ChipMaster's bwBASIC This also includes history going back to v2.10. *WARN* some binary files might have been corrupted by CRLF.
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254 lines
14 KiB

  1. 10 'Tested on CP/M and Added CLS change 18 July 87, Jim Lill
  2. 20 'fixed misspellings and redundancies in data
  3. 30 CLS$=CHR$(26):' set for your terminal
  4. 40 C%=330:' THIS IS NUMBER OF CITIES
  5. 50 DIM A1%(26)
  6. 60 DIM N$(C%),LA(C%),LO(C%)
  7. 70 PI= 4 * ATN(1):'added in CP/M conversion
  8. 80 PI2=2 * PI
  9. 90 DG=360/PI2 '2 pi radians in 360 degrees
  10. 100 'arc cosine function using arc tangent & sin2(x) + cos2(x) = 1
  11. 110 DEF FNACOS(V1)=ATN(SQR(1-V1*V1)/V1)*DG 'answer returned in degrees
  12. 120 'GREAT CIRCLE MILEAGE
  13. 130 'Note: If you wish to add cities to the data list, they
  14. 140 'must be inserted alphabetically (by first letter only), and the
  15. 150 'value of "C%" (in the first line) increased accordingly.
  16. 160 'The data for each city is the name, latitude and longitude.
  17. 170 'Latitude is +/- 90 degrees. Negative values are below the equator.
  18. 180 'Longitude is +/- 180 degrees. Negative values are East of Greenwich.
  19. 190 'Duplicate entries arise when data sources disagree on lat/long.
  20. 200 PRINT CLS$:PRINT "AIRLINE DISTANCES BETWEEN CITIES"
  21. 210 PRINT:PRINT:PRINT"If you are not sure of the spelling of a city,"
  22. 220 PRINT "type in only the first letters of which you are confident."
  23. 230 PRINT
  24. 240 PRINT "All entries must be in UPPER CASE."
  25. 250 PRINT:PRINT "PLEASE WAIT FOR ARRAYS TO BE SET UP."
  26. 260 X%=1 'Index to letters of alphabet
  27. 270 FOR Y=1 TO C%: READ N$(Y),LA(Y),LO(Y)
  28. 280 'Find data positions for each letter of the alphabet
  29. 290 'Brackets search positions and makes database updates easier.
  30. 300 IF ASC(LEFT$(N$(Y),1))<=64+X% THEN GOTO 330 'First occurrence of new letter
  31. 310 A1%(X%)=Y-1:X%=X%+1 'Number of last city in the list with letter# X%
  32. 320 GOTO 300 'In case no cities started with X%-1
  33. 330 NEXT Y
  34. 340 A1%(26)=C% 'guarantee last entry
  35. 350 PRINT
  36. 360 INPUT "TYPE IN CITY OF ORIGIN ";A$
  37. 370 GOSUB 560
  38. 380 IF C1%>0 THEN GOTO 400
  39. 390 PRINT "NO CITY SELECTED":PRINT:GOTO 550
  40. 400 LAT1=LA(C1%)/DG:LONG1=LO(C1%)/DG:L$=N$(C1%)
  41. 410 PRINT
  42. 420 INPUT "TYPE IN DESTINATION CITY NAME ";A$
  43. 430 GOSUB 560
  44. 440 IF C1%>0 THEN GOTO 460
  45. 450 PRINT "NO CITY SELECTED":PRINT:GOTO 550
  46. 460 LAT2=LA(C1%)/DG:LONG2=LO(C1%)/DG:M$=N$(C1%)
  47. 470 DAB=SIN(LAT1)*SIN(LAT2)+COS(LAT1)*COS(LAT2)*COS(LONG1-LONG2)
  48. 480 DIST=ABS(FNACOS(DAB))
  49. 490 PRINT Z$
  50. 500 PRINT"THE DISTANCE FROM ";L$;" TO ";M$;" IS:"
  51. 510 PRINT USING "#####,.#";DIST*69.113;:PRINT" STATUTE MILES ";
  52. 520 PRINT USING "#####,.#";DIST*60.0576;:PRINT" NAUTICAL MILES ";
  53. 530 PRINT USING "#####,.#";DIST*111.203;:PRINT" KILOMETERS"
  54. 540 PRINT
  55. 550 INPUT "RUN AGAIN? ",A$: IF LEFT$(A$,1)="Y" OR LEFT$(A$,1)="Y" THEN GOTO 350 ELSE END
  56. 560 'Subroutine to find the city's name.
  57. 570 T=ASC(LEFT$(A$,1))-64 'Number (1-26) of first letter of city name.
  58. 580 BOT%=A1%(T-1)+1:TOP%=A1%(T)
  59. 590 'First & last cities starting with this letter.
  60. 600 'A1%(T-1) is the last position of the letter before this one.
  61. 610 'Thus the next one, A1%(T-1)+1, must be the first one with this letter.
  62. 620 'Your version of Basic must allow A1%(0) to exist or this won't work
  63. 630 'when a city begins with "A".
  64. 640 IF LEN(A$)>1 THEN GOTO 720 'Go try and match spelling
  65. 650 FOR M%=BOT% TO TOP% 'For each city
  66. 660 TT=24*(M% MOD 3)
  67. 670 PRINT M%;N$(M%);TAB(TT); 'Print a list of name & number
  68. 680 NEXT M%
  69. 690 PRINT:PRINT "CHOOSE THE NUMBER OF THE CITY YOU WANT"
  70. 700 INPUT "ENTER 0, TO QUIT";C1%
  71. 710 RETURN
  72. 720 'If more than one letter is given, try to match spelling.
  73. 730 C1%=0:J=0
  74. 740 FOR M%=BOT% TO TOP%
  75. 750 IF LEFT$(N$(M%),LEN(A$))=A$ THEN PRINT M%,N$(M%) :C1%=M%:J=J+1
  76. 760 NEXT
  77. 770 IF J=1 THEN RETURN
  78. 780 IF C1%<>0 THEN GOTO 690 ELSE GOTO 650
  79. 790 DATA ABILENE, 32.4514 , 99.7308, ACAPULCO, 16.85 , 99.9333
  80. 800 DATA ADDIS ABABA, 9.05 ,-38.7 ,AKRON, 41.0833 , 81.5122
  81. 810 DATA ALBANY, 42.6502 , 73.7502 ,ALBUQUERQUE, 33.0836 , 106.651
  82. 820 DATA ALLENTOWN, 40.6031 , 75.4683 ,ALTOONA, 40.5153 , 78.4008
  83. 830 DATA AMARILLO, 35.2075 , 101.834 ,AMSTERDAM, 52.35 ,-4.9
  84. 840 DATA ANCHORAGE, 61.1667 , 149.983 ,ANKARA, 39.9167 ,-32.8333
  85. 850 DATA ANN ARBOR, 42.2831 , 83.7478 ,ASHVILLE, 35.595 , 82.5572
  86. 860 DATA ATHENS, 37.9667 ,-23.7333 ,ATLANTA, 33.6381 , 84.4278
  87. 870 DATA AUGUSTA GA, 33.4722 , 81.9667 ,AUGUSTA ME, 44.3147 , 69.7747
  88. 880 DATA AUSTIN, 30.2692 , 97.7436 ,BAKERSFIELD, 35.3753 , 119.022
  89. 890 DATA BALBOA, 8.95 , 79.5667 ,BALTIMORE, 39.0175 , 76.67
  90. 900 DATA BANGOR, 44.8036 , 68.7717 ,BARCELONA, 41.4167 ,-2.1667
  91. 910 DATA BATON ROUGE, 30.4494 , 91.1833 ,BATTLE CREEK, 42.3161 , 85.18
  92. 920 DATA BEAUMONT, 30.3467 , 94.1025 ,BELFAST, 54.6667 , 5.833
  93. 930 DATA BELLINGHAM, 48.7594 , 122.467 ,BERKELEY, 37.8694 , 122.271
  94. 940 DATA BERLIN, 52.5333 ,-13.0833 ,BERN, 46.95 ,-7.3333
  95. 950 DATA BETHLEHEM, 40.6211 , 75.3761 ,BILLINGS, 45.7928 , 108.501
  96. 960 DATA BILOXI, 30.3967 , 88.8833 ,BINGHAMTON, 42.2075 , 75.9794
  97. 970 DATA BIRMINGHAM, 33.5169 , 86.81 ,BISMARCK, 46.8064 , 100.788
  98. 980 DATA BLOOMINGTON, 40.4828 , 88.9933 ,BOGOTA, 4.6333 , 74.0833
  99. 990 DATA BOISE, 43.6186 , 116.199 ,BOMBAY, 18.9333 ,-72.85
  100. 1000 DATA BOSTON, 42.3642 , 71.0056 ,BOWLING GREEN, 36.9947 , 86.4425
  101. 1010 DATA BRIDGEPORT, 41.1803 , 73.1894 ,BRISBANE,-27.5 ,-153
  102. 1020 DATA BRISTOL, 36.5833 , 82.2 ,BROCKTON, 42.0839 , 71.0236
  103. 1030 DATA BROWNSVILLE, 25.9019 , 97.4994 ,BRUSSELLS, 50.8333 ,-4.35
  104. 1040 DATA BUFFALO, 42.9406 , 78.7325 ,BURLINGTON VT, 44.4761 , 73.2128
  105. 1050 DATA BUTTE, 46.0183 , 112.536 ,CALCUTTA, 22.5833 ,-88.35
  106. 1060 DATA CAMBRIDGE, 42.3669 , 71.1061 ,CAMDEN, 39.9447 , 75.1206
  107. 1070 DATA CANBERRA,-35.3 ,-149.133 ,CANTON, 40.7972 , 81.3769
  108. 1080 DATA CARACAS, 10.5833 , 60.9333 ,CARSON CITY, 39.1667 , 119.767
  109. 1090 DATA CASABLANCA, 33.65 , 7.5833 ,CEDAR RAPIDS, 41.9669 , 91.6647
  110. 1100 DATA CEDAR RAPIDS, 41.8844 , 91.7086 ,CHAMPAIGN, 40.0397 , 88.2781
  111. 1110 DATA CHAMPAIGN, 40.118 , 88.2467 ,CHARLESTON SC, 32.8986 , 80.04
  112. 1120 DATA CHARLESTON WV, 38.3731 , 81.5933 ,CHARLOTTE, 35.2147 , 80.9383
  113. 1130 DATA CHATTANOOGA, 35.0447 , 85.3089 ,CHEYENNE, 41.1358 , 104.819
  114. 1140 DATA CHICAGO, 41.9825 , 87.9069 ,CINCINNATI, 39.0478 , 84.6667
  115. 1150 DATA CLARKSBURG, 39.2956 , 80.2289 ,CLEVELAND, 41.4103 , 81.8489
  116. 1160 DATA COLORADO SPRINGS, 38.8353 , 104.821 ,COLUMBIA, 34.0006 , 81.0333
  117. 1170 DATA COLUMBUS, 39.9947 , 82.8856 ,COLUMBUS GA, 32.4686 , 84.99
  118. 1180 DATA CONCORD, 43.2061 , 71.5403 ,CORPUS CHRISTI, 27.7975 , 97.3959
  119. 1190 DATA DAKAR, 14.6333 , 17.3333 ,DALLAS, 32.8967 , 97.0336
  120. 1200 DATA DAVENPORT, 41.5219 , 90.5758 ,DAYTON, 39.9011 , 84.22
  121. 1210 DATA DAYTONA BEACH, 29.2122 , 81.0194 ,DECATUR, 39.845 , 88.9464
  122. 1220 DATA DECATUR, 39.8342 , 88.8681 ,DENVER, 39.7742 , 104.878
  123. 1230 DATA DES MOINES, 41.4872 , 93.6167 ,DETROIT, 42.2153 , 83.3486
  124. 1240 DATA DODGE CITY, 37.7547 , 100.019 ,DUBLIN, 53.3333 , 6.25
  125. 1250 DATA DUBUQUE, 42.4986 , 90.6689 ,DULUTH, 46.7822 , 92.1067
  126. 1260 DATA DURHAM, 36 , 78.9125 ,EAU CLAIRE, 44.8086 , 91.4969
  127. 1270 DATA EL PASO, 31.78 , 106.486 ,ELIZABETH, 40.6619 , 74.2164
  128. 1280 DATA ELMIRA, 42.1595 , 76.8925 ,ENID, 36.3944 , 97.8764
  129. 1290 DATA EUGENE, 44.0544 , 123.092 ,EVANSVILLE, 37.9722 , 87.5725
  130. 1300 DATA FAIRBANKS, 64.8 , 147.85 ,FARGO, 46.875 , 96.7883
  131. 1310 DATA FLAGSTAFF, 35.1933 , 111.652 ,FLINT, 43.0139 , 83.6925
  132. 1320 DATA FRANKFURT, 50.1 ,-8.6833 ,FRESNO, 36.7367 , 119.786
  133. 1330 DATA FT. SMITH, 35.3861 , 94.4267 ,FT. WAYNE, 41.0725 , 85.1406
  134. 1340 DATA FT. WORTH, 32.7486 , 97.3289 ,GADSDEN, 34.0158 , 86.0114
  135. 1350 DATA GAINSVILLE, 29.6486 , 82.3219 ,GALLOP, 35.525 , 108.742
  136. 1360 DATA GALVESTON, 29.3028 , 94.7953 ,GARY, 41.6033 , 87.3386
  137. 1370 DATA GENOA, 44.4 ,-8.9333 ,GLASGOW, 55.8833 , 4.6833
  138. 1380 DATA GRAND JUNCTION, 39.0683 , 108.565 ,GRAND RAPIDS, 42.9675 , 85.6703
  139. 1390 DATA GREAT FALLS, 47.4925 , 111.306 ,GREEN BAY, 44.4106 , 88.0139
  140. 1400 DATA GREENSBORO, 36.0714 , 79.7903 ,GREENVILLE, 34.8964 , 82.2186
  141. 1410 DATA GUADALAJARA, 20.5 , 103.333 ,GUAYAQUIL,-2.5167 , 79.9
  142. 1420 DATA GULFPORT, 30.3678 , 89.0933 ,HALIFAX, 44.6442 , 63.5761
  143. 1430 DATA HARRISBURG, 40.2019 , 76.8831 ,HARTFORD, 41.7361 , 72.6506
  144. 1440 DATA HARTFORD, 41.77 , 72.6803 ,HELENA, 46.4925 , 112.04
  145. 1450 DATA HELSINKI, 60.1355 ,-25 ,HILO, 19.725 , 155.09
  146. 1460 DATA HOLYOKE, 42.2081 , 72.61 ,HONOLULU, 21.3061 , 157.86
  147. 1470 DATA HOUSTON, 29.9828 , 95.3458 ,HUNTINGTON, 38.3667 , 82.5581
  148. 1480 DATA HUNTINGTON, 38.42 , 82.4425 ,HUNTSVILLE, 34.7383 , 86.5886
  149. 1490 DATA INDIANAPOLIS, 39.7244 , 86.2833 ,ITHACA, 42.4903 , 76.4578
  150. 1500 DATA JACKSON MI, 42.2453 , 84.4061 ,JACKSON MS, 32.2989 , 90.185
  151. 1510 DATA JACKSONVILLE, 30.4925 , 81.69 ,JERSEY CITY, 40.7306 , 74.0656
  152. 1520 DATA JERUSALEM, 31.7833 ,-35.2167 ,JOHANNESBURG,-26.1667 ,-28.0333
  153. 1530 DATA JOPLIN, 37.0906 , 90.7031 ,JUNEAU, 58.3033 , 134.408
  154. 1540 DATA KANSAS CITY, 39.2992 , 94.7178 ,KNOXVILLE, 35.9608 , 83.9186
  155. 1550 DATA LAFAYETTE, 40.4197 , 86.8942 ,LANCASTER, 40.0403 , 76.3081
  156. 1560 DATA LANSING, 42.7336 , 84.5542 ,LAREDO, 27.5061 , 99.5083
  157. 1570 DATA LAS VEGAS, 36.08 , 115.152
  158. 1580 DATA LENINGRAD, 59.9167 ,-30.4167 ,LEXINGTON, 38.0367 , 84.6058
  159. 1590 DATA LIMA OH, 40.7431 , 84.1056 ,LIMA PERU,-12.1 , 77.05
  160. 1600 DATA LINCOLN, 40.8164 , 96.7042 ,LISBON, 38.7333 , 9.1333
  161. 1610 DATA LITTLE ROCK, 34.7303 , 92.2331 ,LIVERPOOL, 53.7167 , 1.6833
  162. 1620 DATA LONDON, 51.5 , 0 ,LONG BEACH, 33.7706 , 118.188
  163. 1630 DATA LOS ANGELES, 33.9419 , 118.406 ,LOUISVILLE, 38.1778 , 85.7364
  164. 1640 DATA LOWELL, 42.6403 , 71.3206 ,LUBBOCK, 33.5847 , 101.843
  165. 1650 DATA LUXEMBOURG, 49.6167 ,-6.1333 ,MACON, 32.8367 , 83.6267
  166. 1660 DATA MADISON, 43.0731 , 89.3819 ,MADISON, 43.1389 , 89.3375
  167. 1670 DATA MADRID, 40.4167 , 3.7167 ,MALAGA, 36.7167 , 4.4167
  168. 1680 DATA MARSHALL, 32.55 , 94.3833 ,MEMPHIS, 35.05 , 89.9789
  169. 1690 DATA MEXICO CITY, 19.4292 , 99.1167 ,MIAMI, 25.7944 , 80.2881
  170. 1700 DATA MILWAUKEE, 42.948 , 87.8964 ,MINNEAPOLIS, 44.8842 , 93.215
  171. 1710 DATA MINOT, 48.2358 , 101.294 ,MOBILE, 30.6933 , 88.0425
  172. 1720 DATA MOLINE, 41.4486 , 90.5081 ,MONTERREY, 25.6667 , 100.333
  173. 1730 DATA MONTGOMERY, 32.3758 , 86.3086 ,MONTIVIDEO,-17.55 , 51.1333
  174. 1740 DATA MONTPELIER, 44.26 , 72.5781 ,MONTREAL, 45.5083 , 73.5556
  175. 1750 DATA MOSCOW, 55.75 ,-37.7 ,NASHVILLE, 36.1267 , 86.6819
  176. 1760 DATA NASSAU, 25.0833 , 77.3333 ,NATCHEZ, 31.5633 , 91.3917
  177. 1770 DATA NEW BEDFORD, 42.6369 , 70.9281
  178. 1780 DATA NEW DELHI, 28.6333 ,-77.2 ,NEW HAVEN, 41.3069 , 72.925
  179. 1790 DATA NEW ORLEANS, 29.9928 , 90.2564 ,NEW YORK JFK, 40.6403 , 73.7783
  180. 1800 DATA NEW YORK LGA, 40.7772 , 73.8742 ,NEWARK, 40.6931 , 74.1686
  181. 1810 DATA NIAGARA FALLS, 43.0928 , 79.0572 ,NOME, 64.5 , 165.417
  182. 1820 DATA NORFOLK, 36.8953 , 76.2 ,OAKLAND, 37.8008 , 122.265
  183. 1830 DATA OGDEN, 41.2253 , 111.973 ,OKLAHOMA CITY, 35.3936 , 97.5997
  184. 1840 DATA OMAHA, 41.3011 , 95.885 ,ORLANDO, 28.4317 , 81.3247
  185. 1850 DATA OSLO, 59.9333 ,-10.75 ,OTTAWA, 45.4278 , 75.7125
  186. 1860 DATA PADUCAH, 37.0869 , 88.5989 ,PALERMO, 38.1333 ,-13.3833
  187. 1870 DATA PANAMA CITY FL, 30.1667 , 85.6833 ,PARIS, 48.8372 ,-2.3372
  188. 1880 DATA PASADENA, 34.1456 , 118.145 ,PEKING, 39.9 ,-116.467
  189. 1890 DATA PENSACOLA, 30.4142 , 87.2156 ,PEORIA, 40.6642 , 89.69
  190. 1900 DATA PERTH,-31.9667 ,-115.817 ,PHILADELPHIA, 39.8703 , 75.2453
  191. 1910 DATA PHOENIX, 33.4361 , 112.009 ,PIERRE, 44.3717 , 100.348
  192. 1920 DATA PITTSBURGH, 40.4936 , 80.2317 ,POCATELLO, 42.8606 , 112.45
  193. 1930 DATA PORT ARTHUR, 29.875 , 93.9375
  194. 1940 DATA PORTLAND ME, 43.6592 , 70.2553 ,PORTLAND OR, 45.5183 , 122.676
  195. 1950 DATA PRAGUE, 49.65 ,-13.8167 ,PROVIDENCE, 41.8256 , 71.4114
  196. 1960 DATA PROVO, 40.235 , 111.657 ,PUEBLO, 38.2714 , 104.609
  197. 1970 DATA QUEBEC, 46.8128 , 71.2056 ,QUITO,-.14 , 78.3
  198. 1980 DATA RACINE, 42.7303 , 87.7867 ,RALEIGH, 35.7772 , 78.6392
  199. 1990 DATA RAPID CITY, 44.0811 , 103.22 ,READING, 40.3358 , 75.9278
  200. 2000 DATA RENO, 39.5242 , 119.811
  201. 2010 DATA RICHMOND, 37.5375 , 77.4358 ,RIO DE JANEIRO,-22.8953 , 43.2228
  202. 2020 DATA ROANOKE, 37.2703 , 79.9456 ,ROCHESTER NY, 43.1189 , 77.6728
  203. 2030 DATA ROCKFORD, 42.2686 , 89.0967 ,ROME, 41.8833 ,-12.5
  204. 2040 DATA SACREMENTO, 38.5825 , 121.495 ,SAGINAW, 43.4311 , 83.9347
  205. 2050 DATA SALEM OR, 44.94 , 123.033 ,SALINA, 38.8433 , 97.6128
  206. 2060 DATA SALT LAKE CITY, 40.7842 , 111.967 ,SAN ANGELO, 31.4608 , 100.434
  207. 2070 DATA SAN ANTONIO, 29.5333 , 98.4697 ,SAN BERNADINO, 34.1083 , 117.291
  208. 2080 DATA SAN DIEGO, 32.7336 , 117.187 ,SAN FRANCISCO, 37.6194 , 122.374
  209. 2090 DATA SAN JOSE, 37.3614 , 121.927 ,SAN JUAN, 18.4414 , 66.0022
  210. 2100 DATA SAN SALVADOR, 13.6667 , 89.1667 ,SANTA BARBABRA, 34.4217 , 119.699
  211. 2110 DATA SANTA FE, 35.6864 , 105.936 ,SANTIAGO,-33.5 , 70.4
  212. 2120 DATA SAO PAULA,-23.55 , 46.65 ,SARASOTA, 27.3347 , 82.5417
  213. 2130 DATA SAVANNAH, 32.0783 , 81.0936 ,SCHENECTADY, 42.8117 , 73.9283
  214. 2140 DATA SCRANTON, 41.4089 , 75.6628 ,SEATTLE, 47.4492 , 122.308
  215. 2150 DATA SHANGHAI, 31.2167 ,-121.417 ,SHEBOYGAN, 43.7628 , 87.7144
  216. 2160 DATA SHERIDAN, 44.7986 , 106.953 ,SHREVEPORT, 32.5128 , 93.7494
  217. 2170 DATA SINGAPORE, 1.3333 ,-103.833 ,SIOUX CITY, 42.4961 , 96.075
  218. 2180 DATA SIOUX FALLS, 43.5431 , 96.7264 ,SOUTH BEND, 41.6758 , 86.2503
  219. 2190 DATA SPARTANBURG, 34.9508 , 81.935 ,SPOKANE, 47.6589 , 117.426
  220. 2200 DATA SPRINGFIELD, 39.8433 , 89.6678 ,ST. JOSEPH, 39.7658 , 94.8506
  221. 2210 DATA ST. LOUIS, 38.7481 , 90.3622 ,ST. PAUL, 44.9553 , 93.1019
  222. 2220 DATA PETERSBURG, 27.7717 , 82.6386 ,STANFORD, 41.0525 , 73.54
  223. 2230 DATA STOCKHOLM, 59.3333 ,-18.95 ,STOCKTON, 37.9583 , 121.288
  224. 2240 DATA SYDNEY,-33.8667 ,-151.2
  225. 2250 DATA SYRACUSE, 43.1122 , 76.1089 ,TACOMA, 47.2497 , 122.438
  226. 2260 DATA TALLAHASSEE, 30.4417 , 84.2822 ,TAMPA, 27.9739 , 82.5328
  227. 2270 DATA TEHERAN, 35.6667 ,-51.4333 ,TEL AVIV, 32.0833 ,-34.7667
  228. 2280 DATA TENERIFE, 28.25 , 16.588 ,TERRE HAUTE, 39.4675 , 87.4072
  229. 2290 DATA TEXARKANA, 33.43 , 94.0417 ,TOKYO, 35.75 ,-139.75
  230. 2300 DATA TOLEDO, 41.6539 , 83.5442 ,TOPEKA, 39.0544 , 95.6731
  231. 2310 DATA TORONTO, 43.6533 , 79.3833 ,TRENTON, 40.2206 , 74.7703
  232. 2320 DATA TUCSON, 32.2208 , 110.969 ,TULSA, 36.1986 , 95.8878
  233. 2330 DATA UTICA, 43.1033 , 75.2258 ,VANCOUVER, 49.275 , 123.125
  234. 2340 DATA VICTORIA, 48.4278 , 123.363 ,WACO, 31.5533 , 97.1333
  235. 2350 DATA WARSAW, 52.25 ,-21 ,WASHINGTON, 38.9436 , 77.4544
  236. 2360 DATA WATERLOO, 42.4944 , 92.3389 ,WEST PALM BEACH, 26.71 , 80.0519
  237. 2370 DATA WHEELING, 40.0675 , 80.7222 ,WHITE PLAINS, 41.0333 , 73.7633
  238. 2380 DATA WHITEHORSE, 60.7208 , 136.054 ,WICHITA, 37.6517 , 97.4308
  239. 2390 DATA WICHITA FALLS, 33.9094 , 98.4911 ,WILKESBARRE, 41.2422 , 75.8881
  240. 2400 DATA WILMINGTON DE, 39.7461 , 75.5475 ,WILMINGTON NC, 34.2372 , 77.9494
  241. 2410 DATA WINDSOR, 42.3306 , 83.05 ,WINNIPEG, 49.8989 , 97.1389
  242. 2420 DATA WINSTON-SALEM, 36.0978 , 80.245 ,WORCESTER, 42.2603 , 71.8047
  243. 2430 DATA YAKIMA, 46.6025 , 120.511 ,YONKERS, 40.9319 , 73.8983
  244. 2440 DATA YORK, 39.9597 , 87.7267 ,YOUNGSTOWN, 41.0992 , 80.6506
  245. 2450 DATA YUMA, 32.715 , 114.623 ,ZANESVILLE, 39.9383 , 82.0083
  246. 2460 DATA ZURICH, 47.3833 ,-8.55
  247. 2470 'Norman Goldsmith
  248. 2480 '5 Ranger Road
  249. 2490 '7/5/87
  250. 2500 REM ---------------------------------------------------------
  251. 2510 REM Updates for bwBASIC 3.0 by Howard Wulf, AF5NE, May 7th 2015:
  252. 2520 REM a) added semicolons between print items on line 500
  253. 2599 END