: 200, 255, 255;
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--pst-color-navbar-link-active: 255, 255, 255;
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--pst-color-on-background: #006d85;
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}
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h1 {
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--pst-color-heading: #006d85;
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}
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h2 {
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--pst-color-heading: #006d85;
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}
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h3 {
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--pst-color-heading: #006d85;
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}
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.sd-btn{
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border-color: #006d85;
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width: 100%;
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text-align: left;
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font-weight: 600;
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color: #ffffff;
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background-color:rgba(var(--pst-color-primary),1);
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border-color: rgba(var(--pst-color-primary),1);
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}
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text-align: left;
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font-weight: 600;
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border-color: rgba(var(--pst-color-primary),1);
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}
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.btn-block:hover {
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color:#ffffff;
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border-color: rgba(var(--pst-color-primary),1);
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}
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code {
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font-size: 95% !important;
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}
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}
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p .sd-btn:hover{
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background-color: #006d85;
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color: #ffffff
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}
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.bd-header {
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--pst-color-text-muted: #ffffff;
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--pst-color-on-background: #006d85;
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}
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.bd-header ul.navbar-nav > li.nav-item.current > .nav-link{
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color:#c8ffff;
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--pst-color-secondary:#c8ffff;
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}
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.bd-header ul.navbar-nav > li.nav-item > .nav-link:hover{
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color:#c8ffff;
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--pst-color-secondary:#c8ffff;
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}
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.search-button-field{
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color: #5c5c5c
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}

‎docs/case_studies/index.rst‎

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44
Case Studies
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===================
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.. panels::
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.. grid:: 1 2 2 2
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:gutter: 4
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**Interval manipulation**
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.. grid-item-card:: Interval manipulation
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This tutorial introduces the use of :mod:`staircase` for manipulating intervals. The ideas demonstrated form the basis for `the piso package <https://piso.readthedocs.io>`_.
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This tutorial introduces the use of :mod:`staircase` for manipulating intervals. The ideas demonstrated form the basis for `the piso package <https://piso.readthedocs.io>`_.
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.. link-button:: intervals
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:type: ref
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:text:
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:classes: stretched-link
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---
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.. button-ref:: casestudies.intervals
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:ref-type: ref
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:class: stretched-link
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**Queue analysis**
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.. grid-item-card:: Queue analysis
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This case study illustrates the use of :mod:`staircase` for queue analysis, including the exploration of the queue size distribution.
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This case study illustrates the use of :mod:`staircase` for queue analysis, including the exploration of the queue size distribution.
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.. link-button:: queues
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:type: ref
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:text:
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:classes: stretched-link
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.. button-ref:: casestudies.queues
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:ref-type: ref
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:class: stretched-link
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---
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**Asset utilisation**
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.. grid-item-card:: Asset utilisationn
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This case study demonstrates the use of :mod:`staircase` for quick calculation of asset utilisation over various time periods.
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This case study demonstrates the use of :mod:`staircase` for quick calculation of asset utilisation over various time periods.
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.. link-button:: utilisation
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:type: ref
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:text:
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:classes: stretched-link
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.. button-ref:: casestudies.utilisation
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:class: stretched-link
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.. grid-item-card:: Data leakage
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---
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This case study shows how :mod:`staircase` can be used to simplify feature engineering, for machine learning models, while avoiding *data leakage*.
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**Data leakage**
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.. button-ref:: casestudies.dataleakage
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:ref-type: ref
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:class: stretched-link
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This case study shows how :mod:`staircase` can be used to simplify feature engineering, for machine learning models, while avoiding *data leakage*.
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.. link-button:: dataleakage
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:type: ref
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:text:
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:classes: stretched-link
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.. toctree::
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.. toctree::
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:hidden:
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:maxdepth: 1
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‎docs/case_studies/utilisation.rst‎

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import pandas as pd
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import staircase as sc
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data = pd.read_csv(asset_data, parse_dates=['start', 'end'], dayfirst=True)
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data = pd.read_csv(asset_data, parse_dates=['start', 'end'])
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data
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For the analysis we would like a :class:`staircase.Stairs` object for each asset. Each Stairs object will represent a step function which has a value of zero, when the asset is not in use, and a value of one when the asset is in use. We can pandas' groupby process (`"split-apply-combine" <https://pandas.pydata.org/docs/user_guide/groupby.html>`_) with the :class:`staircase.Stairs` constructor method to get a :class:`pandas.Series`, indexed by asset name, with :class:`staircase.Stairs` values:
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.. ipython:: python
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asset_use = data.groupby("asset").apply(sc.Stairs, start="start", end="end")
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asset_use = data.groupby("asset")[["start", "end"]].apply(sc.Stairs, start="start", end="end")
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Note that since we want to examine 2020 we clip the step function at the year endpoints, making the functions undefined for any time outside of 2020 (see :ref:`user_guide.gotchas` for why this is a good idea). :meth:`pandas.Series.apply` is used here, rather than looping, for efficiency.
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asset_use = asset_use.apply(sc.Stairs.clip, (pd.Timestamp("2020"), pd.Timestamp("2021")))
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asset_use = asset_use.apply(sc.Stairs.clip, args=(pd.Timestamp("2020"), pd.Timestamp("2021")))
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We can access an individual :class:`staircase.Stairs` object with the corresponding asset name. For example, to plot the step function corresponding to asset Z, for the first day:
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‎docs/conf.py‎

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# "sphinx.ext.linkcode",
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"numpydoc", # handle NumPy documentation formatted docstrings]
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"nbsphinx",
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"sphinx_design",
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source_suffix = [".rst", ".ipynb"]
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source_suffix = [".rst"]
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"google_analytics_id": "UA-27880019-2",
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# "google_analytics_id": "UA-27880019-2",
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"navbar_end": ["navbar-icon-links"],
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html_show_sourcelink = False
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‎docs/getting_started/intro_tutorials/index.rst‎

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=======================
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.. link-button:: 00_stepfunction
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:text: What is a step function?
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:text: How do I create my step function?
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.. button-ref:: intro_tutorials.stepfunction
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What is a step function?
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:text: What does my step function look like?
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How do I create my step function?
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What does my step function look like?
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How do I combine step functions?
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How can I compare my step function?
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What statistical properties are available?
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What next?
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.. toctree::
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:maxdepth: 1

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