266 lines
7.4 KiB
Plaintext
266 lines
7.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Group recordings in 4 Frysian dialect regions\n",
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"\n",
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" * Klaaifrysk\n",
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" * Waldfrysk\n",
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" * Sudwesthoeksk\n",
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" * Noardhoeksk\n",
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" \n",
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"First run `Dialect Regions from image.ipynb`.\n",
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"\n",
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""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from math import floor\n",
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"import json\n",
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"import pandas\n",
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"import MySQLdb\n",
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"from collections import Counter\n",
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"\n",
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"from math import sqrt\n",
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"import numpy as np\n",
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"from shapely.geometry import shape, Point\n",
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"from vincenty import vincenty\n",
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"\n",
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"from jupyter_progressbar import ProgressBar\n",
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"\n",
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"db = MySQLdb.connect(user='root', passwd='Nmmxhjgt1@', db='stimmen', charset='utf8')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Input\n",
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"\n",
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"Load the geojson with the dialect region and create shapely shapes."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"with open('dialect_regions.geojson', 'r') as f:\n",
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" geojson = json.load(f)\n",
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"\n",
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"dialect_regions = [region['properties']['dialect'] for region in geojson['features']]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"shapes = {\n",
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" feature['properties']['dialect']: shape(feature['geometry'])\n",
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" for feature in geojson['features']\n",
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"}\n",
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"\n",
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"def regions_for(coordinate):\n",
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" regions = {\n",
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" region_name\n",
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" for region_name, shape in shapes.items()\n",
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" if shape.contains(Point(*coordinate))\n",
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" }\n",
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" return regions\n",
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"\n",
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"def distance_to_shape(shape, longitude, latitude):\n",
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" ext = shape.exterior\n",
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" p = ext.interpolate(ext.project(Point(longitude, latitude)))\n",
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" return vincenty((latitude, longitude), (p.y, p.x))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Query and process\n",
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"\n",
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"Query all picture game and free speech recordings and assign the dialect region."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"def dialect_regions_and_distance(data):\n",
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" return[\n",
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" {\n",
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" 'dialects': [\n",
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" {\n",
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" 'dialect': dialect,\n",
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" 'boundary_distance': distance_to_shape(shapes[dialect], longitude, latitude),\n",
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" }\n",
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" for dialect in regions_for((longitude, latitude))\n",
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" ],\n",
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" 'filename': filename,\n",
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" }\n",
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" for filename, (latitude, longitude) in ProgressBar(\n",
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" data[['latitude', 'longitude']].iterrows(),\n",
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" size=len(data)\n",
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" )\n",
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" ]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"picture_games = pandas.read_sql('''\n",
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"SELECT language.name as language, item.name as picture,\n",
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" survey.user_lat as latitude, survey.user_lng as longitude,\n",
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" survey.area_name as area, survey.country_name as country,\n",
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" result.recording as filename,\n",
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" result.submitted_at as date\n",
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"FROM core_surveyresult as survey\n",
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"INNER JOIN core_picturegameresult as result ON survey.id = result.survey_result_id\n",
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"INNER JOIN core_language as language ON language.id = result.language_id\n",
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"INNER JOIN core_picturegameitem as item\n",
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" ON result.picture_game_item_id = item.id\n",
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"''', db)\n",
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"picture_games.set_index('filename', inplace=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "67ed3190256b447c81daf3df1f189318",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"VBox(children=(HBox(children=(FloatProgress(value=0.0, max=1.0), HTML(value='<b>0</b>s passed', placeholder='0…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"dialect_region_per_picture_game = dialect_regions_and_distance(picture_games)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pandas.DataFrame([\n",
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" [r['filename'], r['dialects'][0]['dialect'], r['dialects'][0]['boundary_distance']]\n",
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" for r in dialect_region_per_picture_game\n",
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" if len(r['dialects']) == 1\n",
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"], columns = ['filename', 'dialect', 'boundary_distance'])\n",
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"\n",
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"df.to_excel('../data/picture_game_recordings_by_dialect.xlsx')\n",
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"df.to_csv('../data/picture_game_recordings_by_dialect.csv')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"free_speech_games = pandas.read_sql('''\n",
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"SELECT language.name as language,\n",
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" survey.user_lat as latitude, survey.user_lng as longitude,\n",
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" survey.area_name as area, survey.country_name as country,\n",
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" result.recording as filename,\n",
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" result.submitted_at as date\n",
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"FROM core_surveyresult as survey\n",
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"INNER JOIN core_freespeechresult as result ON survey.id = result.survey_result_id\n",
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"INNER JOIN core_language as language ON language.id = result.language_id\n",
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"''', db)\n",
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"free_speech_games.set_index('filename', inplace=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "201b0aed64e8494db603de15b560d919",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"VBox(children=(HBox(children=(FloatProgress(value=0.0, max=1.0), HTML(value='<b>0</b>s passed', placeholder='0…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"dialect_region_per_free_speech = dialect_regions_and_distance(free_speech_games)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pandas.DataFrame([\n",
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" [r['filename'], r['dialects'][0]['dialect'], r['dialects'][0]['boundary_distance']]\n",
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" for r in dialect_region_per_free_speech\n",
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" if len(r['dialects']) == 1\n",
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"], columns = ['filename', 'dialect', 'boundary_distance'])\n",
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"\n",
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"df.to_excel('../data/free_speech_recordings_by_dialect.xlsx')\n",
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"df.to_csv('../data/free_speech_recordings_by_dialect.csv')"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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