def create_contours(container, document):
"""Create a KML file containing MMI contour lines.
Args:
container (ShakeMapOutputContainer): Results of model.conf.
datadir (str): Path to data directory where output KMZ will be written.
document (Element): LXML KML Document element.
"""
# TODO - label contours? gx:labelVisibility doesn't seem to be working...
folder = document.newfolder(name='Contours', visibility=0)
mmi_line_styles = create_line_styles()
pgm_line_style = skml.Style(linestyle=skml.LineStyle(width=3))
ic = skml.IconStyle(scale=0)
component = list(container.getComponents())[0]
imts = container.getIMTs(component)
for imt in imts:
line_strings = contour(container.getIMTGrids(imt, component), imt,
DEFAULT_FILTER_SIZE, None)
# make a folder for the contours
imt_folder = folder.newfolder(name='%s Contours' % imt,
visibility=0)
for line_string in line_strings:
if imt == 'MMI':
val = '%.1f' % line_string['properties']['value']
else:
val = '%g' % line_string['properties']['value']
line_list = []
for segment in line_string['geometry']['coordinates']:
ctext = []
for vertex in segment:
ctext.append((vertex[0], vertex[1]))
ls = skml.LineString(coords=ctext)
line_list.append(ls)
lc = len(ctext)
if lc < 10:
dopts = []
elif (ctext[0][0] == ctext[-1][0] and
ctext[0][1] == ctext[-1][1]):
if lc < 30:
dopts = [0, int(lc/2)]
elif lc < 60:
dopts = [0, int(lc/3), int(2*lc/3)]
else:
dopts = [0, int(lc/4), int(lc/2), int(3*lc/4)]
else:
dopts = [int(lc/2)]
for i in dopts:
p = imt_folder.newpoint(name=val, coords=[ctext[i]],
visibility=0)
p.style.iconstyle = ic
mg = imt_folder.newmultigeometry(geometries=line_list,
visibility=0,
name="%s %s" % (imt, val))
if imt == 'MMI':
mg.style = mmi_line_styles[val]
else:
mg.style = pgm_line_style
def ConverttoKml(Input,Evt_df):
kml = simplekml.Kml()
for ind in Evt_df.index:
pnt = kml.newpoint(name="", coords=[(Evt_df['Longitude'][ind], Evt_df['Latitude'][ind])])
pnt.iconstyle = simplekml.IconStyle(color=simplekml.Color.rgb(0, 255, 0), scale=0.4, heading=Evt_df['Heading'][ind] - 180,
icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None,
href='http://maps.google.com/mapfiles/kml/shapes/arrow.png'),
hotspot=None)
kml.save(OutputLogDirectory + EV_type + '_' + Input + '.kml')
return
def create_epicenter(container, document):
"""Place a star marker at earthquake epicenter.
Args:
container (ShakeMapOutputContainer): Results of model.conf.
document (Element): LXML KML Document element.
"""
icon = skml.Icon(href=EPICENTER_URL)
iconstyle = skml.IconStyle(icon=icon)
style = skml.Style(iconstyle=iconstyle)
info = container.getMetadata()
lon = info['input']['event_information']['longitude']
lat = info['input']['event_information']['latitude']
point = document.newpoint(name='Earthquake Epicenter',
coords=[(lon, lat)],
visibility=0)
point.style = style
def add_icon_style(document, icon_text, icon_scale, label_scale, color):
"""Create Style tag around Icon in KML.
Args:
document (Element): LXML KML Document element.
icon_text (str): The name of the icon file.
icon_scale (float): The icon scale.
label_scale (float): The label scale.
"""
icon = skml.Icon(href=icon_text)
icon_style = skml.IconStyle(scale="%.1f" % icon_scale,
color=color,
icon=icon)
label_style = skml.LabelStyle(scale='%.1f' % label_scale)
# list_style = skml.ListStyle(listitemtype='checkHideChildren')
balloon_style = skml.BalloonStyle(text='$[description]')
# style = skml.Style(iconstyle=icon_style, labelstyle=label_style,
# liststyle=list_style, balloonstyle=balloon_style)
style = skml.Style(iconstyle=icon_style, labelstyle=label_style,
balloonstyle=balloon_style)
return style
def create_polygons(container, document):
component = container.getComponents('MMI')
if len(component) == 0:
return
component = component[0]
gdict = container.getIMTGrids("MMI", component)
fgrid = median_filter(gdict['mean'], size=10)
cont_min = np.floor(np.min(fgrid)) - 0.5
if cont_min < 0:
cont_min = 0.5
cont_max = np.ceil(np.max(fgrid)) + 0.5
if cont_max > 10.5:
cont_max = 10.5
contour_levels = np.arange(cont_min, cont_max, 1, dtype=np.double)
gjson = pcontour(fgrid,
gdict['mean_metadata']['dx'],
gdict['mean_metadata']['dy'],
gdict['mean_metadata']['xmin'],
gdict['mean_metadata']['ymax'],
contour_levels, 4, 0)
folder = document.newfolder(name="MMI Polygons")
for feature in gjson['features']:
cv = feature['properties']['value']
f = folder.newfolder(name="MMI %g Polygons" % cv)
color = color_hash["%g" % cv]
name = "MMI %g Polygon" % cv
s = skml.PolyStyle(fill=1, outline=0, color=color,
colormode='normal')
for plist in feature['geometry']['coordinates']:
ib = []
for i, coords in enumerate(plist):
if i == 0:
ob = coords
else:
ib.append(coords)
p = f.newpolygon(outerboundaryis=ob, innerboundaryis=ib,
name=name, visibility=0)
p.style.polystyle = s
# Make the polygon labels
cont_min = np.floor(np.min(fgrid))
cont_max = np.ceil(np.max(fgrid))
contour_levels = np.arange(cont_min, cont_max, 1, dtype=np.double)
gjson = pcontour(fgrid,
gdict['mean_metadata']['dx'],
gdict['mean_metadata']['dy'],
gdict['mean_metadata']['xmin'],
gdict['mean_metadata']['ymax'],
contour_levels, 2, 0)
f = folder.newfolder(name="MMI Labels")
ic = skml.IconStyle(scale=0)
for feature in gjson['features']:
cv = "%g" % feature['properties']['value']
if cv.endswith(".5"):
continue
for coords in feature['geometry']['coordinates']:
lc = len(coords)
if lc < 150:
continue
if coords[0][0] == coords[-1][0] and coords[0][1] == coords[-1][1]:
if lc < 500:
dopts = [0, int(lc/2)]
elif lc < 1000:
dopts = [0, int(lc/3), int(2*lc/3)]
else:
dopts = [0, int(lc/4), int(lc/2), int(3*lc/4)]
else:
dopts = [int(lc/2)]
for i in dopts:
p = f.newpoint(name=arabic2roman[cv], coords=[coords[i]],
visibility=0)
p.style.iconstyle = ic
def process_tim_rf(input_rf_log, filename):
temp1year = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMTime', 'year'])
temp1month = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMTime', 'month'])
temp1day = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMTime', 'day'])
temp1hour = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMTime', 'hour'])
temp1minute = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMTime', 'minute'])
temp1second = floor(get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMTime', 'second']) / 1000)
temp1microsec = (get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMTime', 'second']) % 1000) * 1000
temp1fulltime = datetime.datetime(temp1year, temp1month, temp1day, temp1hour, temp1minute, temp1second,
temp1microsec)
print(get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMRecord', 'msgHeader', 'myRFLevel']))
firsttim_id = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMRecord', 'timMsg', 'packetID'])
first_sight_lat = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMLocation', 'coreData', 'lat']) / Loc_Factor
first_sight_long = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMLocation', 'coreData', 'long']) / Loc_Factor
first_sight_speed = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMLocation', 'coreData', 'speed'])
first_sight_head = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMLocation', 'coreData', 'heading']) * Head_Factor
#print(get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime']))
temp2year = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime', 'year'])
temp2month = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime', 'month'])
temp2day = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime', 'day'])
temp2hour = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime', 'hour'])
temp2minute = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime', 'minute'])
temp2second = floor(get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime', 'second']) / 1000)
temp2microsec = (get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMTime', 'second']) % 1000) * 1000
temp2fulltime = datetime.datetime(temp2year, temp2month, temp2day, temp2hour, temp2minute, temp2second,
temp2microsec)
print(get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMRecord', 'msgHeader', 'myRFLevel']))
lasttim_id = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMRecord', 'timMsg', 'packetID'])
last_sight_lat = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMLocation', 'coreData', 'lat']) / Loc_Factor
last_sight_long = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMLocation', 'coreData', 'long']) / Loc_Factor
last_sight_speed = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMLocation', 'coreData', 'speed'])
last_sight_head = get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMLocation', 'coreData', 'heading']) * Head_Factor
tim_refP_lat = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMRecord', 'timMsg', 'dataFrames', 0, 'msgId', 'roadSignID', 'position', 'lat']) / Loc_Factor
tim_refP_long = get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMRecord', 'timMsg', 'dataFrames', 0, 'msgId',
'roadSignID', 'position', 'long']) / Loc_Factor
traversersedtime = abs(temp1fulltime - temp2fulltime)
# TODO - PacketID Read is reading 0x4E as "N" Need to Fix
# print(input_rf_log.to_asn1())
# print("Rojer" + str(firsttim_id))
# print(get_val_at(input_rf_log, ['timRFList', 0, 'firstTIMRecord', 'timMsg', 'packetID']))
# print(lasttim_id)
# print(get_val_at(input_rf_log, ['timRFList', 0, 'lastTIMRecord', 'timMsg', 'packetID']))
if firsttim_id == lasttim_id:
if traversersedtime.total_seconds != 0:
print("Valid TIM RF Log")
# firstmap_id + filename
# http://maps.google.com/mapfiles/kml/shapes/placemark_circle.png
kml = simplekml.Kml()
pnt = kml.newpoint(name="", coords=[(tim_refP_long, tim_refP_lat)])
pnt.iconstyle = simplekml.IconStyle(scale=2, heading=0,
icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None,
href='http://maps.google.com/mapfiles/kml/paddle/T.png'),
hotspot=None)
pnt = kml.newpoint(name="", coords=[(first_sight_long, first_sight_lat)])
pnt.iconstyle = simplekml.IconStyle(color=simplekml.Color.rgb(0, 255, 0), scale=0.4, heading=first_sight_head - 180,
icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None,
href='http://maps.google.com/mapfiles/kml/shapes/arrow.png'),
hotspot=None)
pnt = kml.newpoint(name="", coords=[(last_sight_long, last_sight_lat)])
pnt.iconstyle = simplekml.IconStyle(color=simplekml.Color.rgb(0, 0, 255), scale=0.4, heading=last_sight_head - 180,
icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None,
href='http://maps.google.com/mapfiles/kml/shapes/arrow.png'),
hotspot=None)
temp_str = str(firsttim_id)
temp_str = temp_str.replace("\\x", "")
temp_str = temp_str.replace("b'", "")
temp_str = temp_str.replace("'", "")
print(str(firsttim_id))
print(temp_str)
kml.save(
OutputLogDirectory + '\\' + temp_str[0:2] + "_" + temp_str[-4:] + "_TIM_" + get_val_at(input_rf_log, ['asdSerialNumber']) + "_" + filename + '.kml')
print("TIMRF -> BSM Heading in RF Log (Last):" + str(first_sight_head))
print("TIMRF ->BSM Heading in RF Log (Last):" + str(last_sight_head))
print("TIMRF ->BSM Speed in RF Log (Last):" + str(first_sight_speed))
print("TIMRF ->BSM Speed in RF Log (Last):" + str(last_sight_speed))
else:
print("Invalid TIM RF Log. TIM RF Log Time Difference is 0.")
else:
print("Invalid TIM RF Log. First and Last TIM Entries have different TIM Messages")
def process_spat_rf(input_rf_log, filename):
#print(input_rf_log.to_asn1())
#print(get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime']))
temp1year = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime', 'year'])
temp1month = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime', 'month'])
temp1day = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime', 'day'])
temp1hour = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime', 'hour'])
temp1minute = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime', 'minute'])
temp1second = floor(get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime', 'second']) / 1000)
temp1microsec = (get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTTime', 'second']) % 1000) * 1000
temp1fulltime = datetime.datetime(temp1year, temp1month, temp1day, temp1hour, temp1minute, temp1second,
temp1microsec)
print(get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTRecord', 'msgHeader', 'myRFLevel']))
firstmap_id = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTRecord', 'spatMsg', 'intersections', 0, 'id', 'id'])
first_sight_lat = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTLocation', 'coreData', 'lat']) / Loc_Factor
first_sight_long = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTLocation', 'coreData', 'long']) / Loc_Factor
first_sight_speed = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTLocation', 'coreData', 'speed'])
first_sight_head = get_val_at(input_rf_log, ['spatRFList', 0, 'firstSPaTLocation', 'coreData', 'heading']) * Head_Factor
#print(get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime']))
temp2year = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime', 'year'])
temp2month = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime', 'month'])
temp2day = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime', 'day'])
temp2hour = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime', 'hour'])
temp2minute = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime', 'minute'])
temp2second = floor(get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime', 'second']) / 1000)
temp2microsec = (get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTTime', 'second']) % 1000) * 1000
temp2fulltime = datetime.datetime(temp2year, temp2month, temp2day, temp2hour, temp2minute, temp2second,
temp2microsec)
print(get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTRecord', 'msgHeader', 'myRFLevel']))
lastmap_id = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTRecord', 'spatMsg', 'intersections', 0, 'id', 'id'])
last_sight_lat = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTLocation', 'coreData', 'lat']) / Loc_Factor
last_sight_long = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTLocation', 'coreData', 'long']) / Loc_Factor
last_sight_speed = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTLocation', 'coreData', 'speed'])
last_sight_head = get_val_at(input_rf_log, ['spatRFList', 0, 'lastSPaTLocation', 'coreData', 'heading']) * Head_Factor
traversersedtime = abs(temp1fulltime - temp2fulltime)
if firstmap_id == lastmap_id:
if traversersedtime.total_seconds != 0:
print("Valid SPaT RF Log")
SPaT_RSU_Pos = MAP_SPaT_DB_Cleaned[MAP_SPaT_DB_Cleaned.AstcId.eq(str(firstmap_id))]
#print(SPaT_RSU_Pos)
if SPaT_RSU_Pos.empty:
print("No matching Intersection ID found in database.. Skipping..")
else:
SPaT_RSUL_lat = int(SPaT_RSU_Pos.iloc[0].RsuLocLatitude) / Loc_Factor
SPaT_RSUL_long = int(SPaT_RSU_Pos.iloc[0].RsuLocLongitude) / Loc_Factor
kml = simplekml.Kml()
pnt = kml.newpoint(name="", coords=[(SPaT_RSUL_long, SPaT_RSUL_lat)])
pnt.iconstyle = simplekml.IconStyle(scale=2, heading=0,
icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None,
href='http://maps.google.com/mapfiles/kml/paddle/S.png'),
hotspot=None)
pnt = kml.newpoint(name="", coords=[(first_sight_long, first_sight_lat)])
pnt.iconstyle = simplekml.IconStyle(color=simplekml.Color.rgb(0, 255, 0), scale=0.4, heading=first_sight_head - 180,
icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None,
href='http://maps.google.com/mapfiles/kml/shapes/arrow.png'),
hotspot=None)
pnt = kml.newpoint(name="", coords=[(last_sight_long, last_sight_lat)])
pnt.iconstyle = simplekml.IconStyle(color=simplekml.Color.rgb(0, 0, 255), scale=0.4, heading=last_sight_head - 180,
icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None,
href='http://maps.google.com/mapfiles/kml/shapes/arrow.png'),
hotspot=None)
kml.save(
OutputLogDirectory + '\\' + str(firstmap_id) + "_SPaT_" + get_val_at(input_rf_log, ['asdSerialNumber']) + "_" + filename + '.kml')
print("SPaTRF -> BSM Heading in RF Log (Last):" + str(first_sight_head))
print("SPaTRF ->BSM Heading in RF Log (Last):" + str(last_sight_head))
print("SPaTRF ->BSM Speed in RF Log (Last):" + str(first_sight_speed))
print("SPaTRF ->BSM Speed in RF Log (Last):" + str(last_sight_speed))
else:
print("Invalid SPaT RF Log. SPaT RF Log Time Difference is 0.")
else:
print("Invalid SPaT RF Log. First and Last SPaT Entries have different SPaT Messages")
def bc2kml(input_bc_file,filename):
#print("Function that converts NYC BreadCrumb Log to KML File")
totaldistance = 0
kml = simplekml.Kml()
print("SerialNumber of BC Log: " + get_val_at(input_bc_file, ['asdSerialNumber']))
print("Resolution of Bread Crumbs in BC Log: " + get_val_at(input_bc_file, ['timeRecordResolution']))
bc = get_val_at(input_bc_file, ['locList'])
numberofbc = len(bc)
avgspeedlist = []
#print(input_bc_file.to_asn1())
for j in range(numberofbc):
pnt = kml.newpoint(name="", coords=[(get_val_at(input_bc_file, ['locList', j, 'longitude'])/Loc_Factor, get_val_at(input_bc_file, ['locList', j, 'latitude'])/Loc_Factor)])
pnt.iconstyle = simplekml.IconStyle(color = simplekml.Color.rgb(255, 0, 0), scale=0.5, heading=0, icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None, href = 'http://maps.google.com/mapfiles/kml/shapes/placemark_circle.png'), hotspot=None)
#pnt.style.iconstyle.icon.href = 'http://maps.google.com/mapfiles/kml/shapes/info-i.png'
#pnt.style.iconstyle.color = simplekml.Color.rgb(255, 0, 0) # RGB values(255,255,0)
if j > 0:
tempdistance = distancecalc((get_val_at(input_bc_file, ['locList', j, 'latitude'])/Loc_Factor),(get_val_at(input_bc_file, ['locList', j, 'longitude'])/Loc_Factor),(get_val_at(input_bc_file, ['locList', j-1, 'latitude'])/10000000),(get_val_at(input_bc_file, ['locList', j-1, 'longitude'])/Loc_Factor))
totaldistance = totaldistance + tempdistance
temp1year = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'year'])
temp1month = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'month'])
temp1day = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'day'])
temp1hour = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'hour'])
temp1minute = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'minute'])
temp1second = floor(get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) / 1000)
temp1microsec = (get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) % 1000) * 1000
temp1fulltime = datetime.datetime(temp1year, temp1month, temp1day, temp1hour, temp1minute, temp1second,temp1microsec)
temp2year = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'year'])
temp2month = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'month'])
temp2day = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'day'])
temp2hour = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'hour'])
temp2minute = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'minute'])
temp2second = floor(get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'second']) / 1000)
temp2microsec = (get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'second']) % 1000) * 1000
temp2fulltime = datetime.datetime(temp2year, temp2month, temp2day, temp2hour, temp2minute, temp2second,temp2microsec)
temptraversersedtime = abs(temp1fulltime - temp2fulltime)
if temptraversersedtime.total_seconds() != 0:
tempavgspeed = round(tempdistance / temptraversersedtime.total_seconds(),5)
avgspeedlist.append(tempavgspeed)
else:
print("Duplicate BC Log.. Avoid Divide by zero..")
if j == 0:
tempyear = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'year'])
tempmonth = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'month'])
tempday = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'day'])
temphour = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'hour'])
tempminute = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'minute'])
tempsecond = floor(get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) / 1000)
tempmicrosec = (get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) % 1000) * 1000
firstbctime = datetime.datetime(tempyear, tempmonth, tempday, temphour, tempminute, tempsecond, tempmicrosec)
if j == (numberofbc-1):
tempyear = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'year'])
tempmonth = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'month'])
tempday = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'day'])
temphour = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'hour'])
tempminute = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'minute'])
tempsecond = floor(get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) / 1000)
tempmicrosec = (get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) % 1000) * 1000
lastbctime = datetime.datetime(tempyear, tempmonth, tempday, temphour, tempminute, tempsecond, tempmicrosec)
BCavgspeed = round(sum(avgspeedlist) / len(avgspeedlist),5)
traversersedtime = abs(lastbctime - firstbctime)
#print(traversersedtime.total_seconds())
kml.save(OutputLogDirectory + '\\' + get_val_at(input_bc_file, ['asdSerialNumber']) + "_" + filename + '.kml')
print("TimeStamp of First BC Entry= " + str(firstbctime))
print("TimeStamp of Last BC Entry= " + str(lastbctime))
print("Total time between first and last BC= " + str(traversersedtime.total_seconds()) + "seconds")
print("Total Distance travelled in BC Log (m): " + str(round(totaldistance,2)) + " m")
print("Total Distance travelled in BC Log (km): " + str(round(totaldistance / 1000,2)) + " km" )
print("Average Speed in BC Log (mps): " + str(BCavgspeed) + " mps")
print("Average Speed in BC Log (mph): " + str(round(BCavgspeed * 2.23694,2)) + " mph")
pdf = FPDF(orientation='P', unit='mm', format='A4')
pdf.add_page()
pdf.set_font("Arial", size=10)
pdf.cell(200, 10, txt="Processed File Name" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + filename, ln=1, align="L")
pdf.cell(200, 10, txt="Processed File Type" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + "Bread Crumb Log", ln=1, align="L")
pdf.cell(200, 10, txt="Processed File ASN Version" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + "J2735_NYC_03062020", ln=1, align="L")
pdf.cell(200, 10, txt="Serial Number of ASD" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + get_val_at(input_bc_file, ['asdSerialNumber']), ln=1, align="L")
pdf.cell(200, 10, txt="Resolution of Bread Crumbs" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + get_val_at(input_bc_file, ['timeRecordResolution']), ln=1, align="L")
pdf.cell(200, 10, txt="TimeStamp of First BC Entry" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + str(firstbctime), ln=1, align="L")
pdf.cell(200, 10, txt="TimeStamp of Last BC Entry" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + str(lastbctime), ln=1, align="L")
pdf.cell(200, 10, txt="Total time between first and last BC" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + str(traversersedtime.total_seconds()) + "seconds", ln=1, align="L")
pdf.cell(200, 10, txt="Total Distance travelled in BC Log (m)" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + str(round(totaldistance,2)) + " m", ln=1, align="L")
pdf.cell(200, 10, txt="Total Distance travelled in BC Log (km)" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + str(round(totaldistance / 1000,2)) + " km", ln=1, align="L")
pdf.cell(200, 10, txt="Average Speed in BC Log (mps)" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + str(BCavgspeed) + " mps", ln=1, align="L")
pdf.cell(200, 10, txt="Average Speed in BC Log (mph)" + "\t" + "\t" + "\t" + "\t" + "\t" + ":" + "\t" + str(round(BCavgspeed * 2.23694,2)) + " mph", ln=1, align="L")
pdf.output(OutputLogDirectory + '\\' + get_val_at(input_bc_file, ['asdSerialNumber']) + "_" + filename + '.pdf')
pid_trips = route.GetPatternIdTripDict()
for pattern_id in pid_trips.keys():
trip = pid_trips[pattern_id][
0] # Since we only want to map, any trip will do
print trip["trip_id"], route["route_id"]
if trip["direction_id"] == "1":
direction = " (Reverse)"
else:
# direction = " (Forward)"
direction = ""
shape = gtfs.GetShape(trip["shape_id"])
coords = [(lon, lat) for (lat, lon, dist) in shape.points]
name = route["route_short_name"] + ": " + route[
"route_long_name"] + direction
line = routefolder.newlinestring(name=name, coords=coords)
line.iconstyle = simplekml.IconStyle(icon=simplekml.Icon(
href="http://maps.google.com/mapfiles/kml/pal2/icon13.png"))
if "route_color" in route.keys() and route.route_color != '':
color = "8F" + route.route_color
else:
color = "8F" + default_color
line.linestyle = simplekml.LineStyle(width=4, color=color)
stopfolder = routefolder.newfolder(name="Stops")
for stop in trip.GetPattern():
coords = [(stop.stop_lon, stop.stop_lat)]
stopfolder.newpoint(coords=coords, name=stop.stop_name)
# TODO: Stops not in any route
#orphan_stops = kml.newfolder(name="Unused Stops")
# Possible TODO: handle multiple instances of same stop
kml.save("test.kml", False)
def bc2kml(input_bc_file,filename):
#print("Function that converts NYC BreadCrumb Log to KML File")
totaldistance = 0
kml = simplekml.Kml()
# print("SerialNumber of BC Log: " + get_val_at(input_bc_file, ['asdSerialNumber']))
# print("Resolution of Bread Crumbs in BC Log: " + get_val_at(input_bc_file, ['timeRecordResolution']))
bc = get_val_at(input_bc_file, ['locList'])
numberofbc = len(bc)
avgspeedlist = []
#print(input_bc_file.to_asn1())
for j in range(numberofbc):
pnt = kml.newpoint(name="", coords=[(get_val_at(input_bc_file, ['locList', j, 'longitude'])/Loc_Factor, get_val_at(input_bc_file, ['locList', j, 'latitude'])/Loc_Factor)])
pnt.iconstyle = simplekml.IconStyle(color = simplekml.Color.rgb(255, 0, 0), scale=0.5, heading=0, icon=simplekml.Icon(gxx=None, gxy=None, gxw=None, gxh=None, href = 'http://maps.google.com/mapfiles/kml/shapes/placemark_circle.png'), hotspot=None)
#pnt.style.iconstyle.icon.href = 'http://maps.google.com/mapfiles/kml/shapes/info-i.png'
#pnt.style.iconstyle.color = simplekml.Color.rgb(255, 0, 0) # RGB values(255,255,0)
if j > 0:
tempdistance = distancecalc((get_val_at(input_bc_file, ['locList', j, 'latitude'])/Loc_Factor),(get_val_at(input_bc_file, ['locList', j, 'longitude'])/Loc_Factor),(get_val_at(input_bc_file, ['locList', j-1, 'latitude'])/10000000),(get_val_at(input_bc_file, ['locList', j-1, 'longitude'])/Loc_Factor))
totaldistance = totaldistance + tempdistance
temp1year = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'year'])
temp1month = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'month'])
temp1day = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'day'])
temp1hour = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'hour'])
temp1minute = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'minute'])
temp1second = floor(get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) / 1000)
temp1microsec = (get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) % 1000) * 1000
temp1fulltime = datetime.datetime(temp1year, temp1month, temp1day, temp1hour, temp1minute, temp1second,temp1microsec)
temp2year = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'year'])
temp2month = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'month'])
temp2day = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'day'])
temp2hour = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'hour'])
temp2minute = get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'minute'])
temp2second = floor(get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'second']) / 1000)
temp2microsec = (get_val_at(input_bc_file, ['locList', j-1, 'timeStamp', 'second']) % 1000) * 1000
temp2fulltime = datetime.datetime(temp2year, temp2month, temp2day, temp2hour, temp2minute, temp2second,temp2microsec)
temptraversersedtime = abs(temp1fulltime - temp2fulltime)
if temptraversersedtime.total_seconds() != 0:
tempavgspeed = round(tempdistance / temptraversersedtime.total_seconds(),5)
avgspeedlist.append(tempavgspeed)
else:
print("Duplicate BC Log.. Avoid Divide by zero..")
if j == 0:
tempyear = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'year'])
tempmonth = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'month'])
tempday = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'day'])
temphour = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'hour'])
tempminute = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'minute'])
tempsecond = floor(get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) / 1000)
tempmicrosec = (get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) % 1000) * 1000
firstbctime = datetime.datetime(tempyear, tempmonth, tempday, temphour, tempminute, tempsecond, tempmicrosec)
if j == (numberofbc-1):
tempyear = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'year'])
tempmonth = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'month'])
tempday = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'day'])
temphour = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'hour'])
tempminute = get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'minute'])
tempsecond = floor(get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) / 1000)
tempmicrosec = (get_val_at(input_bc_file, ['locList', j, 'timeStamp', 'second']) % 1000) * 1000
lastbctime = datetime.datetime(tempyear, tempmonth, tempday, temphour, tempminute, tempsecond, tempmicrosec)
BCavgspeed = round(sum(avgspeedlist) / len(avgspeedlist),5)
traversersedtime = abs(lastbctime - firstbctime)
#print(traversersedtime.total_seconds())
kml.save(OutputLogDirectory + '\\' + get_val_at(input_bc_file, ['asdSerialNumber']) + "_" + filename + '.kml')
return
