#############################################################
333855.923,4849928.319,335972.595,4852044.989
#############################################################
minx = 293176.154 maxx = 336612.886 dx = 43436.732
miny = 4827041.814 maxy = 4857580.084 dy = 30538.27
400x400 px = 333855.923,4849928.319,334914.259,4850986.654 800x800 px = 333855.923,4849928.319,335972.595,4852044.989
400x400 px d = 1058.335,1058.335 800x800 px d = 2116.67,2116.67
335972.595,4849928.319,338089.265,4852044.989
bbox for miny = 299838.375,4827041.814,302595.3397680129,4828100.150283633 bbox for minx = 293176.1542629752,4844835.079586833,295933.11811023625,4845893.415036838
bbox for maxx = 333855.92312251305,4849928.318939979,336612.8869697741,4850986.654389984 bbox for maxy = 329887.16518499714,4856521.748793509,332644.1290322582,4857580.084243514
wget -O - -o /dev/null "http://gis.toronto.ca/arcgis/rest/services/primary/cot_geospatial2_mtm/MapServer/export?dpi=96&transparent=true&format=svg&layers=show%3A8,3&bbox=302844.048,4846380.249,305601.012,4847438.584&bboxSR=2019&imageSR=2019&size=1042,400&f=image" > withlabels.svg
./bin/read_svg -f withlabels.svg
| ./bin/filter --column=tagName --value=tspan > tspan.b
./bin/read_svg -f withlabels.svg
| ./bin/filter --column=tagName --value=tspan --operator=DELETE
| ./bin/filter --column=tagName --value=rect --operator=DELETE > shapes.b
cat shapes.b | ./bin/tesselate > shapes.t.b
cat tspan.b | ./bin/join_geographic -f shapes.t.b | ./bin/unique --column=first_hit_shape_row_id > joined_geographic.b
cat shapes.b | ./bin/columns --remove=text | ./bin/join --join=left --right_file=joined_geographic.b --left_column=shape_row_id --right_column=first_hit_shape_row_id | ./bin/bounds --bbox=302844.048,305601.012,4847438.584,4846380.249 | ./bin/coordinate_convert | ./bin/inspect | ./bin/write_kml --filename=output.kml
wget -O - -o /dev/null "http://gis.toronto.ca/arcgis/rest/services/primary/cot_geospatial2_mtm/MapServer/export?dpi=96&transparent=true&format=svg&layers=show%3A8,3&bbox=305601.012,4846380.249,308357.976,4847438.584&bboxSR=2019&imageSR=2019&size=1042,400&f=image" > withlabels2.svg
./bin/read_svg -f withlabels2.svg
| ./bin/filter --column=tagName --value=tspan > tspan2.b
./bin/read_svg -f withlabels2.svg
| ./bin/filter --column=tagName --value=tspan --operator=DELETE
| ./bin/filter --column=tagName --value=rect --operator=DELETE > shapes2.b
cat shapes2.b | ./bin/tesselate > shapes2.t.b
cat tspan2.b | ./bin/join_geographic -f shapes2.t.b | ./bin/unique --column=first_hit_shape_row_id > joined_geographic2.b
cat shapes2.b | ./bin/columns --remove=text | ./bin/join --join=left --right_file=joined_geographic2.b --left_column=shape_row_id --right_column=first_hit_shape_row_id | ./bin/bounds --bbox=305601.012,308357.976,4847438.584,4846380.249 | ./bin/coordinate_convert | ./bin/inspect | ./bin/write_kml --filename=output2.kml
#############################################################
- zoom in?
- counts, such as number of addresses, number of bus stops
#############################################################
cat <(cat <(./bin/read_dem -f data/030/m/030m11/030m11_0200_demw.dem | ./bin/grayscale) <(./bin/read_dem -f data/030/m/030m11/030m11_0200_deme.dem | ./bin/grayscale)
<(./bin/read_dem -f data/030/m/030m12/030m12_0200_demw.dem | ./bin/grayscale) <(./bin/read_dem -f data/030/m/030m12/030m12_0200_deme.dem | ./bin/grayscale)
<(./bin/read_dem -f data/030/m/030m13/030m13_0200_demw.dem | ./bin/grayscale) <(./bin/read_dem -f data/030/m/030m13/030m13_0200_deme.dem | ./bin/grayscale)
<(./bin/read_dem -f data/030/m/030m14/030m14_0200_demw.dem | ./bin/grayscale) <(./bin/read_dem -f data/030/m/030m14/030m14_0200_deme.dem | ./bin/grayscale)
| ./bin/reduce_by_bbox -f <(cat data/canada.ontario.municipalities_on_land_reduced.b | ./bin/reduce_by_attribute -n LEGALNAME1 -v "City of Toronto" | ./bin/bbox -b 0.1))
> data/toronto.elevation.b
gcc src/pass_through_translate_colors_for_toronto_map.c bin/scheme.o -o bin/pass_through_translate_colors_for_toronto_map
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_1.png -z 1
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_2.png -z 2
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_3.png -z 3
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_4.png -z 4
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_5.png -z 5
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_6.png -z 6
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_7.png -z 7
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_8.png -z 8
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.25,0.25,0.25,1)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets.csv)
| ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_map_9.png -z 9
/ImageMagick-6.7.5/bin/montage /bin/ls toronto_map_* -geometry +0+0 toronto_map.all.png
#############################################################
blah
cat <(cat data/toronto.elevation.b | ./bin/transform -a 1 -s 0.3,0.3,0.3,1 | ./bin/transform -a 1 -s -1,-1,-1,1 | ./bin/transform -a 1 -o 1,1,1,0)
<(cat data.toronto.rivers.b | ./bin/add_color_from_csv -f <(echo "FCODE_DESC:River,red:0.6,green:0.6,blue:1.0"))
<(cat data/toronto.centreline.*.b | ./bin/add_color_from_csv -f colors_for_streets_white_background.csv)
<(cat data/toronto_addresses_colors_according_to_walking_distance_to_myttc_stop.b
data/toronto_addresses_where_walking_distance_to_a_road_was_over_250_meters.b
| ./bin/pass_through_translate_colors_for_toronto_map)
| ./bin/write_png -s particle.png -p 3 -w 1500 -z 9
#############################################################
cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_1.png -z 1 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_2.png -z 2 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_3.png -z 3 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_4.png -z 4 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_5.png -z 5 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_6.png -z 6 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_7.png -z 7 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_8.png -z 8 cat data/toronto.elevation.b | ./bin/write_png -s particle.png -p 3 -w 1000 -f toronto_elevation_9.png -z 9
/ImageMagick-6.7.5/bin/montage /bin/ls toronto_elevation_* -geometry +0+0 output.all.png
#############################################################
toronto tickets per minute throughout the day
./bin/read_mysql "select (round(substring(time_of_infraction,-2,2)) + round(substring(time_of_infraction,1,2))60) as x, count() y, 1 as unique_set_id from parking_tickets_toronto.parking_tickets group by x" | ./bin/transform -s 4 | ./bin/write_png
map of toronto tickets
./bin/read_mysql "select lat y, lng x, id, date_of_infraction date, time_of_infraction time from parking_tickets_toronto.parking_tickets where lat is not null AND date_of_infraction = 20101001 AND secs = 1" > toronto_parking_tickets.b
cat toronto_parking_tickets.b | ./bin/reduce_by_attribute -n date -v 20101001 > toronto_parking_tickets.20101001.b
cat toronto_parking_tickets.20101001.b | ./bin/reduce_by_bbox -f <(./bin/produce_unit_square -x -79.395835 -y 43.647616 -w 0.03 -h 0.03) | ./bin/write_png
#############################################################
read in a soundwave, calculating a sliding window rms with fft for color and normalize ranges to [0,1], output should have 1000 samples
./bin/read_soundwave -f data/mnm.wav -o 1000 -n -t > tempsoundwave.b
cat <(cat tempsoundwave.b | ./bin/reduce_by_attribute -n original_channel -v 0 | ./bin/transform -s 100)
<(cat tempsoundwave.b | ./bin/reduce_by_attribute -n original_channel -v 1 | ./bin/transform -s -100)
| ./bin/write_png
#############################################################
NO LONGER WORKS
Takes the first channel of a wave file, grabs the root mean square of that wave, normalizes it and writes it to json ./bin/read_soundwave -c 1 -f data/Mists_of_Time-4T.wav | ./bin/rms | ./bin/normalize | ./bin/write_json
#############################################################
NO LONGER WORKS
First channel of a wave file, rms, add color according to the FFT of that same data
./bin/read_soundwave -c 1 -f data/mnm.wav | ./bin/rms |
./bin/add_color_from_source_interpolation -f <(./bin/read_soundwave -c 1 -f data/mnm.wav | ./bin/fft_sliding_window) |
./bin/normalize |
./bin/write_json -w
#############################################################
This is for the viewing ttc vehicles, traveling along the which ever specific shape over time Assumes the following: 'nextbus' mysql database is setup and populated as the following: ./bin/read_nextbus -n 0 | ./bin/write_sql -de | mysql -uroot nextbus 'nextbus_null' mysql database is setup and populated as the following: ./bin/read_nextbus -n 0 -r '' | ./bin/write_sql -de | mysql -uroot nextbus_null 'ttc_gtfs' mysql database is setup and populated with ttc gtfs data (in the iroquois format, shapes and shape_points tables) 'nextbus_temp' mysql database is created (points table will be created, emptied)
#############################################################
./bin/read_mysql "SELECT shape_id = 192 as r, 0 as g, 0 as b, round((shape_id = 192) * 0.5) + (!(shape_id = 192))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (192,194) ORDER BY shape_id = '192' asc, shape_id, position" |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 194 as r, 0 as g, 0 as b, round((shape_id = 194) * 0.5) + (!(shape_id = 194))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (192,194) ORDER BY shape_id = '194' asc, shape_id, position") |
./bin/write_png
#############################################################
./bin/read_shapefile -f /work/data/canada/hydro_v3r1/hydro_candd.dbf
| ./bin/clip -f <(./bin/read_shapefile -f /work/data/canada/provinces/prov_ab_p_geo83_e.dbf | ./bin/reduce_by_attribute -n NAME -v ONTARIO) \
hydro.ontario.b
./bin/read_shapefile -f /work/data/canada/municipalities/ontario.dbf
| ./bin/clip -f hydro.ontario.b \
ontario.muni.b
cat ontario.muni.b
| ./bin/clip -f <(./bin/produce_unit_square -x -79.38698 -y 43.67008 -w 1.5 -h 1.5)
| ./bin/tesselate
| ./bin/add_color_from_csv -f colors_for_andrew.txt
| ./bin/write_png
#############################################################
cat <(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-12.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-12.dwg -l BUILDING_LINE*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-12.dwg -l BRIDGES*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-12.dwg -l PATHWAY*)
| ./bin/write_png
cat <(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-22.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-22.dwg -l BUILDING_LINE*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-22.dwg -l BRIDGES*)
| ./bin/write_png
cat <(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-12.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-12.dwg -l BUILDING_LINE*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-12.dwg -l BRIDGES*)
| ./bin/write_png
cat
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-13.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-13.dwg -l BUILDING_LINE*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-13.dwg -l BRIDGES*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50h-13.dwg -l PATHWAY*)
| ./bin/write_png
cat
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-23.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-23.dwg -l BUILDING_LINE*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-23.dwg -l BRIDGES*)
| ./bin/write_png
cat <(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-13.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-13.dwg -l BUILDING_LINE*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/50g-13.dwg -l BRIDGES*)
| ./bin/write_png
cat <(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/51h-11.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/51h-11.dwg -l BUILDING_LINE*)
| ./bin/write_png
cat <(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/51g-21.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/51g-21.dwg -l BUILDING_LINE*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/51g-11.dwg -l CURB*)
<(./bin/read_dwg -f /work/data/canada/toronto/city_toronto/51g-11.dwg -l BUILDING_LINE*)
| ./bin/write_png
#############################################################
cat <(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/49g-13-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/49j-13-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50g-11-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50g-12-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50g-13-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50g-21-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50g-22-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50g-23-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50h-11-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50h-12-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50h-21-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50h-22-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50j-11-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_dwg -f ../property_data_for_trinity_spadina_ward/50j-12-2000.dwg -l BUILDING_LINE* | ./bin/coordinate_convert from NAD83 UTM 17 T)
<(./bin/read_shapefile -f /work/data/canada/toronto/address_points/ADDRESS_POINT_WGS84.dbf -a 0 | ./bin/reduce_by_bbox -f <(./bin/read_shapefile -f /work/data/canada/toronto/wards/icitw_wgs84.dbf | ./bin/reduce_by_attribute -n SCODE_NAME -v 20 | ./bin/bbox))
<(./bin/read_shapefile -f /work/data/canada/toronto/wards/icitw_wgs84.dbf | ./bin/reduce_by_attribute -n SCODE_NAME -v 20)
| ./bin/add_random_colors
| ./bin/write_png -w 2500
| ./bin/clip -f <(./bin/read_shapefile -f /work/data/canada/toronto/wards/icitw_wgs84.dbf | ./bin/reduce_by_attribute -n SCODE_NAME -v 20) \
> buildings_in_trinity_spadina_ward20_wgs84.b
cat buildings_in_trinity_spadina_ward20_wgs84.b \
<(./bin/read_shapefile -f /work/data/canada/toronto/wards/icitw_wgs84.dbf | ./bin/reduce_by_attribute -n SCODE_NAME -v 20) \
| ./bin/add_random_colors \
| ./bin/write_png -w 2500
#############################################################
pretty elevation map, with toronto border, it's pretty
cat <(cat <(./bin/read_dem -f data/030/m/030m11/030m11_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m11/030m11_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m12/030m12_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m12/030m12_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m13/030m13_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m13/030m13_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m14/030m14_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m14/030m14_0200_deme.dem)
| ./bin/reduce_by_bbox -f <(cat data/canada.ontario.municipalities_on_land_reduced.b | ./bin/reduce_by_attribute -n LEGALNAME1 -v "City of Toronto" | ./bin/bbox -b 0.1))
<(cat data/canada.ontario.municipalities_on_land_reduced.b | ./bin/reduce_by_attribute -n LEGALNAME1 -v "City of Toronto" |
./bin/add_color_from_csv -f <(echo "LEGALNAME1:City of Toronto,red:0.8,green:0.4,blue:0.4"))
| ./bin/write_png
cat <(./bin/read_dem -f data/030/m/030m03/030m03_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m03/030m03_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m04/030m04_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m04/030m04_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m05/030m05_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m05/030m05_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m06/030m06_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m06/030m06_0200_deme.dem)
<(./bin/read_dem -f data/031/d/031d03/031d03_0200_demw.dem) <(./bin/read_dem -f data/031/d/031d03/031d03_0200_deme.dem)
<(./bin/read_dem -f data/031/d/031d04/031d04_0200_demw.dem) <(./bin/read_dem -f data/031/d/031d04/031d04_0200_deme.dem)
<(./bin/read_dem -f data/031/d/031d05/031d05_0200_demw.dem) <(./bin/read_dem -f data/031/d/031d05/031d05_0200_deme.dem)
<(./bin/read_dem -f data/031/d/031d06/031d06_0200_demw.dem) <(./bin/read_dem -f data/031/d/031d06/031d06_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m11/030m11_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m11/030m11_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m12/030m12_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m12/030m12_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m13/030m13_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m13/030m13_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m14/030m14_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m14/030m14_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m15/030m15_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m15/030m15_0200_deme.dem)
<(./bin/read_dem -f data/030/m/030m16/030m16_0200_demw.dem) <(./bin/read_dem -f data/030/m/030m16/030m16_0200_deme.dem)
| ./bin/write_png
#############################################################
./bin/read_mysql "SELECT shape_id = 871 as r, 0 as g, 0 as b, round((shape_id = 871) * 0.5) + (!(shape_id = 871))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '871' asc, shape_id, position" |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 872 as r, 0 as g, 0 as b, round((shape_id = 872) * 0.5) + (!(shape_id = 872))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '872' asc, shape_id, position") |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 873 as r, 0 as g, 0 as b, round((shape_id = 873) * 0.5) + (!(shape_id = 873))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '873' asc, shape_id, position" |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 874 as r, 0 as g, 0 as b, round((shape_id = 874) * 0.5) + (!(shape_id = 874))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '874' asc, shape_id, position")) |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 875 as r, 0 as g, 0 as b, round((shape_id = 875) * 0.5) + (!(shape_id = 875))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '875' asc, shape_id, position" |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 876 as r, 0 as g, 0 as b, round((shape_id = 876) * 0.5) + (!(shape_id = 876))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '876' asc, shape_id, position")) |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 877 as r, 0 as g, 0 as b, round((shape_id = 877) * 0.5) + (!(shape_id = 877))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '877' asc, shape_id, position" |
./bin/tile <(./bin/read_mysql "SELECT shape_id = 878 as r, 0 as g, 0 as b, round((shape_id = 878) * 0.5) + (!(shape_id = 878))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '878' asc, shape_id, position")) |
./bin/tile -y -f <(./bin/read_mysql "SELECT shape_id = 879 as r, 0 as g, 0 as b, round((shape_id = 879) * 0.5) + (!(shape_id = 879))* 0.1 as a, lat as y, lng as x, shape_id as id FROM ttc_gtfs.shape_points WHERE shape_id IN (871,872,873,874,875,876,877,878,879) ORDER BY shape_id = '879' asc, shape_id, position") |
./bin/write_png
#############################################################
./bin/read_mysql "select lat, lng, arrival_time as y, departure_time, trip_id as id, stop_sequence as x from ttc_gtfs.stop_times st left join ttc_gtfs.trips t using (gtfs_trip_id) left join ttc_gtfs.stops using (gtfs_stop_id) where route_id = 25 and service_id = 1 and shape_id = 192 order by trip_id, stop_sequence"
| ./bin/write_png
#############################################################
cat <(./bin/read_mysql "select 1 as r, 0 as g, 0 as b, 1 as a, lat as y, lng as x, ss.id as id, 1 as reported_at, 0 as vehicle_number from ttc_gtfs.shape_stops ss left join ttc_gtfs.stops s on ss.stop_id = s.id where shape_id = 192"
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 192 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_192
)
<(./bin/read_mysql "select x, y, id, -1 * (unix_timestamp() - unix_timestamp(created_at) - secsSinceReport) as reported_at, unique_set_id as vehicle_number, dirTag from nextbus.points where routeTag = 125 and round(secsSinceReport) < 6 order by dirTag, unique_set_id, created_at"
| ./bin/reduce_by_attribute -n dirTag -v 125_0_125
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 192 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_192
)
<(./bin/read_mysql "select x, y, id, -1 * (unix_timestamp() - unix_timestamp(created_at) - secsSinceReport) as reported_at, unique_set_id as vehicle_number, dirTag from nextbus.points where routeTag = 125 and round(secsSinceReport) < 6 order by dirTag, unique_set_id, created_at"
| ./bin/reduce_by_attribute -n dirTag -v 125_1_125
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 194 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_194 -i
)
| ./bin/write_png -f cache_images/ttc.125.to.finch.png
#############################################################
./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id IN (192) order by shape_id, position" \
125.shape.192.b
./bin/read_mysql "select x, y, id, unix_timestamp(created_at) as reported_at, secsSinceReport, unique_set_id as vehicle_number, dirTag from nextbus.points where routeTag = 125 order by dirTag, unique_set_id, created_at" \
125.gps.b
cat 125.gps.b
| ./bin/align_points_to_line_strips -f 125.shape.192.b \
125.aligned.b
cat 125.aligned.b
| ./bin/reduce_by_attribute -n dirTag -v 125_0_125
| ./bin/graph_ttc_performance
| ./bin/write_png
cat <(./bin/read_mysql "select 1 as r, 0 as g, 0 as b, 1 as a, lat as y, lng as x, ss.id as id, 1 as reported_at, 0 as vehicle_number from ttc_gtfs.shape_stops ss left join ttc_gtfs.stops s on ss.stop_id = s.id where shape_id = 192"
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 192 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_192
)
<(./bin/read_mysql "select x, y, id, -1 * (unix_timestamp() - unix_timestamp(created_at) - secsSinceReport) as reported_at, unique_set_id as vehicle_number, dirTag from nextbus.points where routeTag = 125 and round(secsSinceReport) < 6 order by dirTag, unique_set_id, created_at"
| ./bin/reduce_by_attribute -n dirTag -v 125_0_125
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 192 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_192
)
| ./bin/write_png -f cache_images/ttc.125.to.finch.png
./bin/read_mysql "select x, y, id, unix_timestamp(created_at) - (select min(unix_timestamp(created_at)) from nextbus.points where routeTag = 125 and round(secsSinceReport) < 6) - secsSinceReport as reported_at, unique_set_id as vehicle_number, dirTag from nextbus.points where routeTag = 125 and round(secsSinceReport) < 6 order by dirTag, unique_set_id, created_at"
| ./bin/reduce_by_attribute -n dirTag -v 125_1_125
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 194 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_194
| ./bin/write_png -f cache_images/ttc.125.to.antibes.png
./bin/read_mysql "select x, y, id, unix_timestamp(created_at) - (select min(unix_timestamp(created_at)) from nextbus.points where routeTag = 60 and round(secsSinceReport) < 6) - secsSinceReport as reported_at, unique_set_id as vehicle_number, dirTag from nextbus.points where routeTag = 60 and round(secsSinceReport) < 6 order by dirTag, unique_set_id, created_at"
| ./bin/reduce_by_attribute -n dirTag -v 60_0_60D
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 1020 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_1020
| ./bin/write_png -f cache_images/ttc.60D.to.signal.hill.png
./bin/read_mysql "select x, y, id, unix_timestamp(created_at) - (select min(unix_timestamp(created_at)) from nextbus.points where routeTag = 60 and round(secsSinceReport) < 6) - secsSinceReport as reported_at, unique_set_id as vehicle_number, dirTag from nextbus.points where routeTag = 60 and round(secsSinceReport) < 6 order by dirTag, unique_set_id, created_at"
| ./bin/reduce_by_attribute -n dirTag -v 60_1_60D
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 1027 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_1027
| ./bin/write_png -f cache_images/ttc.60D.to.finch.png
#############################################################
./bin/read_mysql "select lat as y, lng as x, ss.id as id, 1 as reported_at, 0 as vehicle_number from ttc_gtfs.shape_stops ss left join ttc_gtfs.stops s on ss.stop_id = s.id where shape_id = 192"
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc_gtfs.shape_points where shape_id = 192 order by shape_id, position")
| ./bin/graph_ttc_performance -a dist_line_192
| ./bin/write_png
#############################################################
./bin/read_mysql "select x, y, id, created_at as reported_at, unique_set_id as vehicle_number, secsSinceReport from nextbus.points where routeTag = 510 and dirTag = '510_0_510' order by unique_set_id, created_at"
| ./bin/align_points_to_line_strips -f <(./bin/read_mysql "SELECT lat as y, lng as x, shape_id as unique_set_id from ttc.shape_points where shape_id = 667 order by position")
| ./bin/write_sql -d
| mysql -uroot nextbus_temp
./bin/read_mysql "select (dist_line_667+0.0)/2 as x, unix_timestamp(reported_at) - (select min(unix_timestamp(reported_at)) from nextbus_temp.points) - secsSinceReport as y, vehicle_number as unique_set_id from nextbus_temp.points order by vehicle_number, reported_at"
| ./bin/write_png
#############################################################
./bin/read_mysql "SELECT lat as y, lng as x, shape_id as id FROM ontc.shape_points sp left join ontc.shapes s on sp.shape_id = s.id left join ontc.routes r on s.route_id = r.id WHERE r.agency_id = 37 order by shape_id, sequence"
| ./bin/write_png
./bin/read_mysql "SELECT s.lat as y, s.lng as x, fr.id as unique_set_id, 1 as s from ontc.fare_rules fr left join ontc.stops s on fr.origin_id = s.id WHERE fr.ccf_code LIKE 'ON%' UNION SELECT s.lat as y, s.lng as x, fr.id as unique_set_id, 2 as s from ontc.fare_rules fr left join ontc.stops s on fr.destination_id = s.id WHERE fr.ccf_code LIKE 'ON%' ORDER BY unique_set_id, s"
| ./bin/write_png