def test_ubuntu4(self):
import tempfile
import os
import shutil
import datetime
dirpath=tempfile.mkdtemp()
try:
# Test setup
stacktrace_path = os.path.join(dirpath, "Stacktrace.txt")
with open(stacktrace_path, 'w') as stacktrace_file:
stacktrace_file.write(self.example_ubuntu_stacktrace4)
post_path = os.path.join(dirpath, "Post.txt")
with open(post_path, 'w') as post_file:
post_file.write(self.example_ubuntu_post4)
# Test crash loader
crash = Crash.load_from_file(dirpath)
# test that contents are loaded correctly
assert (isinstance(crash, Crash))
stacktrace = crash['stacktrace']
assert stacktrace is crash.stacktrace
assert (isinstance(stacktrace, Stacktrace))
assert (isinstance(stacktrace[0], Stackframe))
assert stacktrace[0]['function'] is None
finally:
shutil.rmtree(dirpath)
def test_ubuntu2(self):
import tempfile
import os
import shutil
import datetime
dirpath=tempfile.mkdtemp()
try:
# Test setup
stacktrace_path = os.path.join(dirpath, "Stacktrace.txt (retraced)")
with open(stacktrace_path, 'w') as stacktrace_file:
stacktrace_file.write(self.example_ubuntu_stacktrace2)
post_path = os.path.join(dirpath, "Post.txt")
with open(post_path, 'w') as post_file:
post_file.write(self.example_ubuntu_post2)
# Test crash loader
crash = Crash.load_from_file(dirpath)
# test that contents are loaded correctly
assert (isinstance(crash, Crash))
assert (crash['cpu'] == 'amd64')
assert (crash['date'] == datetime.datetime(2007, 6, 20, 10, 27, 6))
stacktrace = crash['stacktrace']
assert stacktrace is crash.stacktrace
assert (isinstance(stacktrace, Stacktrace))
assert (isinstance(stacktrace[0], Stackframe))
assert (stacktrace[0]['depth'] == 0)
assert (stacktrace[0]['function'] == 'cairo_transform')
assert (not 'address' in stacktrace[0])
assert (stacktrace[1]['depth'] == 1)
assert (stacktrace[1]['address'] == '0x00002b344498a150')
finally:
shutil.rmtree(dirpath)
def test_ubuntu3(self):
import tempfile
import os
import shutil
import datetime
dirpath=tempfile.mkdtemp()
try:
# Test setup
stacktrace_path = os.path.join(dirpath, "Stacktrace.txt (retraced)")
with open(stacktrace_path, 'w') as stacktrace_file:
stacktrace_file.write(self.example_ubuntu_stacktrace3)
post_path = os.path.join(dirpath, "Post.txt")
with open(post_path, 'w') as post_file:
post_file.write(self.example_ubuntu_post3)
# Test crash loader
crash = Crash.load_from_file(dirpath)
# test that contents are loaded correctly
assert (isinstance(crash, Crash))
stacktrace = crash['stacktrace']
assert stacktrace is crash.stacktrace
assert (isinstance(stacktrace, Stacktrace))
assert (isinstance(stacktrace[0], Stackframe))
assert (stacktrace[0]['depth'] == 0)
assert (stacktrace[1]['depth'] == 1)
assert (stacktrace[6]['function'] == '<signal handler called>')
assert (stacktrace[4]['extra'][0] == 'No locals.')
assert (stacktrace[0]['file'] == '../../src/QuExt.c')
assert (stacktrace[0]['fileline'] == '46')
assert (len(stacktrace[0]['extra']) == 2)
finally:
shutil.rmtree(dirpath)
def test_ubuntu(self):
import tempfile
import os
import shutil
import datetime
dirpath=tempfile.mkdtemp()
try:
# Test setup
stacktrace_path = os.path.join(dirpath, "Stacktrace.txt")
with open(stacktrace_path, 'w') as stacktrace_file:
stacktrace_file.write(self.example_ubuntu_stacktrace)
post_path = os.path.join(dirpath, "Post.txt")
with open(post_path, 'w') as post_file:
post_file.write(self.example_ubuntu_post)
# Test crash loader
crash = Crash.load_from_file(dirpath)
# test that contents are loaded correctly
assert (isinstance(crash, Crash))
assert (crash['cpu'] == 'i386')
assert (crash['date'] == datetime.datetime(2008, 4, 11, 22, 12, 11))
stacktrace = crash['stacktrace']
assert stacktrace is crash.stacktrace
assert (isinstance(stacktrace, Stacktrace))
assert (isinstance(stacktrace[0], Stackframe))
assert (stacktrace[0]['depth'] == 0)
assert (stacktrace[0]['function'] == 'free')
assert (stacktrace[1]['depth'] == 1)
assert (stacktrace[1]['address'] == '0xb78e78b1')
finally:
shutil.rmtree(dirpath)
def rg():
pygame.init()
screen = pygame.display.set_mode((1200, 800))
pygame.display.set_caption('blue sky')
bg_color = (0, 0, 230)
crash = Crash(screen)
while True:
for event in pygame.event.get():
if event.type == pygame.QUIT:
sys.exit()
screen.fill(bg_color)
crash.blitme()
pygame.display.flip()
def test_no_function(self):
should_contain = 'launchpad:122451#0'
crash = Crash.fromjson(self.exampleJson1)
topn = TopN(3)
topna = TopNAddress(3)
topnf = TopNFile(3)
signature = topn.get_signature(crash)
assert 'launchpad:122451#0' in signature
print repr(signature)
assert signature == \
u'launchpad:122451#0 ≻ launchpad:122451#1 ≻ launchpad:122451#2'
assert topna.get_signature(crash) == \
u'0x0805f92c ≻ 0x085e5618 ≻ 0x085e5618'
crash2 = Crash.fromjson(self.exampleJson2)
assert not topn.compare(crash, crash2)
assert topn.compare(crash, crash)
assert not topna.compare(crash, crash2)
assert topna.compare(crash, crash)
assert not topnf.compare(crash, crash2)
assert topnf.compare(crash, crash)
def test_no_function(self):
should_contain = 'launchpad:122451#0'
crash = Crash.fromjson(self.exampleJson1)
topn = TopN(3)
topna = TopNAddress(3)
topnf = TopNFile(3)
signature = topn.get_signature(crash)
assert 'launchpad:122451#0' in signature
print repr(signature)
assert signature == \
u'launchpad:122451#0 ≻ launchpad:122451#1 ≻ launchpad:122451#2'
assert topna.get_signature(crash) == \
u'0x0805f92c ≻ 0x085e5618 ≻ 0x085e5618'
crash2 = Crash.fromjson(self.exampleJson2)
assert not topn.compare(crash, crash2)
assert topn.compare(crash, crash)
assert not topna.compare(crash, crash2)
assert topna.compare(crash, crash)
assert not topnf.compare(crash, crash2)
assert topnf.compare(crash, crash)
def getrawbyid(cls, database_id, index=None):
if index is None:
raise ValueError('No ElasticSearch index specified!')
if cls.es is None:
raise RuntimeError(
'Forgot to monkey-patch ES connection to ESCrash!')
if index in cls.crashes:
if database_id in cls.crashes[index]:
return cls.crashes[database_id]
try:
response = cls.es.get(index=index, id=database_id)
except elasticsearch.exceptions.NotFoundError:
return None
return Crash(response['_source'])
def test_es_add(self):
import gc
es = ESCrash.es
es.indices.delete(index='crashes', ignore=[400, 404])
mycrash = ESCrash(self.exampleCrash1)
mycrash_dupe = ESCrash(self.exampleCrash1)
assert mycrash is mycrash_dupe
mycrash_another = ESCrash('exampleCrash1')
assert mycrash is mycrash_another
del mycrash
del mycrash_another
del mycrash_dupe
gc.collect()
es.indices.flush(index='crashes')
time.sleep(1)
fetched_from_es = ESCrash('exampleCrash1')
fetched_from_es_undone = Crash(fetched_from_es)
assert fetched_from_es_undone == self.exampleCrash1
fetched_from_es['cpu'] = 'amd64'
def __call__(cls, crash=None, index=None, unsafe=False):
# This is the case that the constructor was called with a whole
# crash datastructure
if index is None:
raise ValueError('No ElasticSearch index specified!')
if index not in cls._cached:
cls._cached[index] = WeakValueDictionary()
if isinstance(crash, Crash):
if 'database_id' in crash:
# The case that we already have it in memory
if crash['database_id'] in cls._cached[index]:
already = cls._cached[index][crash['database_id']]
assert (Crash(already) == crash)
return already
# We don't have it in memory so see if its already in ES
if not unsafe:
existing = cls.getrawbyid(crash['database_id'],
index=index)
else:
existing = None
if not existing is None:
if existing != crash:
# We already know of it! Raise an identical report
# error.
# TODO: not resilient to multiple running instances of
# PartyCrasher :c
raise IdenticalReportError(existing)
# It is already in elastic search
# make sure its the same data
newish = super(ESCrashMeta, cls).__call__(crash=existing,
index=index)
# cache it as a weak reference
cls._cached[index][crash['database_id']] = newish
return newish
# It's not in ES, so add it
else:
# Ensure this is UTC ISO format
now = datetime.datetime.utcnow()
crash.setdefault('date', now.isoformat())
if 'stacktrace' in crash and crash[
'stacktrace'] is not None:
for frame in crash['stacktrace']:
if 'logdf' in frame:
raise ValueError(
"logdf should not be stored in ElasticSearch"
)
crash_es_safe = crash.copy()
try:
response = cls.es.create(
index=index,
doc_type='crash',
body=json.dumps(crash, cls=ESCrashEncoder),
id=crash['database_id'],
refresh=True)
assert response['created']
except elasticsearch.exceptions.ConflictError as e:
if (('DocumentAlreadyExistsException' in e.error) or
('document_already_exists_exception' in e.error)):
print(
"Got DocumentAlreadyExistsException on create!",
file=sys.stderr)
already = None
while already is None:
print(
"Waiting for ElasticSearch to catch up...",
file=sys.stderr)
time.sleep(1) # Let ES think about its life...
already = cls.getrawbyid(crash['database_id'],
index=index)
if not already is None:
# It got added...
# I think what is happening here is that the
# python client lib is retrying after the create
# times out, but ES did recieve the create and
# created the document but didn't return in time
pass
else:
raise
else:
raise
new = super(ESCrashMeta, cls).__call__(crash=crash,
index=index)
# Cache it as a weak reference
cls._cached[index][crash['database_id']] = new
return new
else:
raise Exception("Crash with no database_id!")
# The case where the constructor is called with a database id only
elif isinstance(crash, str) or isinstance(crash, unicode):
if crash in cls._cached[index]:
return cls._cached[index][crash]
existing = cls.getrawbyid(crash, index=index)
if existing is not None:
# Found it in ElasticSearch!
newish = super(ESCrashMeta, cls).__call__(crash=existing,
index=index)
cls._cached[index][crash] = newish
return newish
else:
raise ReportNotFoundError(crash)
else:
raise ValueError()
class TestCrash(unittest.TestCase):
exampleCrash1 = Crash({
'database_id':
'exampleCrash1',
'project':
'Ubuntu',
'CrashCounter':
'1',
'ExecutablePath':
'/bin/nbd-server',
'NonfreeKernelModules':
'fglrx',
'Package':
'nbd-server 1:2.9.3-3ubuntu1',
'PackageArchitecture':
'i386',
'ProcCmdline':
'/bin/nbd-server',
'ProcCwd':
'/',
'ProcEnviron':
'PATH=/sbin:/bin:/usr/sbin:/usr/bin',
'Signal':
'11',
'SourcePackage':
'nbd',
'StacktraceTop':
'\xa0?? ()',
'Title':
'nbd-server crashed with SIGSEGV',
'Uname':
'Linux mlcochff 2.6.22-7-generic #1 SMP Mon Jun 25 17:33:14 GMT 2007 i686 GNU/Linux',
'cpu':
'i386',
'date':
datetime.datetime(2007, 6, 27, 12, 4, 43),
'os':
'Ubuntu 7.10',
'stacktrace':
Stacktrace([
Stackframe({
'address':
u'0x0804cbd3',
'args':
u'argc=',
'depth':
0,
'extra': [
u'\tserve = (SERVER *) 0x0',
u'\tservers = (GArray *) 0x8051418',
u'\terr = (GError *) 0x0'
],
'file':
u'nbd-server.c:1546',
'function':
u'main'
}),
Stackframe({
'address': u'0xb7cfcebc',
'args': u'',
'depth': 1,
'function': u'??'
}),
Stackframe({
'address': u'0x00000001',
'args': u'',
'depth': 2,
'function': u'??'
}),
Stackframe({
'address': u'0xbfeff544',
'args': u'',
'depth': 3,
'function': u'??'
}),
Stackframe({
'address': u'0xbfeff54c',
'args': u'',
'depth': 4,
'function': u'??'
}),
Stackframe({
'address': u'0xb7f1b898',
'args': u'',
'depth': 5,
'function': u'??'
}),
Stackframe({
'address': u'0x00000000',
'args': u'',
'depth': 6,
'function': u'??'
})
]),
'type':
'Crash'
})
def test_es_reachable_working(self):
es = Elasticsearch(hosts=['localhost'])
es.indices.create(index='test-index', ignore=400)
es.indices.delete(index='test-index', ignore=[400, 404])
def test_es_add(self):
import gc
es = ESCrash.es
es.indices.delete(index='crashes', ignore=[400, 404])
mycrash = ESCrash(self.exampleCrash1)
mycrash_dupe = ESCrash(self.exampleCrash1)
assert mycrash is mycrash_dupe
mycrash_another = ESCrash('exampleCrash1')
assert mycrash is mycrash_another
del mycrash
del mycrash_another
del mycrash_dupe
gc.collect()
es.indices.flush(index='crashes')
time.sleep(1)
fetched_from_es = ESCrash('exampleCrash1')
fetched_from_es_undone = Crash(fetched_from_es)
assert fetched_from_es_undone == self.exampleCrash1
fetched_from_es['cpu'] = 'amd64'
def main():
"""
*********************************************
Extract and clean data from nyc open data
*********************************************
"""
APP_TOKEN = app_token()
base_url = "https://data.cityofnewyork.us/resource/h9gi-nx95.json?$$app_token={}".format(
APP_TOKEN)
url = base_url + "{}"
cnt_url = base_url + "{}{}" # select , where
where_inj = "&$where=number_of_cyclist_injured>0.0&$limit=50000"
where_kill = "&$where=number_of_cyclist_killed>0.0"
inj_df = pd.read_json(url.format(where_inj))
killed_df = pd.read_json(url.format(where_kill))
def dt(date, time):
date = pd.to_datetime(date).dt.date
time = pd.to_datetime(time).dt.time
return date, time
# so frustrating. NYC open data changed columns from "accident" to "crash"
killed_df.crash_date, killed_df.crash_time = dt(killed_df.crash_date,
killed_df.crash_time)
inj_df.crash_date, inj_df.crash_time = dt(inj_df.crash_date,
inj_df.crash_time)
killed_df = killed_df.rename(columns={
'crash_date': 'accident_date',
'crash_time': 'accident_time'
})
inj_df = inj_df.rename(columns={
'crash_date': 'accident_date',
'crash_time': 'accident_time'
})
df = (pd.concat([
inj_df, killed_df
]).drop(columns='location').drop_duplicates().reset_index(drop=True))
df.vehicle_type_code1 = df.vehicle_type_code1.apply(
lambda x: str(x).upper())
df.vehicle_type_code2 = df.vehicle_type_code2.apply(
lambda x: str(x).upper())
df['Accident Year'] = df.accident_date.apply(lambda x: x.year)
df['Accident Month'] = df.accident_date.apply(lambda x: x.month)
df['Accident Hour'] = df.accident_time.apply(lambda x: x.hour)
def create_df(group):
return (df.groupby(group).collision_id.count().reset_index().rename(
columns={'collision_id': 'Number of Accidents'}))
"""
*********************************************
Create figures for month and hour data
*********************************************
"""
crash_mo_yr = create_df(['Accident Year', 'Accident Month'])
crash_hr = create_df('Accident Hour')
crash_mo_hr = create_df(['Accident Month', 'Accident Hour'])
killed_df['accident_year'] = killed_df.accident_date.apply(
lambda x: x.year)
killed_df['accident_month'] = killed_df.accident_date.apply(
lambda x: x.month)
killed_df['accident_hr'] = killed_df.accident_time.apply(lambda x: x.hour)
mo_fig = px.area(crash_mo_yr,
x="Accident Month",
y="Number of Accidents",
animation_frame="Accident Year",
range_y=[0, 800],
range_x=[1, 12])
mo_fig.layout.updatemenus[0].buttons[0].args[1]["frame"]["duration"] = 1000
mo_fig.layout.title = "Bicycle Accidents by Month for Each Year"
pio.write_html(mo_fig, file="app/static/mo_fig.html", auto_play=False)
hr_fig = px.area(crash_mo_hr,
x="Accident Hour",
y="Number of Accidents",
animation_frame="Accident Month",
range_y=[0, 400],
range_x=[0, 23])
hr_fig.layout.updatemenus[0].buttons[0].args[1]["frame"]["duration"] = 1000
hr_fig.layout.title = "Bicycle Accidents by Hour For Each Month"
pio.write_html(hr_fig, file="app/static/hr_fig.html", auto_play=False)
"""
*********************************************
Extract data from citibike files - all trips
*********************************************
"""
fdir = './agg_trip'
agg_files = os.listdir(fdir)
agg_df = pd.read_csv(fdir + '/' + agg_files[0]).iloc[:, [0, 1]]
for i in range(1, len(agg_files)):
agg_df = agg_df.append(
pd.read_csv(fdir + '/' + agg_files[i]).iloc[:, [0, 1]])
agg_df.Date = pd.to_datetime(agg_df.Date).dt.date
agg_df = agg_df.rename(columns={
'Trips over the past 24-hours (midnight to 11:59pm)':
'Number of Trips'
})
agg_df = agg_df.sort_values('Date')
fig = px.line(agg_df,
x='Date',
y='Number of Trips',
title="Number of CitiBike Trips by Day",
hover_name='Date')
pio.write_html(fig, file="app/static/fig.html", auto_play=False)
"""
*********************************************
Using 9/25/2019 to map common citibike routes
*********************************************
"""
high_day = pd.read_csv('./app/static/high_day.csv')
coord092519 = high_day[[
'start station name', 'start station id', 'start station latitude',
'start station longitude', 'end station name', 'end station id',
'end station latitude', 'end station longitude'
]].copy()
coord092519['id'] = (coord092519['start station name'] +
coord092519['end station name'])
coord092519 = coord092519.groupby([
'start station name', 'start station id', 'start station latitude',
'start station longitude', 'end station name', 'end station id',
'end station latitude', 'end station longitude'
]).id.count().reset_index()
coord092519['filt'] = coord092519.apply(
lambda x: 'y'
if x['start station name'] == x['end station name'] else '',
axis=1)
coord092519 = coord092519[coord092519.filt != 'y'].reset_index(drop=True)
cohort = coord092519[coord092519.id >= 4]
cohort = cohort.rename(columns={'id': 'count'})
cohort['id'] = cohort['start station id'].apply(
str) + '-' + cohort['end station id'].apply(str)
routes = pd.read_csv('./app/static/backup_route_file.csv')
routes = routes[
routes.geojson != '{"message":"Too Many Requests"}'].reset_index(
drop=True)
cohort_df = pd.merge(cohort,
routes[['id', 'geojson']],
on='id',
how='inner')
cohort_df = cohort_df[['geojson']].drop_duplicates()
geojson = list(cohort_df.geojson)
gjson = []
for i in range(len(geojson)):
gjson.append(
json.loads(geojson[i])['routes'][0]['geometry']['coordinates'])
for i in gjson:
for j in i:
j.reverse()
"""
*********************************************
mapping the accidents
*********************************************
"""
loc_df = df[[
'borough', 'latitude', 'longitude', 'on_street_name',
'off_street_name', 'accident_date'
]].copy()
loc_df = loc_df[(pd.isna(loc_df.latitude) == False)
& (loc_df.latitude != 0) & (loc_df.longitude != 0)]
loc_df.on_street_name = loc_df.on_street_name.str.strip()
loc_df.off_street_name = loc_df.off_street_name.str.strip()
loc_df.accident_date = loc_df.accident_date.apply(str)
loc_df['lat_lon_list'] = loc_df.apply(lambda x: [x.longitude, x.latitude],
axis=1)
loc_df = loc_df.sort_values('accident_date').reset_index(drop=True)
intersect_df = loc_df.copy()
intersect_df[
'intersection'] = intersect_df.on_street_name + ';' + intersect_df.off_street_name
intersect_df.intersection = intersect_df.intersection.apply(
lambda x: ' & '.join(sorted(x.split(';')))
if pd.isna(x) == False else x)
dang_int = (intersect_df.groupby(
['borough',
'intersection'])['accident_date'].count().reset_index().sort_values(
'accident_date', ascending=False).rename(
columns={'accident_date': 'Number of Bike Accidents'}))
# For the table
dang_int_viz = (dang_int[dang_int['Number of Bike Accidents'] >= 10].copy(
).reset_index(drop=True).rename(columns={
'borough': 'Borough',
'intersection': 'Intersection'
}))
for i in dang_int_viz.index:
Crash(
dang_int_viz.iloc[i].Borough,
dang_int_viz.iloc[i].Intersection).create_map().save(
'app/static/crash_maps/' + dang_int_viz.iloc[i].Borough +
dang_int_viz.iloc[i].Intersection.replace(' ', '_') + '.html')
dang_int_viz.Intersection = dang_int_viz.apply(
lambda x: '<a href={} target="iframe_map">{}</a>'.format(
'../static/crash_maps/' + x.Borough + x.Intersection.replace(
' ', '_') + '.html', x.Intersection),
axis=1)
html = """<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th>Borough</th>
<th>Intersection</th>
<th>Number of Bike Accidents</th>
</tr>
</thead>
<tbody>
"""
for i in dang_int_viz.index:
html = (html + '<tr><td>' + dang_int_viz.iloc[i].Borough +
'</td><td>' + dang_int_viz.iloc[i].Intersection + '</td><td>' +
str(dang_int_viz.iloc[i]['Number of Bike Accidents']) +
'</td></tr>')
html = html + "</tbody></table>"
html = BeautifulSoup(html, "lxml")
html.body.insert(
0,
BeautifulSoup('<link rel="stylesheet" href="/static/style.css">',
"lxml"))
with open('app/static/crash_table.html', 'w') as f:
f.write(str(html))
lat_lon = intersect_df[['intersection', 'lat_lon_list']].copy()
lat_lon.lat_lon_list = lat_lon.lat_lon_list.apply(
lambda x: str(round(x[0], 5)) + ';' + str(round(x[1], 5)))
lat_lon = lat_lon.drop_duplicates().reset_index(drop=True)
lat_lon.lat_lon_list = lat_lon.lat_lon_list.apply(
lambda x: [float(i) for i in x.split(';')])
for i in lat_lon.index:
lat_lon.lat_lon_list[i].reverse()
dang_int = pd.merge(dang_int, lat_lon, on='intersection', how='left')
dang_int.to_csv('app/static/dang_int.csv', index=False)
dang_int_10 = (
dang_int[(dang_int['Number of Bike Accidents'] >= 10)
& (dang_int['Number of Bike Accidents'] < 15)].reset_index(
drop=True))
dang_int_15 = (
dang_int[(dang_int['Number of Bike Accidents'] >= 15)
& (dang_int['Number of Bike Accidents'] < 20)].reset_index(
drop=True))
dang_int_20 = (
dang_int[dang_int['Number of Bike Accidents'] >= 20].reset_index(
drop=True))
features = [{
'type': 'Feature',
'geometry': {
'type': 'MultiPoint',
'coordinates': list(loc_df.lat_lon_list),
},
'properties': {
'times': list(loc_df.accident_date),
'icon': 'circle',
'iconstyle': {
'fillColor': 'red',
'fillOpacity': 0.5,
'stroke': 'false',
'radius': 5
},
'style': {
'weight': 0.5
}
}
}]
"""
*********************************************
Getting the bike lanes and formatting the data
*********************************************
"""
bike_lanes = pd.read_json('./app/static/Bicycle Routes.geojson')
bl_prot_json = []
bl_stand_json = []
for i in bike_lanes.index:
if bike_lanes.iloc[i].features['properties']['facilitycl'] == 'I':
for j in range(
len(bike_lanes.iloc[i].features['geometry']
['coordinates'])):
bl_prot_json.append(
bike_lanes.iloc[i].features['geometry']['coordinates'][j])
else:
for j in range(
len(bike_lanes.iloc[i].features['geometry']
['coordinates'])):
bl_stand_json.append(
bike_lanes.iloc[i].features['geometry']['coordinates'][j])
for i in bl_prot_json:
for j in i:
j.reverse()
for i in bl_stand_json:
for j in i:
j.reverse()
"""
*********************************************
Creating the map and interactive features
*********************************************
"""
nyc_map = folium.Map(location=[40.735, -73.95],
zoom_start=11.5,
tiles=None)
folium.TileLayer('cartodbdark_matter', control=False).add_to(nyc_map)
# Add bike lanes
folium.PolyLine(bl_prot_json, weight=1, opacity=0.9, color='lime').add_to(
folium.FeatureGroup(name='Protected Bike Lanes').add_to(nyc_map))
folium.PolyLine(bl_stand_json, weight=1, opacity=0.9,
color='yellow').add_to(
folium.FeatureGroup(
name='Non-Protected Bike Lanes').add_to(nyc_map))
# Add citibike routes
folium.PolyLine(gjson, weight=1, opacity=0.2).add_to(
folium.FeatureGroup(name='Commonly Used Citibike Routes',
overlay=False).add_to(nyc_map))
# Add Dangerous intersections data
over10 = folium.FeatureGroup(name='Intersections w/10-14 Accidents',
overlay=False)
for i in dang_int_10.index:
over10.add_child(
folium.Marker(
dang_int_10.lat_lon_list[i],
tooltip=(dang_int_10.intersection[i] + ':\t' +
str(dang_int_10['Number of Bike Accidents'][i]) +
' Accidents'),
icon=folium.Icon(color='red',
prefix='fa',
icon='fas fa-bicycle')))
over15 = folium.FeatureGroup(name='Intersections w/15-19 Accidents',
overlay=False)
for i in dang_int_15.index:
over15.add_child(
folium.Marker(
dang_int_15.lat_lon_list[i],
tooltip=(dang_int_15.intersection[i] + ':\t' +
str(dang_int_15['Number of Bike Accidents'][i]) +
' Accidents'),
icon=folium.Icon(color='red',
prefix='fa',
icon='fas fa-bicycle')))
over20 = folium.FeatureGroup(name='Intersections w/20 or More Accidents',
overlay=False)
for i in dang_int_20.index:
over20.add_child(
folium.Marker(
dang_int_20.lat_lon_list[i],
tooltip=(dang_int_20.intersection[i] + ':\t' +
str(dang_int_20['Number of Bike Accidents'][i]) +
' Accidents'),
icon=folium.Icon(color='red',
prefix='fa',
icon='fas fa-bicycle')))
nyc_map.add_child(over10)
nyc_map.add_child(over15)
nyc_map.add_child(over20)
plugins.TimestampedGeoJson(
{
'type': 'FeatureCollection',
'features': features
},
period='P1M',
add_last_point=True,
auto_play=True,
loop=False,
max_speed=2,
loop_button=True,
date_options='YYYY-MM-DD',
time_slider_drag_update=True,
duration='P1M').add_to(nyc_map)
folium.LayerControl().add_to(nyc_map)
nyc_map.save('app/static/map_nyc.html')
"""
*********************************************
Bike crash causes
*********************************************
"""
# Decided not to use the below for now. Could use it in the future...
bike_list = ['BIKE', 'BICYCLE', 'E-BIK', 'BICYCLE', 'BYCIC']
cause_df = df[((pd.isna(df.contributing_factor_vehicle_3) == True) &
((df.vehicle_type_code1.isin(bike_list) == True) |
(df.vehicle_type_code2.isin(bike_list) == True)))]
cause_df = cause_df[(cause_df.vehicle_type_code1.isin(bike_list) == False)
|
(cause_df.vehicle_type_code2.isin(bike_list) == False)]
def bike_cause(x):
if x.vehicle_type_code1 in bike_list:
return x.contributing_factor_vehicle_1
else:
return x.contributing_factor_vehicle_2
def veh_cause(x):
if x.vehicle_type_code1 not in bike_list:
return x.contributing_factor_vehicle_1
else:
return x.contributing_factor_vehicle_2
cause_df['bike_cause'] = cause_df.apply(bike_cause, axis=1)
cause_df['veh_cause'] = cause_df.apply(veh_cause, axis=1)
# remove Unspecified from dataset. Not useful
bike_cause_df = (cause_df.groupby(
'bike_cause').collision_id.count().reset_index().sort_values(
'collision_id', ascending=False).head(15).reset_index(drop=True))
bike_cause_df = bike_cause_df[bike_cause_df.bike_cause != 'Unspecified']
veh_cause_df = (cause_df.groupby(
'veh_cause').collision_id.count().reset_index().sort_values(
'collision_id', ascending=False).head(15).reset_index(drop=True))
veh_cause_df = veh_cause_df[veh_cause_df.veh_cause != 'Unspecified']
def make_mlt_query_explain(self,
crash,
index=None,
use_existing=None,
max_query_terms=None,
terminate_after=None,
dont_explain=False):
"""
Builds the more_like_this query.
"""
if index is None:
index = self.index
if isinstance(crash, basestring):
crash = Crash(ESCrash(crash, index=index))
del crash['buckets']
if use_existing is None:
use_existing = False # this should be true but ES seems to be broken?
else:
if use_existing is None:
use_existing = False
body = self.make_more_like_this_query(crash, max_query_terms,
terminate_after)
body["explain"] = (not dont_explain)
if use_existing:
# Prevent crash from being its own highest match when its already in ES
del body["query"]["more_like_this"]["like"][0]["doc"]
body["query"]["more_like_this"]["like"][0]["_id"] = crash[
"database_id"]
skip_fields = Set([
'database_id',
'buckets',
'force_bucket',
'depth',
'date',
])
def all_but_skip_fields(c, prefix=""):
fields = Set()
if isinstance(c, dict):
for k, v in c.iteritems():
#print(prefix + k, file=sys.stderr)
if k not in skip_fields:
fields.add(prefix + k)
subfields = all_but_skip_fields(v, prefix + k + ".")
#print(len(fields))
fields.update(subfields)
elif isinstance(c, list):
for i in c:
subfields = all_but_skip_fields(i, prefix)
fields.update(subfields)
elif isinstance(c, basestring) or c is None:
pass
elif isinstance(c, datetime):
pass
else:
raise NotImplementedError("all_but_fields can't handle " +
c.__class__.__name__)
return fields
fields = list(all_but_skip_fields(crash))
# including the extra field seems to improve recall at the expense of precision
# overall F-score seems to go down so I'm not sure this is worthwhile
#if 'stacktrace.function' in fields:
# fields.append('stacktrace.function.whole')
for field in fields:
assert "buckets" not in field
body["query"]["more_like_this"]["fields"] = fields
#self.ensure_field_mappings(fields)
#print(json.dumps(fields, indent=2), file=sys.stderr)
return body