CRIM_06_Homorhythm_Verovio.ipynb

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    "## Find Homorhythm\n",
    "\n",
    "#### This function predicts homorhythmic passages in a given piece.\n",
    "    \n",
    "The method follows various stages:\n",
    "- gets **durational ngrams**, and finds passages in which these are the same in **more than two voices at a given offsets**\n",
    "- gets **lyric ngrams**, and finds passages in which the **same sequence of two syllables** are heard successively in at least two voices at the **same offsets**.\n",
    "- checks the **number of active voices** (so that we can count the number moving on coordinated homorhythm\n",
    "\n",
    "to call the method:  \n",
    "\n",
    "```\n",
    "piece.homorhythm()\n",
    "```\n",
    "\n",
    "It is also possible to specify the length of the durational and lyric ngrams found in this method.  The default is 4.\n",
    "The argument `full_hr=True` will return HR passages of three or more voices.  `full_hr=False` returns even passages with just two voices in HR\n",
    "\n",
    "Typical use:\n",
    "\n",
    "```\n",
    "piece.homorhythm(ngram_length=4, full_hr=True)\n",
    "```\n",
    "\n",
    "\n",
    "\n",
    "##### View Score Excerpts with Verovio in the NB\n",
    "\n",
    "It is also possible to display the results of the Homorhythm method in the Notebook with Verovio. The excerpts vary in length. Sometimes the same measure is part of overlapping groups--more work is pending to solve this problem.\n",
    "\n",
    "The function also displays metadata about each excerpt: piece ID, composer, title, measures, and the minimum and maximum of voices in each passage moving in coordinated durations and syllables.\n",
    "\n",
    "To use the function, pass the piece, homorhythm data frame, url of the piece, and mei_file name (all loaded in the first part of this notebook) as follows:\n",
    "\n",
    "```\n",
    "piece.verovioHomorhythm()\n",
    "```\n",
    "\n",
    "#### Corpus with Verovio\n",
    "\n",
    "- Currently this is done as follows:\n",
    "\n",
    "Define corpus_list of file names\n",
    "\n",
    "* Read the documentation:  `print(piece.homorhythm.__doc__)`\n",
    "\n"
   ]
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     "text": [
      "saved_csv folder already exists.\n",
      "Music_Files folder already exists.\n"
     ]
    }
   ],
   "source": [
    "import intervals\n",
    "from intervals import * \n",
    "from intervals import main_objs\n",
    "import pandas as pd\n",
    "import re\n",
    "from ipywidgets import interact\n",
    "from pandas.io.json import json_normalize\n",
    "from IPython.display import display\n",
    "import os\n",
    "import numpy\n",
    "import itertools\n",
    "\n",
    "MYDIR = (\"saved_csv\")\n",
    "CHECK_FOLDER = os.path.isdir(MYDIR)\n",
    "\n",
    "# If folder doesn't exist, then create it.\n",
    "if not CHECK_FOLDER:\n",
    "    os.makedirs(MYDIR)\n",
    "    print(\"created folder : \", MYDIR)\n",
    "\n",
    "else:\n",
    "    print(MYDIR, \"folder already exists.\")\n",
    "    \n",
    "MUSDIR = (\"Music_Files\")\n",
    "CHECK_FOLDER = os.path.isdir(MUSDIR)\n",
    "\n",
    "# If folder doesn't exist, then create it.\n",
    "if not CHECK_FOLDER:\n",
    "    os.makedirs(MUSDIR)\n",
    "    print(\"created folder : \", MUSDIR)\n",
    "\n",
    "else:\n",
    "    print(MUSDIR, \"folder already exists.\")"
   ]
  },
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    "## Import Your Piece\n",
    "\n",
    "- Here you will want to select the appropriate 'prefix' that identifies the location of your file.\n",
    "- `'Music_Files/'` is for files in the local notebook; `'https://crimproject.org/mei/'` is for the files on CRIM.\n",
    "- Then provide the full name (and extension) of your music file, such as `'CRIM_Model_0038.mei'`"
   ]
  },
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     "text": [
      "Downloading remote score...\n",
      "Successfully imported https://crimproject.org/mei/CRIM_Model_0032.mei\n",
      "{'title': 'Sancta et immaculata virginitas', 'composer': 'Cristóbal de Morales'}\n"
     ]
    }
   ],
   "source": [
    "# Select a prefix:\n",
    "\n",
    "# prefix = 'Music_Files/'\n",
    "prefix = 'https://crimproject.org/mei/'\n",
    "\n",
    "# Add your filename here\n",
    "\n",
    "mei_file = 'CRIM_Model_0032.mei'\n",
    "\n",
    "url = prefix + mei_file\n",
    "\n",
    "piece = importScore(url)\n",
    "\n",
    "print(piece.metadata)"
   ]
  },
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       "                     active_voices  number_dur_ngrams           hr_voices  \\\n",
       "Measure Beat Offset                                                         \n",
       "25      2.0  194.0             2.0                1.0   [Superius, Tenor]   \n",
       "26      4.0  206.0             2.0                1.0  [Superius, Bassus]   \n",
       "83      4.0  662.0             2.0                1.0      [Altus, Tenor]   \n",
       "\n",
       "                                Superius            Altus               Tenor  \\\n",
       "Measure Beat Offset                                                             \n",
       "25      2.0  194.0    (sci, o, qui, bus)              NaN  (sci, o, qui, bus)   \n",
       "26      4.0  206.0   (qui, bus, te, lau)              NaN                 NaN   \n",
       "83      4.0  662.0                   NaN  (in, mu, li, e)     (in, mu, li, e)   \n",
       "\n",
       "                                  Bassus  \\\n",
       "Measure Beat Offset                        \n",
       "25      2.0  194.0                   NaN   \n",
       "26      4.0  206.0   (qui, bus, te, lau)   \n",
       "83      4.0  662.0                   NaN   \n",
       "\n",
       "                                                   syllable_set  \\\n",
       "Measure Beat Offset                                               \n",
       "25      2.0  194.0     [(sci, o, qui, bus), (sci, o, qui, bus)]   \n",
       "26      4.0  206.0   [(qui, bus, te, lau), (qui, bus, te, lau)]   \n",
       "83      4.0  662.0           [(in, mu, li, e), (in, mu, li, e)]   \n",
       "\n",
       "                     count_lyr_ngrams  active_syll_voices voice_match  \n",
       "Measure Beat Offset                                                    \n",
       "25      2.0  194.0                1.0                 2.0        True  \n",
       "26      4.0  206.0                1.0                 2.0        True  \n",
       "83      4.0  662.0                1.0                 2.0        True  "
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   "source": [
    "piece.homorhythm().head()"
   ]
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       "      <td>(qui, bus, te, lau)</td>\n",
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       "      <td>NaN</td>\n",
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       "                     active_voices  number_dur_ngrams           hr_voices  \\\n",
       "Measure Beat Offset                                                         \n",
       "25      2.0  194.0             2.0                1.0   [Superius, Tenor]   \n",
       "26      4.0  206.0             2.0                1.0  [Superius, Bassus]   \n",
       "83      4.0  662.0             2.0                1.0      [Altus, Tenor]   \n",
       "\n",
       "                                Superius            Altus               Tenor  \\\n",
       "Measure Beat Offset                                                             \n",
       "25      2.0  194.0    (sci, o, qui, bus)              NaN  (sci, o, qui, bus)   \n",
       "26      4.0  206.0   (qui, bus, te, lau)              NaN                 NaN   \n",
       "83      4.0  662.0                   NaN  (in, mu, li, e)     (in, mu, li, e)   \n",
       "\n",
       "                                  Bassus  \\\n",
       "Measure Beat Offset                        \n",
       "25      2.0  194.0                   NaN   \n",
       "26      4.0  206.0   (qui, bus, te, lau)   \n",
       "83      4.0  662.0                   NaN   \n",
       "\n",
       "                                                   syllable_set  \\\n",
       "Measure Beat Offset                                               \n",
       "25      2.0  194.0     [(sci, o, qui, bus), (sci, o, qui, bus)]   \n",
       "26      4.0  206.0   [(qui, bus, te, lau), (qui, bus, te, lau)]   \n",
       "83      4.0  662.0           [(in, mu, li, e), (in, mu, li, e)]   \n",
       "\n",
       "                     count_lyr_ngrams  active_syll_voices voice_match  \n",
       "Measure Beat Offset                                                    \n",
       "25      2.0  194.0                1.0                 2.0        True  \n",
       "26      4.0  206.0                1.0                 2.0        True  \n",
       "83      4.0  662.0                1.0                 2.0        True  "
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   "source": [
    "# now with longer ngrams\n",
    "\n",
    "piece.homorhythm(ngram_length=4, full_hr=True).head()"
   ]
  },
  {
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   "id": "75cf1858",
   "metadata": {},
   "source": [
    "### Print the Results with Verovio\n",
    "\n",
    "- Note that it's possible to use all of the same arguments as noted above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "daae7c0a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "piece.verovioHomorhythm(ngram_length=3, full_hr=True)"
   ]
  },
  {
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   "id": "a165bcb8",
   "metadata": {},
   "source": [
    "### Corpus and Homorhythm\n",
    "\n",
    "Define the corpus list:\n",
    "\n",
    "```\n",
    "corpus_list = ['https://crimproject.org/mei/CRIM_Model_0011.mei',\n",
    "              'https://crimproject.org/mei/CRIM_Model_0012.mei']\n",
    "```\n",
    "\n",
    "Import corpus:\n",
    "\n",
    "```\n",
    "corpus  = CorpusBase(corpus_list)\n",
    "```\n",
    "\n",
    "Set the length with 'ngram_length' and 'full_hr'  as True or False:\n",
    "\n",
    "```\n",
    "func = ImportedPiece.homorhythm\n",
    "list_of_hr = corpus.batch(func=func, kwargs={'ngram_length' : 8, \"full_hr\" : True}, metadata=True)\n",
    "\n",
    "combined_df = pd.concat(list_of_hr, ignore_index=False)\n",
    "combined_df.head(10)\n",
    "```\n",
    "\n"
   ]
  },
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   "source": [
    "corpus_list = ['https://crimproject.org/mei/CRIM_Model_0011.mei',\n",
    "              'https://crimproject.org/mei/CRIM_Model_0012.mei']\n",
    "corpus_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1cff844",
   "metadata": {},
   "outputs": [],
   "source": [
    "corpus  = CorpusBase(corpus_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "24cc41f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set the length with 'ngram_length'\n",
    "# set full_hr  as True or False\n",
    "\n",
    "func = ImportedPiece.homorhythm\n",
    "list_of_hr = corpus.batch(func=func, kwargs={'ngram_length' : 8, \"full_hr\" : True}, metadata=True)\n",
    "\n",
    "combined_df = pd.concat(list_of_hr, ignore_index=False)\n",
    "combined_df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83b17269",
   "metadata": {},
   "source": [
    "### Render HR Corpus with Verovio\n",
    "\n",
    "Define the corpus list:\n",
    "\n",
    "```\n",
    "corpus_list = ['https://crimproject.org/mei/CRIM_Model_0011.mei',\n",
    "              'https://crimproject.org/mei/CRIM_Model_0012.mei']\n",
    "```\n",
    "Call print function for each piece individually via 'for' loop:\n",
    "\n",
    "```\n",
    "for url in corpus_list:\n",
    "    piece = importScore(url)\n",
    "    piece.verovioHomorhythm(ngram_length=8, full_hr=True)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68b474a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "for url in corpus_list:\n",
    "    piece = importScore(url)\n",
    "    piece.verovioHomorhythm(ngram_length=8, full_hr=True)\n",
    "\n"
   ]
  },
  {
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