Matplotlib/Matplotlib_Errorbar_limit_selection.ipynb

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   "source": [
    "# Matplotlib - Errorbar Limit Selection\n",
    "<a href=\"https://bit.ly/3JyWIk6\">Give Feedback</a> | <a href=\"https://github.com/jupyter-naas/awesome-notebooks/issues/new?assignees=&labels=bug&template=bug_report.md&title=Matplotlib+-+Errorbar+Limit+Selection:+Error+short+description\">Bug report</a>"
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   "source": [
    "**Tags:** #matplotlib #chart #errorbar #dataviz #snippet #operations #image"
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   "source": [
    "**Author:** [Mardiat-Iman](https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262)"
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   "source": [
    "**Last update:** 2023-07-24 (Created: 2023-07-24)"
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   "source": [
    "**Description:** This notebook provides instructions on how to create illustrations of selectively drawing lower and/or upper limit symbols on errorbars using the parameters uplims, lolims of errorbar using Matplotlib."
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   "source": [
    "**References:** \n",
    "- [Errorbar Limit Selection](https://matplotlib.org/stable/gallery/lines_bars_and_markers/errorbar_limits_simple.html#sphx-glr-gallery-lines-bars-and-markers-errorbar-limits-simple-py)"
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   "source": [
    "## Input"
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   "source": [
    "### Import libraries"
   ]
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import naas"
   ]
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   "source": [
    "### Setup variables\n",
    "- `fig_path`: A string representing the path where the generated figure will be saved with the name \"fig.png\".\n",
    "- `x`: This is a NumPy array that represents the x-coordinates of the data points. It contains 10 values generated using `np.arange(10)`, which creates an array from 0 to 9.\n",
    "- `y`: This is a NumPy array that represents the y-coordinates of the data points. It is calculated as `2.5 * np.sin(x / 20 * np.pi)`, which scales the sine function values by 2.5. It is used to generate a sinusoidal curve.\n",
    "- `yerr`: This is a NumPy array that represents the magnitude of the error bars in the y-direction for each data point. It is created using `np.linspace(0.05, 0.2, 10)`, which generates 10 evenly spaced values from 0.05 to 0.2.\n",
    "- `upperlimits`: This is a boolean or an array of booleans that controls whether the upper error bar is drawn as an arrow (True) or as a simple line (False) for each data point. It is used to specify which data points should have upper error bars as arrows.\n",
    "- `lowerlimits`: This is a boolean or an array of booleans that controls whether the lower error bar is drawn as an arrow (True) or as a simple line (False) for each data point. It is used to specify which data points should have lower error bars as arrows."
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   "source": [
    "# Inputs\n",
    "x = np.arange(10)\n",
    "y = 2.5 * np.sin(x / 20 * np.pi)\n",
    "yerr = np.linspace(0.05, 0.2, 10)\n",
    "upperlimits = [True, False] * 5\n",
    "lowerlimits = [False, True] * 5\n",
    "\n",
    "# Outputs\n",
    "fig_path = \"fig.png\""
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   "source": [
    "## Model"
   ]
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   "source": [
    "### Plot the Graph"
   ]
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    "fig = plt.figure()\n",
    "\n",
    "plt.errorbar(x, y + 3, yerr=yerr, label='both limits (default)')\n",
    "\n",
    "plt.errorbar(x, y + 2, yerr=yerr, uplims=True, label='uplims=True')\n",
    "\n",
    "plt.errorbar(x, y + 1, yerr=yerr, uplims=True, lolims=True,\n",
    "             label='uplims=True, lolims=True')\n",
    "\n",
    "plt.errorbar(x, y, yerr=yerr, uplims=upperlimits, lolims=lowerlimits,\n",
    "             label='subsets of uplims and lolims')\n",
    "\n",
    "plt.legend(loc='lower right')"
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   "source": [
    "## Output"
   ]
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   "source": [
    "### Save the figure"
   ]
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    "fig.savefig(fig_path)"
   ]
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    "### Share asset with naas"
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