def draw_choropleth_map(spark): df = spark.read.format("csv").option("header", True).option( "delimiter", "," ).schema( "VendorID string, tpep_pickup_datetime timestamp, tpep_dropoff_datetime timestamp, passenger_count long, trip_distance double, pickup_longitude double, pickup_latitude double, dropoff_longitude double, dropoff_latitude double, fare_amount double, tip_amount double, total_amount double, buildingid_pickup long, buildingid_dropoff long, buildingtext_pickup string, buildingtext_dropoff string" ).load("file:///tmp/0_5M_nyc_taxi_and_building.csv").cache() df.show(20, False) df.createOrReplaceTempView("nyc_taxi") # df.createOrReplaceGlobalTempView("nyc_taxi") res = spark.sql( "select buildingtext_dropoff as wkt, passenger_count as w from nyc_taxi" ) res.printSchema() res.createOrReplaceTempView("pickup") vega_choropleth_map = VegaChoroplethMap( 1900, 1410, [-73.984092, 40.753893, -73.977588, 40.756342], "blue_to_red", [2.5, 5], 1.0) vega = vega_choropleth_map.build() res = choroplethmap(res, vega) save_png(res, '/tmp/choroplethmap.png') spark.sql("show tables").show() spark.catalog.dropGlobalTempView("nyc_taxi")
def draw_choropleth_map(spark): start_time = time.time() df = spark.read.format("csv").option("header", True).option( "delimiter", "," ).schema( "VendorID string, tpep_pickup_datetime timestamp, tpep_dropoff_datetime timestamp, passenger_count long, trip_distance double, pickup_longitude double, pickup_latitude double, dropoff_longitude double, dropoff_latitude double, fare_amount double, tip_amount double, total_amount double, buildingid_pickup long, buildingid_dropoff long, buildingtext_pickup string, buildingtext_dropoff string" ).load("file:///tmp/0_5M_nyc_taxi_and_building.csv").cache() df.createOrReplaceTempView("nyc_taxi") register_funcs(spark) res = spark.sql( "select ST_GeomFromText(buildingtext_dropoff) as polygon, passenger_count as w from nyc_taxi where (buildingtext_dropoff!='')" ) vega1 = vega_choroplethmap( 1900, 1410, bounding_box=[-73.994092, 40.753893, -73.977588, 40.759642], color_gradient=["#0000FF", "#FF0000"], color_bound=[2.5, 5], opacity=1.0, coordinate_system='EPSG:4326') res1 = choroplethmap(vega1, res) save_png(res1, '/tmp/choroplethmap1.png') spark.sql("show tables").show() spark.catalog.dropGlobalTempView("nyc_taxi") print("--- %s seconds ---" % (time.time() - start_time))
def db_query(): """ /db/query handler """ log.INSTANCE.info('POST /db/query: {}'.format(request.json)) if not utils.check_json(request.json, 'id') \ or not utils.check_json(request.json, 'query') \ or not utils.check_json(request.json['query'], 'type') \ or not utils.check_json(request.json['query'], 'sql'): return jsonify(status='error', code=-1, message='query format error') query_sql = request.json['query']['sql'] query_type = request.json['query']['type'] content = {} content['sql'] = query_sql content['err'] = False db_instance = db.CENTER.get(str(request.json['id']), None) if db_instance is None: return jsonify(status="error", code=-1, message='there is no database whose id equal to ' + str(request.json['id'])) if query_type == 'sql': res = db_instance.run_for_json(query_sql) data = [] for row in res: obj = json.loads(row) data.append(obj) content['result'] = data else: if not utils.check_json(request.json['query'], 'params'): return jsonify(status='error', code=-1, message='query format error') query_params = request.json['query']['params'] res = db_instance.run(query_sql) if query_type == 'point': vega = vega_pointmap(int(query_params['width']), int(query_params['height']), query_params['point']['bounding_box'], int(query_params['point']['point_size']), query_params['point']['point_color'], float(query_params['point']['opacity']), query_params['point']['coordinate_system']) data = pointmap(vega, res) content['result'] = data elif query_type == 'heat': vega = vega_heatmap(int(query_params['width']), int(query_params['height']), query_params['heat']['bounding_box'], float(query_params['heat']['map_zoom_level']), query_params['heat']['coordinate_system'], query_params['heat']['aggregation_type']) data = heatmap(vega, res) content['result'] = data elif query_type == 'choropleth': vega = vega_choroplethmap( int(query_params['width']), int(query_params['height']), query_params['choropleth']['bounding_box'], query_params['choropleth']['color_gradient'], query_params['choropleth']['color_bound'], float(query_params['choropleth']['opacity']), query_params['choropleth']['coordinate_system'], query_params['choropleth']['aggregation_type']) data = choroplethmap(vega, res) content['result'] = data elif query_type == 'weighted': vega = vega_weighted_pointmap( int(query_params['width']), int(query_params['height']), query_params['weighted']['bounding_box'], query_params['weighted']['color_gradient'], query_params['weighted']['color_bound'], query_params['weighted']['size_bound'], float(query_params['weighted']['opacity']), query_params['weighted']['coordinate_system']) data = weighted_pointmap(vega, res) content['result'] = data elif query_type == 'icon': vega = vega_icon(int(query_params['width']), int(query_params['height']), query_params['icon']['bounding_box'], query_params['icon']['icon_path'], query_params['icon']['coordinate_system']) data = icon_viz(vega, res) content['result'] = data else: return jsonify(status="error", code=-1, message='{} not support'.format(query_type)) return jsonify(status="success", code=200, data=content)
def db_query(): """ /db/query handler """ if not utils.check_json(request.json, 'id') \ or not utils.check_json(request.json, 'query') \ or not utils.check_json(request.json['query'], 'type') \ or not utils.check_json(request.json['query'], 'sql'): return jsonify(status='error', code=-1, message='query format error') query_sql = request.json['query']['sql'] query_type = request.json['query']['type'] content = {} content['sql'] = query_sql content['err'] = False if query_type == 'sql': res = spark.Spark.run_for_json(query_sql) data = [] for row in res: obj = json.loads(row) data.append(obj) content['result'] = data else: if not utils.check_json(request.json['query'], 'params'): return jsonify(status='error', code=-1, message='query format error') query_params = request.json['query']['params'] res = spark.Spark.run(query_sql) if query_type == 'point': vega = vega_pointmap(int(query_params['width']), int(query_params['height']), query_params['point']['bounding_box'], int(query_params['point']['stroke_width']), query_params['point']['stroke'], float(query_params['point']['opacity']), query_params['point']['coordinate']) data = pointmap(res, vega) content['result'] = data elif query_type == 'heat': vega = vega_heatmap(int(query_params['width']), int(query_params['height']), float(query_params['heat']['map_scale']), query_params['heat']['bounding_box'], query_params['heat']['coordinate']) data = heatmap(res, vega) content['result'] = data elif query_type == 'choropleth': vega = vega_choroplethmap( int(query_params['width']), int(query_params['height']), query_params['choropleth']['bounding_box'], query_params['choropleth']['color_style'], query_params['choropleth']['rule'], float(query_params['choropleth']['opacity']), query_params['choropleth']['coordinate']) data = choroplethmap(res, vega) content['result'] = data else: return jsonify(status="error", code=-1, message='{} not support'.format(query_type)) return jsonify(status="success", code=200, data=content)
coordinate_system="EPSG:4326") res = heatmap(vega, pickup_df) save_png(res, "/tmp/arctern_heatmap.png") # 在指定地理区域(经度范围:-73.991504 至 -73.945155;纬度范围:40.770759 至 40.783434)中随机选取 200 个坐标点,并将 fare_amount 作为颜色权重。 pickup_sql = f"select ST_GeomFromText(buildingtext_pickup) as buildings, fare_amount as color_weight from nyc_taxi where (pickup_longitude between {pos1[0]} and {pos2[0]}) and (pickup_latitude between {pos1[1]} and {pos2[1]}) and (buildingtext_pickup!='') limit {limit_num}" pickup_df = spark.sql(pickup_sql) # 根据查询结果绘制轮廓图图层。轮廓的填充颜色根据 color_weight 在 "#115f9a" ~ "#d0f400" 之间变化。 vega = vega_choroplethmap(1024, 384, bounding_box=[pos1[0], pos1[1], pos2[0], pos2[1]], color_gradient=["#115f9a", "#d0f400"], color_bound=[2.5, 5], opacity=1.0, coordinate_system="EPSG:4326") res = choroplethmap(vega, pickup_df) save_png(res, "/tmp/arctern_choroplethmap.png") # 在指定地理区域(经度范围:-73.991504 至 -73.945155;纬度范围:40.770759 至 40.783434)中随机选取 25 个坐标点。 pickup_sql = f"select st_point(pickup_longitude, pickup_latitude) from nyc_taxi where (pickup_longitude between {pos1[0]} and {pos2[0]}) and (pickup_latitude between {pos1[1]} and {pos2[1]}) limit 25" pickup_df = spark.sql(pickup_sql) # 根据查询结果绘制图标图图层。 # 注意: 请将 /path/to/icon.png 改为 png 文件所在的绝对路径 vega = vega_icon(1024, 384, bounding_box=[pos1[0], pos1[1], pos2[0], pos2[1]], icon_path='/path/to/icon.png', coordinate_system="EPSG:4326") res = icon_viz(vega, pickup_df) save_png(res, "/tmp/arctern_iconviz.png")
def run_test_choropleth_map(spark): df = spark.read.format("csv").option("header", True).option("delimiter", ",").schema( "VendorID string, tpep_pickup_datetime timestamp, tpep_dropoff_datetime timestamp, passenger_count long, " "trip_distance double, pickup_longitude double, pickup_latitude double, dropoff_longitude double, " "dropoff_latitude double, fare_amount double, tip_amount double, total_amount double, buildingid_pickup long, " "buildingid_dropoff long, buildingtext_pickup string, buildingtext_dropoff string").load( file_path).cache() df.createOrReplaceTempView("nyc_taxi") res = spark.sql("select buildingtext_dropoff as wkt, passenger_count as w from nyc_taxi") # 1-9 test color_style # 1 blue_to_red vega_1 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "blue_to_red", [2.5, 5], 1.0, 'EPSG:4326') baseline1 = choroplethmap(res, vega_1) choropleth_map1_1 = choroplethmap(res, vega_1) choropleth_map1_2 = choroplethmap(res, vega_1) baseline_png1 = png_path + "choropleth_map_nyc_1.png" save_png(baseline1, baseline_png1) save_png(choropleth_map1_1, png_path + "test_choropleth_map_nyc_1-1.png") save_png(choropleth_map1_2, png_path + "test_choropleth_map_nyc_1-2.png") # 2 green_yellow_red vega_2 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "green_yellow_red", [2.5, 5], 1.0, 'EPSG:4326') baseline2 = choroplethmap(res, vega_2) choropleth_map2_1 = choroplethmap(res, vega_2) choropleth_map2_2 = choroplethmap(res, vega_2) baseline_png2 = png_path + "choropleth_map_nyc_2.png" save_png(baseline2, baseline_png2) save_png(choropleth_map2_1, png_path + "test_choropleth_map_nyc_2-1.png") save_png(choropleth_map2_2, png_path + "test_choropleth_map_nyc_2-2.png") # 3 blue_white_red vega_3 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "blue_white_red", [2.5, 5], 1.0, 'EPSG:4326') baseline3 = choroplethmap(res, vega_3) choropleth_map3_1 = choroplethmap(res, vega_3) choropleth_map3_2 = choroplethmap(res, vega_3) baseline_png3 = png_path + "choropleth_map_nyc_3.png" save_png(baseline3, baseline_png3) save_png(choropleth_map3_1, png_path + "test_choropleth_map_nyc_3-1.png") save_png(choropleth_map3_2, png_path + "test_choropleth_map_nyc_3-2.png") # 4 skyblue_to_white vega_4 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "skyblue_to_white", [2.5, 5], 1.0, 'EPSG:4326') baseline4 = choroplethmap(res, vega_4) choropleth_map4_1 = choroplethmap(res, vega_4) choropleth_map4_2 = choroplethmap(res, vega_4) baseline_png4 = png_path + "choropleth_map_nyc_4.png" save_png(baseline4, baseline_png4) save_png(choropleth_map4_1, png_path + "test_choropleth_map_nyc_4-1.png") save_png(choropleth_map4_2, png_path + "test_choropleth_map_nyc_4-2.png") # 5 purple_to_yellow vega_5 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 1.0, 'EPSG:4326') baseline5 = choroplethmap(res, vega_5) choropleth_map5_1 = choroplethmap(res, vega_5) choropleth_map5_2 = choroplethmap(res, vega_5) baseline_png5 = png_path + "choropleth_map_nyc_5.png" save_png(baseline5, baseline_png5) save_png(choropleth_map5_1, png_path + "test_choropleth_map_nyc_5-1.png") save_png(choropleth_map5_2, png_path + "test_choropleth_map_nyc_5-2.png") # 6 red_transparency vega_6 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "red_transparency", [2.5, 5], 1.0, 'EPSG:4326') baseline6 = choroplethmap(res, vega_6) choropleth_map6_1 = choroplethmap(res, vega_6) choropleth_map6_2 = choroplethmap(res, vega_6) baseline_png6 = png_path + "choropleth_map_nyc_6.png" save_png(baseline6, baseline_png6) save_png(choropleth_map6_1, png_path + "test_choropleth_map_nyc_6-1.png") save_png(choropleth_map6_2, png_path + "test_choropleth_map_nyc_6-2.png") # 7 blue_transparency vega_7 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "blue_transparency", [2.5, 5], 1.0, 'EPSG:4326') baseline7 = choroplethmap(res, vega_7) choropleth_map7_1 = choroplethmap(res, vega_7) choropleth_map7_2 = choroplethmap(res, vega_7) baseline_png7 = png_path + "choropleth_map_nyc_7.png" save_png(baseline7, baseline_png7) save_png(choropleth_map7_1, png_path + "test_choropleth_map_nyc_7-1.png") save_png(choropleth_map7_2, png_path + "test_choropleth_map_nyc_7-2.png") # 8 blue_green_yellow vega_8 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "blue_green_yellow", [2.5, 5], 1.0, 'EPSG:4326') baseline8 = choroplethmap(res, vega_8) choropleth_map8_1 = choroplethmap(res, vega_8) choropleth_map8_2 = choroplethmap(res, vega_8) baseline_png8 = png_path + "choropleth_map_nyc_8.png" save_png(baseline8, baseline_png8) save_png(choropleth_map8_1, png_path + "test_choropleth_map_nyc_8-1.png") save_png(choropleth_map8_2, png_path + "test_choropleth_map_nyc_8-2.png") # 9 white_blue vega_9 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "white_blue", [2.5, 5], 1.0, 'EPSG:4326') baseline9 = choroplethmap(res, vega_9) choropleth_map9_1 = choroplethmap(res, vega_9) choropleth_map9_2 = choroplethmap(res, vega_9) baseline_png9 = png_path + "choropleth_map_nyc_9.png" save_png(baseline9, baseline_png9) save_png(choropleth_map9_1, png_path + "test_choropleth_map_nyc_9-1.png") save_png(choropleth_map9_2, png_path + "test_choropleth_map_nyc_9-2.png") # 10-12 test ruler # 10 ruler: [1, 500] vega_10 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "blue_to_red", [1, 500], 1.0, 'EPSG:4326') baseline10 = choroplethmap(res, vega_10) choropleth_map10_1 = choroplethmap(res, vega_10) choropleth_map10_2 = choroplethmap(res, vega_10) baseline_png10 = png_path + "choropleth_map_nyc_10.png" save_png(baseline10, baseline_png10) save_png(choropleth_map10_1, png_path + "test_choropleth_map_nyc_10-1.png") save_png(choropleth_map10_2, png_path + "test_choropleth_map_nyc_10-2.png") # 11 ruler: [1, 10000] vega_11 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "blue_to_red", [1, 10000], 1.0, 'EPSG:4326') baseline11 = choroplethmap(res, vega_11) choropleth_map11_1 = choroplethmap(res, vega_11) choropleth_map11_2 = choroplethmap(res, vega_11) baseline_png11 = png_path + "choropleth_map_nyc_11.png" save_png(baseline11, baseline_png11) save_png(choropleth_map11_1, png_path + "test_choropleth_map_nyc_11-1.png") save_png(choropleth_map11_2, png_path + "test_choropleth_map_nyc_11-2.png") # 12 ruler: [0, 2.5] vega_12 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "blue_to_red", [0, 2.5], 1.0, 'EPSG:4326') baseline12 = choroplethmap(res, vega_12) choropleth_map12_1 = choroplethmap(res, vega_12) choropleth_map12_2 = choroplethmap(res, vega_12) baseline_png12 = png_path + "choropleth_map_nyc_12.png" save_png(baseline12, baseline_png12) save_png(choropleth_map12_1, png_path + "test_choropleth_map_nyc_12-1.png") save_png(choropleth_map12_2, png_path + "test_choropleth_map_nyc_12-2.png") # 13-15 test opacity # 13 opacity: 0.0 vega_13 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 0.0, 'EPSG:4326') baseline13 = choroplethmap(res, vega_13) choropleth_map13_1 = choroplethmap(res, vega_13) choropleth_map13_2 = choroplethmap(res, vega_13) baseline_png13 = png_path + "choropleth_map_nyc_13.png" save_png(baseline13, baseline_png13) save_png(choropleth_map13_1, png_path + "test_choropleth_map_nyc_13-1.png") save_png(choropleth_map13_2, png_path + "test_choropleth_map_nyc_13-2.png") # 14 opacity: 1.0 vega_14 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 1.0, 'EPSG:4326') baseline14 = choroplethmap(res, vega_14) choropleth_map14_1 = choroplethmap(res, vega_14) choropleth_map14_2 = choroplethmap(res, vega_14) baseline_png14 = png_path + "choropleth_map_nyc_14.png" save_png(baseline14, baseline_png14) save_png(choropleth_map14_1, png_path + "test_choropleth_map_nyc_14-1.png") save_png(choropleth_map14_2, png_path + "test_choropleth_map_nyc_14-2.png") # 15 opacity: 0.5 vega_15 = vega_choroplethmap(1900, 1410, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 0.5, 'EPSG:4326') baseline15 = choroplethmap(res, vega_15) choropleth_map15_1 = choroplethmap(res, vega_15) choropleth_map15_2 = choroplethmap(res, vega_15) baseline_png15 = png_path + "choropleth_map_nyc_15.png" save_png(baseline15, baseline_png15) save_png(choropleth_map15_1, png_path + "test_choropleth_map_nyc_15-1.png") save_png(choropleth_map15_2, png_path + "test_choropleth_map_nyc_15-2.png") # 16-18 test size # 16 width: 256, height: 256 vega_16 = vega_choroplethmap(256, 256, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 1.0, 'EPSG:4326') baseline16 = choroplethmap(res, vega_16) choropleth_map16_1 = choroplethmap(res, vega_16) choropleth_map16_2 = choroplethmap(res, vega_16) baseline_png16 = png_path + "choropleth_map_nyc_16.png" save_png(baseline16, baseline_png16) save_png(choropleth_map16_1, png_path + "test_choropleth_map_nyc_16-1.png") save_png(choropleth_map16_2, png_path + "test_choropleth_map_nyc_16-2.png") # 17 width: 200, height: 200 vega_17 = vega_choroplethmap(200, 200, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 1.0, 'EPSG:4326') baseline17 = choroplethmap(res, vega_17) choropleth_map17_1 = choroplethmap(res, vega_17) choropleth_map17_2 = choroplethmap(res, vega_17) baseline_png17 = png_path + "choropleth_map_nyc_17.png" save_png(baseline17, baseline_png17) save_png(choropleth_map17_1, png_path + "test_choropleth_map_nyc_17-1.png") save_png(choropleth_map17_2, png_path + "test_choropleth_map_nyc_17-2.png") # 18 width: 500, height: 200 vega_18 = vega_choroplethmap(500, 200, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 1.0, 'EPSG:4326') baseline18 = choroplethmap(res, vega_18) choropleth_map18_1 = choroplethmap(res, vega_18) choropleth_map18_2 = choroplethmap(res, vega_18) baseline_png18 = png_path + "choropleth_map_nyc_18.png" save_png(baseline18, baseline_png18) save_png(choropleth_map18_1, png_path + "test_choropleth_map_nyc_18-1.png") save_png(choropleth_map18_2, png_path + "test_choropleth_map_nyc_18-2.png") # 19 width: 10, height: 10 vega_19 = vega_choroplethmap(10, 10, [-73.994092, 40.753893, -73.977588, 40.759642], "purple_to_yellow", [2.5, 5], 1.0, 'EPSG:4326') baseline19 = choroplethmap(res, vega_19) choropleth_map19_1 = choroplethmap(res, vega_19) choropleth_map19_2 = choroplethmap(res, vega_19) baseline_png19 = png_path + "choropleth_map_nyc_19.png" save_png(baseline19, baseline_png19) save_png(choropleth_map19_1, png_path + "test_choropleth_map_nyc_19-1.png") save_png(choropleth_map19_2, png_path + "test_choropleth_map_nyc_19-2.png") spark.catalog.dropGlobalTempView("nyc_taxi") assert run_diff_png(baseline_png1, png_path + "test_choropleth_map_nyc_1-1.png") assert run_diff_png(baseline_png1, png_path + "test_choropleth_map_nyc_1-2.png") assert run_diff_png(baseline_png2, png_path + "test_choropleth_map_nyc_2-1.png") assert run_diff_png(baseline_png2, png_path + "test_choropleth_map_nyc_2-2.png") assert run_diff_png(baseline_png3, png_path + "test_choropleth_map_nyc_3-1.png") assert run_diff_png(baseline_png3, png_path + "test_choropleth_map_nyc_3-2.png") assert run_diff_png(baseline_png4, png_path + "test_choropleth_map_nyc_4-1.png") assert run_diff_png(baseline_png4, png_path + "test_choropleth_map_nyc_4-2.png") assert run_diff_png(baseline_png5, png_path + "test_choropleth_map_nyc_5-1.png") assert run_diff_png(baseline_png5, png_path + "test_choropleth_map_nyc_5-2.png") assert run_diff_png(baseline_png6, png_path + "test_choropleth_map_nyc_6-1.png") assert run_diff_png(baseline_png6, png_path + "test_choropleth_map_nyc_6-2.png") assert run_diff_png(baseline_png7, png_path + "test_choropleth_map_nyc_7-1.png") assert run_diff_png(baseline_png7, png_path + "test_choropleth_map_nyc_7-2.png") assert run_diff_png(baseline_png8, png_path + "test_choropleth_map_nyc_8-1.png") assert run_diff_png(baseline_png8, png_path + "test_choropleth_map_nyc_8-2.png") assert run_diff_png(baseline_png9, png_path + "test_choropleth_map_nyc_9-1.png") assert run_diff_png(baseline_png9, png_path + "test_choropleth_map_nyc_9-2.png") assert run_diff_png(baseline_png10, png_path + "test_choropleth_map_nyc_10-1.png") assert run_diff_png(baseline_png10, png_path + "test_choropleth_map_nyc_10-2.png") assert run_diff_png(baseline_png11, png_path + "test_choropleth_map_nyc_11-1.png") assert run_diff_png(baseline_png11, png_path + "test_choropleth_map_nyc_11-2.png") assert run_diff_png(baseline_png12, png_path + "test_choropleth_map_nyc_12-1.png") assert run_diff_png(baseline_png12, png_path + "test_choropleth_map_nyc_12-2.png") assert run_diff_png(baseline_png13, png_path + "test_choropleth_map_nyc_13-1.png") assert run_diff_png(baseline_png13, png_path + "test_choropleth_map_nyc_13-2.png") assert run_diff_png(baseline_png14, png_path + "test_choropleth_map_nyc_14-1.png") assert run_diff_png(baseline_png14, png_path + "test_choropleth_map_nyc_14-2.png") assert run_diff_png(baseline_png15, png_path + "test_choropleth_map_nyc_15-1.png") assert run_diff_png(baseline_png15, png_path + "test_choropleth_map_nyc_15-2.png") assert run_diff_png(baseline_png16, png_path + "test_choropleth_map_nyc_16-1.png") assert run_diff_png(baseline_png16, png_path + "test_choropleth_map_nyc_16-2.png") assert run_diff_png(baseline_png17, png_path + "test_choropleth_map_nyc_17-1.png") assert run_diff_png(baseline_png17, png_path + "test_choropleth_map_nyc_17-2.png") assert run_diff_png(baseline_png18, png_path + "test_choropleth_map_nyc_18-1.png") assert run_diff_png(baseline_png18, png_path + "test_choropleth_map_nyc_18-2.png") assert run_diff_png(baseline_png19, png_path + "test_choropleth_map_nyc_19-1.png") assert run_diff_png(baseline_png19, png_path + "test_choropleth_map_nyc_19-2.png")