## File: gb_miles.w

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 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403 % This file is part of the Stanford GraphBase (c) Stanford University 1993 @i boilerplate.w %<< legal stuff: PLEASE READ IT BEFORE MAKING ANY CHANGES! @i gb_types.w \def\title{GB\_\,MILES} \prerequisites{GB\_\,GRAPH}{GB\_\,IO} @* Introduction. This GraphBase module contains the |miles| subroutine, which creates a family of undirected graphs based on highway mileage data between North American cities. Examples of the use of this procedure can be found in the demo programs {\sc MILES\_\,SPAN} and {\sc GB\_\,PLANE}. @(gb_miles.h@>= extern Graph *miles(); @ The subroutine call {\advance\thinmuskip 0mu plus 4mu |miles(n,north_weight,west_weight,pop_weight,max_distance,max_degree,seed)|} constructs a graph based on the information in \.{miles.dat}. Each vertex of the graph corresponds to one of the 128 cities whose name is alphabetically greater than or equal to Ravenna, Ohio' in the 1949 edition of Rand McNally {\char\&} Company's {\sl Standard Highway Mileage Guide}. Edges between vertices are assigned lengths representing distances between cities, in miles. In most cases these mileages come from the Rand McNally Guide, but several dozen entries needed to be changed drastically because they were obviously too large or too small; in such cases an educated guess was made. Furthermore, about 5\% of the entries were adjusted slightly in order to ensure that all distances satisfy the triangle inequality'': The graph generated by |miles| has the property that the distance from |u| to~|v| plus the distance from |v| to~|w| always exceeds or equals the distance from |u| to~|w|. The constructed graph will have $\min(n,128)$ vertices; the default value |n=128| is substituted if |n=0|. If |n| is less than 128, the |n| cities will be selected by assigning a weight to each city and choosing the |n| with largest weight, using random numbers to break ties in case of equal weights. Weights are computed by the formula $$|north_weight|\cdot|lat|+|west_weight|\cdot|lon|+|pop_weight|\cdot|pop|,$$ where |lat| is latitude north of the equator, |lon| is longitude west of Greenwich, and |pop| is the population in 1980. Both |lat| and |lon| are given in centidegrees'' (hundredths of degrees). For example, San Francisco has |lat=3778|, |lon=12242|, and |pop=678974|; this means that, before the recent earthquake, it was located at $37.78^\circ$ north latitude and $122.42^\circ$ west longitude, and that it had 678,974 residents in the 1980 census. The weight parameters must satisfy $$\vert|north_weight|\vert\le100{,}000,\quad \vert|west_weight|\vert\le100{,}000,\quad \vert|pop_weight|\vert\le100.$$ The constructed graph will be complete''---that is, it will have edges between every pair of vertices---unless special values are given to the parameters |max_distance| or |max_degree|. If |max_distance!=0|, edges with more than |max_distance| miles will not appear; if |max_degree!=0|, each vertex will be limited to at most |max_degree| of its shortest edges. Vertices of the graph will appear in order of decreasing weight. The |seed| parameter defines the pseudo-random numbers used wherever a random'' choice between equal-weight vertices or equal-length edges needs to be made. @d MAX_N 128 @(gb_miles.h@>= #define MAX_N 128 /* maximum and default number of cities */ @ Examples: The call |miles(100,0,0,1,0,0,0)| will construct a complete graph on 100 vertices, representing the 100 most populous cities in the database. It turns out that San Diego, with a population of 875,538, is the winning city by this criterion, followed by San Antonio (population 786,023), San Francisco (678,974), and Washington D.C. (638,432). To get |n| cities in the western United States and Canada, you can say $|miles|(n,0,1,0,\ldots\,)$; to get |n| cities in the Northeast, use a call like $|miles|(n,1,-1,0,\ldots\,)$. A parameter setting like $(50,-500,0,1,\ldots\,)$ produces mostly Southern cities, except for a few large metropolises in the north. If you ask for |miles(n,a,b,c,0,1,0)|, you get an edge between cities if and only if each city is the nearest to the other, among the |n| cities selected. (The graph is always undirected: There is an arc from |u| to~|v| if and only if there's an arc of the same length from |v| to~|u|.) A random selection of cities can be obtained by calling |miles(n,0,0,0,m,d,s)|. Different choices of the seed number |s| will produce different selections, in a system-independent manner; identical results will be obtained on all computers when identical parameters have been specified. Equivalent experiments on algorithms for graph manipulation can therefore be performed by researchers in different parts of the world. Any value of |s| between 0 and $2^{31}-1$ is permissible. @ If the |miles| routine encounters a problem, it returns |NULL| (\.{NULL}), after putting a code number into the external variable |panic_code|. This code number identifies the type of failure. Otherwise |miles| returns a pointer to the newly created graph, which will be represented with the data structures explained in {\sc GB\_\,GRAPH}. (The external variable |panic_code| is itself defined in {\sc GB\_\,GRAPH}.) @d panic(c) @+{@+panic_code=c;@+gb_trouble_code=0;@+return NULL;@+} @ The \CEE/ file \.{gb\_miles.c} has the following overall shape: @p #include "gb_io.h" /* we will use the {\sc GB\_\,IO} routines for input */ #include "gb_flip.h" /* we will use the {\sc GB\_\,FLIP} routines for random numbers */ #include "gb_graph.h" /* we will use the {\sc GB\_\,GRAPH} data structures */ #include "gb_sort.h" /* and the linksort routine */ @h@# @@; @@; @# Graph *miles(n,north_weight,west_weight,pop_weight, max_distance,max_degree,seed) unsigned long n; /* number of vertices desired */ long north_weight; /* coefficient of latitude in the weight function */ long west_weight; /* coefficient of longitude in the weight function */ long pop_weight; /* coefficient of population in the weight function */ unsigned long max_distance; /* maximum distance in an edge, if nonzero */ unsigned long max_degree; /* maximum number of edges per vertex, if nonzero */ long seed; /* random number seed */ {@+@@;@# gb_init_rand(seed); @; @; @; @; @; if (gb_trouble_code) { gb_recycle(new_graph); panic(alloc_fault); /* oops, we ran out of memory somewhere back there */ } return new_graph; } @ @= Graph *new_graph; /* the graph constructed by |miles| */ register long j,k; /* all-purpose indices */ @ @= if (n==0 || n>MAX_N) n=MAX_N; if (max_degree==0 || max_degree>=n) max_degree=n-1; if (north_weight>100000 || west_weight>100000 || pop_weight>100 @| || north_weight<-100000 || west_weight<-100000 || pop_weight<-100) panic(bad_specs); /* the magnitude of at least one weight is too big */ @ @= new_graph=gb_new_graph(n); if (new_graph==NULL) panic(no_room); /* out of memory before we're even started */ sprintf(new_graph->id,"miles(%lu,%ld,%ld,%ld,%lu,%lu,%ld)", n,north_weight,west_weight,pop_weight,max_distance,max_degree,seed); strcpy(new_graph->util_types,"ZZIIIIZZZZZZZZ"); @* Vertices. As we read in the data, we construct a list of nodes, each of which contains a city's name, latitude, longitude, population, and weight. These nodes conform to the specifications stipulated in the {\sc GB\_\,SORT} module. After the list has been sorted by weight, the top |n| entries will be the vertices of the new graph. @= typedef struct node_struct { /* records to be sorted by |gb_linksort| */ long key; /* the nonnegative sort key (weight plus $2^{30}$) */ struct node_struct *link; /* pointer to next record */ long kk; /* index of city in the original database */ long lat,lon,pop; /* latitude, longitude, population */ char name[30]; /* |"City Name, ST"| */ } node; @ The constants defined here are taken from the specific data in \.{miles.dat}, because this routine is not intended to be perfectly general. @= static long min_lat=2672, max_lat=5042, min_lon=7180, max_lon=12312, min_pop=2521, max_pop=875538; /* tight bounds on data entries */ static node *node_block; /* array of nodes holding city info */ static long *distance; /* array of distances */ @ The data in \.{miles.dat} appears in 128 groups of lines, one for each city, in reverse alphabetical order. These groups have the general form \vcenter{\halign{\tt#\hfil\cr City Name, ST[lat,lon]pop\cr d1 d2 d3 d4 d5 d6 ... (possibly several lines' worth)\cr }} where \.{City Name} is the name of the city (possibly including spaces); \.{ST} is the two-letter state code; \.{lat} and \.{lon} are latitude and longitude in hundredths of degrees; \.{pop} is the population; and the remaining numbers \.{d1}, \.{d2}, \dots\ are distances to the previously named cities in reverse order. Each distance is separated from the previous item by either a blank space or a newline character. For example, the line $$\hbox{\tt San Francisco, CA[3778,12242]678974}$$ specifies the data about San Francisco that was mentioned earlier. From the first few groups \vcenter{\halign{\tt#\hfil\cr Youngstown, OH[4110,8065]115436\cr Yankton, SD[4288,9739]12011\cr 966\cr Yakima, WA[4660,12051]49826\cr 1513 2410\cr Worcester, MA[4227,7180]161799\cr 2964 1520 604\cr }} we learn that the distance from Worcester, Massachusetts, to Yakima, Washington, is 2964 miles; from Worcester to Youngstown it is 604 miles. The following two-letter state codes'' are used for Canadian provinces: $\.{BC}=\null$British Columbia, $\.{MB}=\null$Manitoba, $\.{ON}=\null$Ontario, $\.{SK}=\null$Saskatchewan. @= node_block=gb_typed_alloc(MAX_N,node,new_graph->aux_data); distance=gb_typed_alloc(MAX_N*MAX_N,long,new_graph->aux_data); if (gb_trouble_code) { gb_free(new_graph->aux_data); panic(no_room+1); /* no room to copy the data */ } if (gb_open("miles.dat")!=0) panic(early_data_fault); /* couldn't open |"miles.dat"| using GraphBase conventions; |io_errors| tells why */ for (k=MAX_N-1; k>=0; k--) @; if (gb_close()!=0) panic(late_data_fault); /* something's wrong with |"miles.dat"|; see |io_errors| */ @ The bounds we've imposed on |north_weight|, |west_weight|, and |pop_weight| guarantee that the key value computed here will be between 0 and~$2^{31}$. @= {@+register node *p; p=node_block+k; p->kk=k; if (k) p->link=p-1; gb_string(p->name,'['); if (gb_char()!='[') panic(syntax_error); /* out of sync in \.{miles.dat} */ p->lat=gb_number(10); if (p->latlat>max_lat || gb_char()!=',') panic(syntax_error+1); /* latitude data was clobbered */ p->lon=gb_number(10); if (p->lonlon>max_lon || gb_char()!=']') panic(syntax_error+2); /* longitude data was clobbered */ p->pop=gb_number(10); if (p->poppop>max_pop) panic(syntax_error+3); /* population data was clobbered */ p->key=north_weight*(p->lat-min_lat) +west_weight*(p->lon-min_lon) +pop_weight*(p->pop-min_pop)+0x40000000; @; gb_newline(); } @ @d d(j,k) *(distance+(MAX_N*j+k)) @= { for (j=k+1; j= {@+register node *p; /* the current node being considered */ register Vertex *v=new_graph->vertices; /* the first unfilled vertex */ gb_linksort(node_block+MAX_N-1); for (j=127; j>=0; j--) for (p=(node*)gb_sorted[j]; p; p=p->link) { if (vvertices+n) @kk| to the graph@>@; else p->pop=0; /* this city is not being used */ } } @ Utility fields |x| and |y| for each vertex are set to coordinates that can be used in geometric computations; these coordinates are obtained by simple linear transformations of latitude and longitude (not by any kind of sophisticated polyconic projection). We will have $$0\le x\le5132, \qquad 0\le y\le 3555.$$ Utility field~|z| is set to the city's index number (0 to 127) in the original database. Utility field~|w| is set to the city's population. The coordinates computed here are compatible with those in the \TEX/ file \.{cities.texmap}. Users might want to incorporate edited copies of that file into documents that display results obtained with |miles| graphs. @.cities.texmap@> @d x_coord x.I @d y_coord y.I @d index_no z.I @d people w.I @kk| to the graph@>= { v->x_coord=max_lon-p->lon; /* |x| coordinate is complement of longitude */ v->y_coord=p->lat-min_lat; v->y_coord+=(v->y_coord)>>1; /* |y| coordinate is 1.5 times latitude */ v->index_no=p->kk; v->people=p->pop; v->name=gb_save_string(p->name); v++; } @ @(gb_miles.h@>= #define x_coord @t\quad@> x.I /* utility field definitions for the header file */ #define y_coord @t\quad@> y.I #define index_no @t\quad@> z.I #define people @t\quad@> w.I @* Arcs. We make the distance negative in the matrix entry for an arc that is not to be included. Nothing needs to be done in this regard unless the user has specified a maximum degree or a maximum edge length. @= if (max_distance>0 || max_degree>0) @; {@+register Vertex *u,*v; for (u=new_graph->vertices;uvertices+n;u++) { j=u->index_no; for (v=u+1;vvertices+n;v++) { k=v->index_no; if (d(j,k)>0 && d(k,j)>0) gb_new_edge(u,v,d(j,k)); } } } @ @= {@+register node *p; if (max_degree==0) max_degree=MAX_N; if (max_distance==0) max_distance=30000; for (p=node_block; ppop) { /* this city not deleted */ k=p->kk; @; } } @ Here we reuse the key fields of the nodes, storing complementary distances there instead of weights. We also let the sorting routine change the link fields. The other fields, however---especially |pop|---remain unchanged. Yes, the author knows this is a wee bit tricky, but why~not? @= {@+register node *q; register node*s=NULL; /* list of nodes containing edges from city |k| */ for (q=node_block; qpop && q!=p) { /* another city not deleted */ j=d(k,q->kk); /* distance from |p| to |q| */ if (j>max_distance) d(k,q->kk)=-j; else { q->key=max_distance-j; q->link=s; s=q; } } gb_linksort(s); /* now all the surviving edges from |p| are in the list |gb_sorted[0]| */ j=0; /* |j| counts how many edges have been accepted */ for (q=(node*)gb_sorted[0]; q; q=q->link) if (++j>max_degree) d(k,q->kk)=-d(k,q->kk); } @ Random access to the distance matrix is provided to users via the external function |miles_distance|. Caution: This function can be used only with the graph most recently made by |miles|, and only when the graph's |aux_data| has not been recycled, and only when the |z| utility fields have not been used for another purpose. The result might be negative when an edge has been suppressed. Moreover, we can in fact have |miles_distance(u,v)<0| when |miles_distance(v,u)>0|, if the distance in question was suppressed by the |max_degree| constraint on~|u| but not on~|v|. @p long miles_distance(u,v) Vertex *u,*v; { return d(u->index_no,v->index_no); } @ @(gb_miles.h@>= extern long miles_distance(); @* Index. As usual, we close with an index that shows where the identifiers of \\{gb\_miles} are defined and used.