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")
