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usairportcode_origin_dest.py
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"""Transformer to parse and augment US airport codes with geolocation info."""
from h2oaicore.separators import orig_feat_prefix
from h2oaicore.transformer_utils import CustomTransformer
from h2oaicore.systemutils import make_experiment_logger, loggerinfo, loggerwarning
import datatable as dt
import pandas as pd
import math
import numpy as np
def computeDistance(lat1, lon1, lat2, lon2):
p = 0.017453292519943295 # Pi/180
a = 0.5 - math.cos((lat2 - lat1) * p) / 2 + math.cos(lat1 * p) * math.cos(lat2 * p) * (
1 - math.cos((lon2 - lon1) * p)) / 2
return 12742 * math.asin(math.sqrt(a)) # 2*R*asin...
class AirportOriginDestPDTransformer(CustomTransformer):
_unsupervised = True
_allow_transform_to_modify_output_feature_names = True
_numeric_output = True
_mojo = False
@staticmethod
def do_acceptance_test():
return True
@staticmethod
def get_default_properties():
return dict(col_type="categorical", min_cols="all", max_cols="all", relative_importance=1)
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.transformer_name = self.__class__.__name__
if self.transformer_name.endswith("Transformer"):
self.transformer_name = self.transformer_name[:-len("Transformer")]
def fit_transform(self, X: dt.Frame, y: np.array = None):
return self.transform(X)
def transform(self, X: dt.Frame):
logger = None
if self.context and self.context.experiment_id:
logger = make_experiment_logger(experiment_id=self.context.experiment_id,
tmp_dir=self.context.tmp_dir,
experiment_tmp_dir=self.context.experiment_tmp_dir)
# X = X[:, dt.str64(dt.f[0])]
X = dt.Frame(X)
codes_pd = self.make_airportcode_data().to_pandas()
# Origin
isOrigin = False
if ("Origin" in X.names):
isOrigin = True
origin_pd = X[:, "Origin"].to_pandas()
origin_pd = pd.merge(origin_pd, codes_pd, how="left", left_on="Origin", right_on="iata_code")
origin_pd = origin_pd.drop(["Origin", "iata_code"], axis=1)
origin_pd.columns = ["origin_elevation_ft", "origin_long", "origin_lat"]
# Destination
isDest = False
if ("Dest" in X.names):
isDest = True
dest_pd = X[:, "Dest"].to_pandas()
dest_pd = pd.merge(dest_pd, codes_pd, how="left", left_on="Dest", right_on="iata_code")
dest_pd = dest_pd.drop(["Dest", "iata_code"], axis=1)
dest_pd.columns = ["dest_elevation_ft", "dest_long", "dest_lat"]
# Both Origin and Destination
if (isOrigin and isDest):
all_pd = pd.concat([origin_pd, dest_pd], axis=1)
all_pd['elevation_diff'] = all_pd['origin_elevation_ft'] - all_pd['dest_elevation_ft']
all_pd['lat_diff'] = all_pd['origin_lat'] - all_pd['dest_lat']
all_pd['long_diff'] = all_pd['origin_long'] - all_pd['dest_long']
all_pd['distance_km'] = all_pd.apply(lambda row: computeDistance(row['origin_lat'], row['origin_long'],
row['dest_lat'], row['dest_long']),
axis=1)
# self._output_feature_names = ['origin_elevation_ft', 'origin_long', 'origin_lat', 'dest_elevation_ft',
# 'dest_long', 'dest_lat', 'elevation_diff', 'lat_diff', 'long_diff']
self._output_feature_names = ["{}{}{}{}{}.{}".format(self.transformer_name,
orig_feat_prefix, "Origin", orig_feat_prefix, "Dest",
f) for f in
['origin_elevation_ft', 'origin_long', 'origin_lat', 'dest_elevation_ft',
'dest_long', 'dest_lat', 'elevation_diff', 'lat_diff', 'long_diff',
'distance_km']]
self._feature_desc = ['Origin Elevation Ft.', 'Origin Longitude', 'Origin Latitude',
'Destination Elevation', 'Destination Longitude', 'Destination Latitude',
'Elevation difference between Origin and Destination',
'Latitude difference between Origin and Destination',
'Longitude difference between Origin and Destination',
'Distance in km between Origin and Destination (Harvestine approx.)']
else:
all_pd = np.zeros(X.shape[0])
return all_pd
def make_airportcode_data(self):
return dt.fread(
"""
iata_code,elevation_ft,long,lat
ALZ,,-154.248001099,56.8995018005
APR,220,142.540138889,-4.67666666667
AQY,150,-149.126007,60.966099
DOI,31,150.7218,-10.7009
EMO,2240,148.0415,-9.1234
IMN,3860,146.1072,-6.7524
LAB,160,148.0566,-5.7204
NKN,5800,146.4533,-5.837
PMN,427,149.4766,-9.7469
TEP,7011,146.5595,-5.9553
AYU,5355,145.904166667,-6.33805555556
WOA,5028,145.891944444,-6.796861111110001
WTP,5200,147.2525,-8.54583333333
AZB,12,149.338333333,-10.2991666667
BNF,0,-134.833146,57.088799
BOF,20,-77.0160980225,38.842899322499996
BOK,459,-124.290001,42.0746
BQV,0,-135.884994507,58.4552001953
BYA,2940,-141.113006592,64.0783004761
YMD,30,-119.3216,76.2392
CGA,,-133.1479949951172,55.47880172729492
CHP,956,-144.610992432,65.485496521
CKU,12,-145.727005005,60.5438995361
CKX,1640,-141.95199585,64.0712966919
CXC,556,-144.427001953,61.582901001
YKY,2277,-109.180999756,51.5175018311
YMW,656,-75.9906005859,46.2728004456
YOW,374,-75.66919708251953,45.3224983215332
YPZ,2343,-125.950996399,54.3763999939
YQB,244,-71.393303,46.7911
YSE,171,-123.162002563,49.7817001343
YUL,118,-73.7407989502,45.4706001282
YVG,2025,-110.823997498,53.355800628699996
YWG,783,-97.2398986816,49.909999847399995
YYM,3876,-114.09400177,49.636398315399994
YYZ,569,-79.63059997559999,43.6772003174
CZK,151,-121.878997803,45.6768989563
CZN,3318,-142.04800415,62.0712013245
CZO,1850,-144.669006348,62.5634994507
IUA,814,-77.325226,42.908902
DBP,360,141.905555556,-6.30861111111
DCK,260,-156.904998779,66.9432983398
DCR,842,-84.862464,40.837548
DDM,75,147.809444444,-8.17736111111
-,,11.375,55.035
EXI,0,-135.449005,58.420502
FIN,60,147.85405,-6.621750109
FLT,309,-157.988998413,62.452598571799996
GAB,4700,-117.958999634,38.924098968500005
GEW,340,148.4949,-9.2263
GFD,895,-85.7360992432,39.790298461899994
GNU,15,-161.57699585,59.117401123
GVE,454,-78.165802002,38.15599823
HAY,175,-161.156997681,65.20099639889999
HEY,317,-85.65429688,31.34600067
HGT,1017,-121.2369995,35.99349976
HNE,2960,-147.304000854,61.901401519800004
HYL,0,-132.645996094,55.4816017151
IOK,39,146.277,-8.401
ITK,2563,148.264261,-9.201527
JLA,450,-149.718994141,60.48270034789999
JPN,40,-77.0575027466,38.8740997314
JRA,7,-74.007103,40.754501
JRB,7,-74.00900269,40.70119858
AAF,20,-85.02749634,29.72750092
ABE,393,-75.44080352783203,40.652099609375
ABI,1791,-99.68190002440001,32.4113006592
ABQ,5355,-106.609001,35.040199
ABR,1302,-98.42179870605469,45.449100494384766
ABY,197,-84.19450378417969,31.535499572753906
ACB,623,-85.198402,44.988602
ACK,47,-70.06020355,41.25310135
ACT,516,-97.23049926757812,31.611299514770508
ACV,221,-124.109,40.978101
ACY,75,-74.57720184326172,39.45759963989258
ADG,798,-84.07730102539999,41.8676986694
ADM,777,-97.0196342,34.30301
ADS,644,-96.8364028931,32.9686012268
ADW,280,-76.866997,38.810799
KAE,,-133.945999,56.973
AEL,1260,-93.36720276,43.68149948
AEX,89,-92.54979705810547,31.32740020751953
AFF,6572,-104.8130035,38.96969986
AFN,1040,-72.0029983521,42.805099487300005
AFO,6221,-110.942001343,42.7112007141
AFW,722,-97.31880187990001,32.9875984192
AGC,1252,-79.9301986694336,40.354400634765625
AGO,319,-93.217002,33.228001
AGS,144,-81.9645004272461,33.36989974975586
AHC,4012,-120.1529999,40.26620102
AHH,1088,-92.37539672850001,45.2811012268
AHN,808,-83.32630157470703,33.94860076904297
AIA,3931,-102.804000854,42.0531997681
AID,919,-85.6129989624,40.10860061649999
AIK,528,-81.684998,33.649399
AIO,1165,-95.04689789,41.40729904
AIV,150,-88.1978,33.106499
AIY,8,-74.4561004639,39.3600006104
AIZ,869,-92.54949951170002,38.0960006714
AKO,4714,-103.222000122,40.1755981445
ALB,285,-73.80169677734375,42.74829864501953
ALI,178,-98.02690124510002,27.740900039699998
ALM,4200,-105.990997314,32.8399009705
ALN,544,-90.0459976196,38.89030075069999
ALO,873,-92.40029907226562,42.557098388671875
ALS,7539,-105.866997,37.434898
ALW,1194,-118.288002,46.09489822
ALX,686,-85.9629974365,32.914699554399995
AMA,3607,-101.706001,35.219398
AMN,754,-84.68800354,43.322101593
AMW,956,-93.621803,41.992001
ANB,612,-85.8581,33.5882
AND,782,-82.70939636230001,34.4945983887
ANP,34,-76.568398,38.942902
ANQ,995,-85.083504,41.639702
ANW,2589,-99.992995,42.579201
ANY,1340,-98.079597,37.158501
AOH,975,-84.026703,40.706902
AOO,1503,-78.31999969,40.29639816
APA,5885,-104.848999,39.57009888
APC,35,-122.280998,38.2132
APF,8,-81.7752990723,26.1525993347
APG,57,-76.1688,39.466202
APH,220,-77.318298,38.068902
APN,690,-83.56030273,45.0780983
APT,641,-85.585297,35.060699
APV,3062,-117.185997009,34.575298309299995
ARA,24,-91.883904,30.0378
ARB,839,-83.74559783939999,42.2229995728
ARG,279,-90.925111,36.124667
ART,325,-76.02169799804688,43.99190139770508
ARV,1629,-89.73090363,45.92789841
ASE,7820,-106.8690033,39.22320175
ASH,199,-71.51480102539999,42.7817001343
ASL,357,-94.307800293,32.5205001831
ASN,529,-86.05090332030001,33.569900512699995
AST,15,-123.878997803,46.158000946
ASX,827,-90.91899872,46.54850006
ASY,2032,-99.3526000977,46.0238990784
ATL,1026,-84.428101,33.6367
ATS,3541,-104.468002319,32.8525009155
ATW,918,-88.5190963745,44.258098602299995
ATY,1749,-97.15470123,44.91400146
AUG,352,-69.7973022461,44.320598602299995
AUM,1234,-92.93340302,43.66500092
AUN,1539,-121.0820007,38.95479965
AUO,777,-85.433998,32.615101
AUS,542,-97.6698989868164,30.194499969482422
AUW,1201,-89.6266021729,44.9262008667
AVL,2165,-82.54180145263672,35.43619918823242
AVO,160,-81.52780151,27.59119987
AVP,962,-75.72339630130001,41.338500976599995
AVX,1602,-118.416,33.4049
AWM,212,-90.2343978882,35.1351013184
AXN,1425,-95.39469909670001,45.8662986755
AXS,1433,-99.3385,34.697952
AXV,913,-84.29889679,40.49340057
AXX,8380,-105.290000916,36.422000885
AYS,142,-82.39550018310001,31.2490997314
AZO,874,-85.5521011352539,42.234901428222656
BAB,113,-121.43699646,39.136100769
BAD,166,-93.6626968384,32.5018005371
BAF,271,-72.715599,42.157799
BAM,4532,-116.874000549,40.598999023400005
BBB,1039,-95.6505966187,45.331901550299996
BBD,1827,-99.3238983154,31.1793003082
BBW,2547,-99.6421966553,41.4365005493
BCB,2132,-80.4077987671,37.207599639899996
BCE,7590,-112.144996643,37.706401825
BCT,13,-80.1076965332,26.3784999847
BDE,1086,-94.612197876,48.7284011841
BDG,5868,-109.4830017,37.58330154
BDL,173,-72.68319702149999,41.9388999939
BDR,9,-73.1261978149414,41.16350173950195
KBE,,-131.572006226,55.9291000366
BEC,1408,-97.21499633790002,37.694499969499994
BED,133,-71.28900146,42.47000122
BEH,643,-86.4284973145,42.128601074200006
BFD,2143,-78.64009857177734,41.8031005859375
BFF,3967,-103.5960007,41.87400055
BFI,21,-122.302001953125,47.529998779296875
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