cleanup notebooks Frysian dialect regions

This commit is contained in:
H.T. Kruitbosch 2018-09-28 12:28:54 +02:00
parent 6968a587ba
commit b3a56c25d7
9 changed files with 39406 additions and 1438 deletions

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data/all.txt
data/left_over.zip
__pycache__
*.pyc
.idea/
.ipynb_checkpoints/

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# Stimmen Fryslan
## Notebooks
# Extract Frysian dialect regions
### Extract Frysian dialect regions
[notebook](notebooks/Dialect%20Regions%20from%20image.ipynb)
@ -9,4 +10,23 @@ Get polygons of dialect regions as mapped in this image
![dialect regions](data/dialects.png)
using image processing
using image processing.
Results
* [notebooks/dialect_regions.geojson](notebooks/dialect_regions.geojson)
### Group recordings to Frysian dialect regions
[notebook](notebooks/Group%20recordings%20in%204%20Frysian%20dialect%20regions.ipynb)
Create spreadsheets with the recordings assigned to dialect regions.
Results
* [data/picture_game_recordings_by_dialect.csv](data/picture_game_recordings_by_dialect.csv)
* [data/picture_game_recordings_by_dialect.csv](data/picture_game_recordings_by_dialect.xlsx)
* [data/free_speech_recordings_by_dialect.xlsx](data/free_speech_recordings_by_dialect.csv)
* [data/free_speech_recordings_by_dialect.xlsx](data/free_speech_recordings_by_dialect.xlsx)

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,filename,dialect,boundary_distance
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3,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_111_0i5tx.wav,Waldfrysk,9.903196
4,free_speech_recordings/Frysk/2017-07-05/fs_joke_99_qt49n.wav,Waldfrysk,10.22498
5,free_speech_recordings/Frysk/2017-07-05/fs_joke_113_bc6pq.wav,Waldfrysk,10.355398
6,free_speech_recordings/Frysk/2017-07-05/fs_joke_123_rcqai.wav,Waldfrysk,10.45873
7,free_speech_recordings/Frysk/2017-07-05/fs_your-own-story_113_68aqo.wav,Waldfrysk,10.355398
8,free_speech_recordings/Frysk/2017-07-05/fs_joke_123_ut0k4.wav,Waldfrysk,10.45873
9,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_99_sykw2.wav,Waldfrysk,10.22498
10,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_123_pj8uq.wav,Waldfrysk,10.45873
11,free_speech_recordings/Frysk/2017-07-05/fs_growing-up_123_7y4am.wav,Waldfrysk,10.45873
12,free_speech_recordings/English/2017-07-05/fs_what-would-you-do-with-a-million-euros_151_k4swb.wav,Waldfrysk,4.19475
13,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_164_uaqwl.wav,Waldfrysk,1.38699
14,free_speech_recordings/Nederlands/2017-07-05/fs_what-would-you-do-with-a-million-euros_146_v72do.wav,Waldfrysk,1.583635
15,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_109_d2ivw.wav,Waldfrysk,9.879676
16,free_speech_recordings/Nederlands/2017-07-05/fs_favourite-recipes_146_uh9n4.wav,Waldfrysk,1.583635
17,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_149_41fai.wav,Waldfrysk,10.621441
18,free_speech_recordings/Frysk/2017-07-05/fs_growing-up_128_e7hnl.wav,Waldfrysk,1.572799
19,free_speech_recordings/Frysk/2017-07-05/fs_joke_149_ti8sz.wav,Waldfrysk,10.621441
20,free_speech_recordings/English/2017-07-05/fs_what-would-you-do-with-a-million-euros_128_uf6gr.wav,Waldfrysk,1.572799
21,free_speech_recordings/Frysk/2017-07-05/fs_your-own-story_149_tec70.wav,Waldfrysk,10.621441
22,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_187_zp2j8.wav,Waldfrysk,3.341861
23,free_speech_recordings/Nederlands/2017-07-05/fs_joke_197_2lrb1.wav,Waldfrysk,4.704471
24,free_speech_recordings/Frysk/2017-07-05/fs_joke_199_6eozl.wav,Waldfrysk,1.358243
25,free_speech_recordings/Nederlands/2017-07-05/fs_joke_197_i7uw4.wav,Waldfrysk,4.704471
26,free_speech_recordings/Frysk/2017-07-05/fs_growing-up_188_7yaz3.wav,Waldfrysk,1.436183
27,free_speech_recordings/Frysk/2017-07-05/fs_read-a-text-2_200_a3is2.wav,Waldfrysk,4.478677
28,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_199_vg1kl.wav,Waldfrysk,1.358243
29,free_speech_recordings/Nederlands/2017-07-05/fs_joke_259_yorak.wav,Waldfrysk,3.935489
30,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_269_i4kag.wav,Waldfrysk,1.447555
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32,free_speech_recordings/Nederlands/2017-07-05/fs_what-would-you-do-with-a-million-euros_260_m2k6h.wav,Waldfrysk,0.846626
33,free_speech_recordings/Nederlands/2017-07-05/fs_joke_255_rj4m1.wav,Waldfrysk,7.027236
34,free_speech_recordings/Nederlands/2017-07-05/fs_favourite-recipes_240_fo1nd.wav,Waldfrysk,4.235696
35,free_speech_recordings/Nederlands/2017-07-05/fs_favourite-recipes_260_ig2yw.wav,Waldfrysk,0.846626
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50,free_speech_recordings/Frysk/2017-07-05/fs_what-would-you-do-with-a-million-euros_388_ank2d.wav,Waldfrysk,10.677306
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53,free_speech_recordings/Frysk/2017-09-20/fs_what-is-your-word-for_640_4bz56.wav,Klaaifrysk,9.595256
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Group recordings in 4 Frysian dialect regions\n",
"\n",
" * Klaaifrysk\n",
" * Waldfrysk\n",
" * Sudwesthoeksk\n",
" * Noardhoeksk\n",
" \n",
"First run `Dialect Regions from image.ipynb`.\n",
"\n",
"![dialect regions](../data/dialects.png)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from math import floor\n",
"import json\n",
"import pandas\n",
"import MySQLdb\n",
"from collections import Counter\n",
"\n",
"from math import sqrt\n",
"import numpy as np\n",
"from shapely.geometry import shape, Point\n",
"from vincenty import vincenty\n",
"\n",
"from jupyter_progressbar import ProgressBar\n",
"\n",
"db = MySQLdb.connect(user='root', passwd='Nmmxhjgt1@', db='stimmen', charset='utf8')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Input\n",
"\n",
"Load the geojson with the dialect region and create shapely shapes."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"with open('dialect_regions.geojson', 'r') as f:\n",
" geojson = json.load(f)\n",
"\n",
"dialect_regions = [region['properties']['dialect'] for region in geojson['features']]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"shapes = {\n",
" feature['properties']['dialect']: shape(feature['geometry'])\n",
" for feature in geojson['features']\n",
"}\n",
"\n",
"def regions_for(coordinate):\n",
" regions = {\n",
" region_name\n",
" for region_name, shape in shapes.items()\n",
" if shape.contains(Point(*coordinate))\n",
" }\n",
" return regions\n",
"\n",
"def distance_to_shape(shape, longitude, latitude):\n",
" ext = shape.exterior\n",
" p = ext.interpolate(ext.project(Point(longitude, latitude)))\n",
" return vincenty((latitude, longitude), (p.y, p.x))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Query and process\n",
"\n",
"Query all picture game and free speech recordings and assign the dialect region."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def dialect_regions_and_distance(data):\n",
" return[\n",
" {\n",
" 'dialects': [\n",
" {\n",
" 'dialect': dialect,\n",
" 'boundary_distance': distance_to_shape(shapes[dialect], longitude, latitude),\n",
" }\n",
" for dialect in regions_for((longitude, latitude))\n",
" ],\n",
" 'filename': filename,\n",
" }\n",
" for filename, (latitude, longitude) in ProgressBar(\n",
" data[['latitude', 'longitude']].iterrows(),\n",
" size=len(data)\n",
" )\n",
" ]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"picture_games = pandas.read_sql('''\n",
"SELECT language.name as language, item.name as picture,\n",
" survey.user_lat as latitude, survey.user_lng as longitude,\n",
" survey.area_name as area, survey.country_name as country,\n",
" result.recording as filename,\n",
" result.submitted_at as date\n",
"FROM core_surveyresult as survey\n",
"INNER JOIN core_picturegameresult as result ON survey.id = result.survey_result_id\n",
"INNER JOIN core_language as language ON language.id = result.language_id\n",
"INNER JOIN core_picturegameitem as item\n",
" ON result.picture_game_item_id = item.id\n",
"''', db)\n",
"picture_games.set_index('filename', inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "67ed3190256b447c81daf3df1f189318",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox(children=(HBox(children=(FloatProgress(value=0.0, max=1.0), HTML(value='<b>0</b>s passed', placeholder='0…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dialect_region_per_picture_game = dialect_regions_and_distance(picture_games)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"df = pandas.DataFrame([\n",
" [r['filename'], r['dialects'][0]['dialect'], r['dialects'][0]['boundary_distance']]\n",
" for r in dialect_region_per_picture_game\n",
" if len(r['dialects']) == 1\n",
"], columns = ['filename', 'dialect', 'boundary_distance'])\n",
"\n",
"df.to_excel('../data/picture_game_recordings_by_dialect.xlsx')\n",
"df.to_csv('../data/picture_game_recordings_by_dialect.csv')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"free_speech_games = pandas.read_sql('''\n",
"SELECT language.name as language,\n",
" survey.user_lat as latitude, survey.user_lng as longitude,\n",
" survey.area_name as area, survey.country_name as country,\n",
" result.recording as filename,\n",
" result.submitted_at as date\n",
"FROM core_surveyresult as survey\n",
"INNER JOIN core_freespeechresult as result ON survey.id = result.survey_result_id\n",
"INNER JOIN core_language as language ON language.id = result.language_id\n",
"''', db)\n",
"free_speech_games.set_index('filename', inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "201b0aed64e8494db603de15b560d919",
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"version_minor": 0
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"text/plain": [
"VBox(children=(HBox(children=(FloatProgress(value=0.0, max=1.0), HTML(value='<b>0</b>s passed', placeholder='0…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dialect_region_per_free_speech = dialect_regions_and_distance(free_speech_games)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"df = pandas.DataFrame([\n",
" [r['filename'], r['dialects'][0]['dialect'], r['dialects'][0]['boundary_distance']]\n",
" for r in dialect_region_per_free_speech\n",
" if len(r['dialects']) == 1\n",
"], columns = ['filename', 'dialect', 'boundary_distance'])\n",
"\n",
"df.to_excel('../data/free_speech_recordings_by_dialect.xlsx')\n",
"df.to_csv('../data/free_speech_recordings_by_dialect.csv')"
]
}
],
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