notebooks/line_doc.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# line documentation\n",
    "\n",
    "    \"\"\"return the figure of a linechart with the notes in the X axis and their value in the Y axis\n",
    "\n",
    "    Keyword arguments:\n",
    "    piece -- the absolute path to the .csv file containing the data or a DataFrame\n",
    "    pitch_type -- the type of data that you want to be read (default 'tpc'), 'pc' could be use for twelve parts chart tpc\n",
    "        form (tpc:[A, B#, Gbbb, ...], pc (pitch class):[0, 3, 7, ...])\n",
    "    measures -- give a set of measures example [5, 18], will display the notes of the measures 5 to 18 included\n",
    "    log -- if True the colors are distributed on a log scale, by default it's a lineare scale (default False)\n",
    "    vocabulary -- the conversion dictionary from pitch class to tpc(F#, A, ...) format,\n",
    "    pitch_class_display -- if True display the pitch class and no the tpc values and so the grid repeat itself.\n",
    "    duration -- tell him if he has to class the notes by their total duration or their number of appearance\n",
    "    fifths -- if True class the notes by fifths order, if not class by the chromatic order\n",
    "    figsize -- tell the size of the figure in inches [x, y]\n",
    "    xmin, xmax -- the notes that will be displayed are in this range according to this values\n",
    "        {0 : F, 1 : C, 2 : G, 3 : D, 4 : A, 5 : E, 6 : B} and +- 7 for a sharp and a flat\n",
    "    display -- if True the figure is displayed, if False it is hidden so you can have only the returned figure\n",
    "    **kwargs -- these arguments are redirected to the matplotlib.pyplot.pie function, see informations at\n",
    "                https://matplotlib.org/api/_as_gen/matplotlib.pyplot.bar.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pitchplots.static as pps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#piece = '../data/data_example.csv'\n",
    "import pitchplots.parser as ppp\n",
    "piece = ppp.xml_to_csv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fig is a matplotlib.figure.Figure, you can see the corresponding documentation below\n",
    "# https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html\n",
    "fig = pps.line(piece)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## default parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def line(\n",
    "    piece,\n",
    "    pitch_type='tpc',\n",
    "    measures=None,\n",
    "    log=False,\n",
    "    vocabulary={0:'C', 1:'Db', 2:'D', 3:'Eb', 4:'E', 5:'F', 6:'Gb', 7:'G', 8:'Ab', 9:'A', 10:'Bb', 11:'B'},\n",
    "    pitch_class_display=False,\n",
    "    duration=False, #TODO\n",
    "    fifths=True, #TODO\n",
    "    color='blue',\n",
    "    figsize=[14, 9],\n",
    "    xmin=None,\n",
    "    xmax=None,\n",
    "    display=True,\n",
    "    **kwargs):\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x648 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# It is better if pitch_type and pitch_class_display are the same,\n",
    "# meaning pitch_type='tpc' with pitch_class_display=False and like the example below\n",
    "pps.line(piece, pitch_type='pc', pitch_class_display=True, display=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x648 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# xmin and xmax indicate the limit notes on the X axis in the line of fifths\n",
    "pps.line(piece, color='grey', display=False, xmin=-3, xmax=11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}