deploy: 1b3dcde

.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 8c6220d7d44658699a85f45a14ded2b0
+tags: 645f666f9bcd5a90fca523b33c5a78b7

_downloads/13d29bba0b7f4883cb92cda379ddc864/plot_dummy.py

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+"""
+==============
+A dummy script
+==============
+
+Dummy script to illustrate structure of examples folder 
+"""
+
+# %%
+# Import necessary packages
+import numpy as np
+import matplotlib.pyplot as plt
+import osipi
+
+# %%
+# Generate synthetic AIF with default settings and plot the result.
+
+# Define time points in units of seconds - in this case we use a time resolution of 0.5 sec and a total duration of 6 minutes.
+t = np.arange(0, 6*60, 0.5)
+
+# Create an AIF with default settings
+ca = osipi.aif_parker(t)
+
+# Plot the AIF over the full range
+plt.plot(t, ca, 'r-')
+plt.plot(t, 0*t, 'k-')
+plt.xlabel('Time (sec)')
+plt.ylabel('Plasma concentration (mM)')
+plt.show()
+
+# %%
+# The bolus arrival time (BAT) defaults to 30s. What happens if we change it? Let's try, by changing it in steps of 30s:
+
+ca = osipi.aif_parker(t, BAT=0)
+plt.plot(t, ca, 'b-', label='BAT = 0s')
+ca = osipi.aif_parker(t, BAT=30)
+plt.plot(t, ca, 'r-', label='BAT = 30s')
+ca = osipi.aif_parker(t, BAT=60)
+plt.plot(t, ca, 'g-', label='BAT = 60s')
+ca = osipi.aif_parker(t, BAT=90)
+plt.plot(t, ca, 'm-', label='BAT = 90s')
+plt.xlabel('Time (sec)')
+plt.ylabel('Plasma concentration (mM)')
+plt.legend()
+plt.show()
+
+# %%
+# the dose defaults to 0.1- what happens if we change it too?
+
+ca = osipi.aif_parker(t, BAT=0, dose=0.05)
+plt.plot(t, ca, 'b-', label='BAT = 0s, dose = 0.05')
+ca = osipi.aif_parker(t, BAT=30, dose=0.1)
+plt.plot(t, ca, 'r-', label='BAT = 30s, dose = 0.1')
+ca = osipi.aif_parker(t, BAT=60, dose=0.2)
+plt.plot(t, ca, 'g-', label='BAT = 60s, dose = 0.2')
+ca = osipi.aif_parker(t, BAT=90, dose=0.3)
+plt.plot(t, ca, 'm-', label='BAT = 90s, dose = 0.3')
+plt.xlabel('Time (sec)')
+plt.ylabel('Plasma concentration (mM)')
+plt.legend()
+plt.show()
+
+# Choose the last image as a thumbnail for the gallery
+# sphinx_gallery_thumbnail_number = -1

_downloads/63a8dfc7aa971c336ef8774e6dbfd272/plot_dummy.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Dummy script as demo\n\nDummy script to show the examples structure. \n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\nimport matplotlib.pyplot as plt\nimport osipi"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Generate synthetic AIF with default settings and plot the result.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "# Define time points in units of seconds - in this case we use a time resolution of 0.5 sec and a total duration of 6 minutes.\nt = np.arange(0, 6*60, 0.5)\n\n# Create an AIF with default settings\nca = osipi.aif_parker(t)\n\n# Plot the AIF over the full range\nplt.plot(t, ca)\nplt.show()\n\n\n# Choose the last image as a thumbnail for the gallery\n# sphinx_gallery_thumbnail_number = -1"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.10"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

_downloads/6794ff0fe2ebfd1be519862fb198ceb5/plot_aif_parker.py

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+"""
+======================================
+The Parker AIF - a play with variables
+======================================
+
+Simulating a Parker AIF with different settings. 
+"""
+
+# %%
+# Import necessary packages
+import numpy as np
+import matplotlib.pyplot as plt
+import osipi
+
+# %%
+# Generate synthetic AIF with default settings and plot the result.
+
+# Define time points in units of seconds - in this case we use a time resolution of 0.5 sec and a total duration of 6 minutes.
+t = np.arange(0, 6*60, 0.5)
+
+# Create an AIF with default settings
+ca = osipi.aif_parker(t)
+
+# Plot the AIF over the full range
+plt.plot(t, ca, 'r-')
+plt.plot(t, 0*t, 'k-')
+plt.xlabel('Time (sec)')
+plt.ylabel('Plasma concentration (mM)')
+plt.show()
+
+# %%
+# The bolus arrival time (BAT) defaults to 30s. What happens if we change it? Let's try, by changing it in steps of 30s:
+
+ca = osipi.aif_parker(t, BAT=0)
+plt.plot(t, ca, 'b-', label='BAT = 0s')
+ca = osipi.aif_parker(t, BAT=30)
+plt.plot(t, ca, 'r-', label='BAT = 30s')
+ca = osipi.aif_parker(t, BAT=60)
+plt.plot(t, ca, 'g-', label='BAT = 60s')
+ca = osipi.aif_parker(t, BAT=90)
+plt.plot(t, ca, 'm-', label='BAT = 90s')
+plt.xlabel('Time (sec)')
+plt.ylabel('Plasma concentration (mM)')
+plt.legend()
+plt.show()
+
+# %%
+# the dose defaults to 0.1- what happens if we change it too?
+
+ca = osipi.aif_parker(t, BAT=0, dose=0.05)
+plt.plot(t, ca, 'b-', label='BAT = 0s, dose = 0.05')
+ca = osipi.aif_parker(t, BAT=30, dose=0.1)
+plt.plot(t, ca, 'r-', label='BAT = 30s, dose = 0.1')
+ca = osipi.aif_parker(t, BAT=60, dose=0.2)
+plt.plot(t, ca, 'g-', label='BAT = 60s, dose = 0.2')
+ca = osipi.aif_parker(t, BAT=90, dose=0.3)
+plt.plot(t, ca, 'm-', label='BAT = 90s, dose = 0.3')
+plt.xlabel('Time (sec)')
+plt.ylabel('Plasma concentration (mM)')
+plt.legend()
+plt.show()
+
+# Choose the last image as a thumbnail for the gallery
+# sphinx_gallery_thumbnail_number = -1

_downloads/9dd8307460a64f1314f28e1650ea27b2/plot_aif_parker.ipynb

@@ -0,0 +1,104 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# The Parker AIF - a play with variables\n\nSimulating a Parker AIF with different settings. \n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Import necessary packages\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\nimport matplotlib.pyplot as plt\nimport osipi"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Generate synthetic AIF with default settings and plot the result.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "# Define time points in units of seconds - in this case we use a time resolution of 0.5 sec and a total duration of 6 minutes.\nt = np.arange(0, 6*60, 0.5)\n\n# Create an AIF with default settings\nca = osipi.aif_parker(t)\n\n# Plot the AIF over the full range\nplt.plot(t, ca, 'r-')\nplt.plot(t, 0*t, 'k-')\nplt.xlabel('Time (sec)')\nplt.ylabel('Plasma concentration (mM)')\nplt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "The bolus arrival time (BAT) defaults to 30s. What happens if we change it? Let's try, by changing it in steps of 30s:\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "ca = osipi.aif_parker(t, BAT=0)\nplt.plot(t, ca, 'b-', label='BAT = 0s')\nca = osipi.aif_parker(t, BAT=30)\nplt.plot(t, ca, 'r-', label='BAT = 30s')\nca = osipi.aif_parker(t, BAT=60)\nplt.plot(t, ca, 'g-', label='BAT = 60s')\nca = osipi.aif_parker(t, BAT=90)\nplt.plot(t, ca, 'm-', label='BAT = 90s')\nplt.xlabel('Time (sec)')\nplt.ylabel('Plasma concentration (mM)')\nplt.legend()\nplt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "the dose defaults to 0.1- what happens if we change it too?\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "ca = osipi.aif_parker(t, BAT=0, dose=0.05)\nplt.plot(t, ca, 'b-', label='BAT = 0s, dose = 0.05')\nca = osipi.aif_parker(t, BAT=30, dose=0.1)\nplt.plot(t, ca, 'r-', label='BAT = 30s, dose = 0.1')\nca = osipi.aif_parker(t, BAT=60, dose=0.2)\nplt.plot(t, ca, 'g-', label='BAT = 60s, dose = 0.2')\nca = osipi.aif_parker(t, BAT=90, dose=0.3)\nplt.plot(t, ca, 'm-', label='BAT = 90s, dose = 0.3')\nplt.xlabel('Time (sec)')\nplt.ylabel('Plasma concentration (mM)')\nplt.legend()\nplt.show()\n\n# Choose the last image as a thumbnail for the gallery\n# sphinx_gallery_thumbnail_number = -1"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.10"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}