[175] | 1 | #include "bltInt.h"
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| 2 |
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| 3 | typedef double TriDiagonalMatrix[3];
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| 4 | typedef struct {
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| 5 | double b, c, d;
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| 6 | } Cubic2D;
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| 7 |
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| 8 | typedef struct {
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| 9 | double b, c, d, e, f;
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| 10 | } Quint2D;
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| 11 |
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| 12 | /*
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| 13 | * Quadratic spline parameters
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| 14 | */
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| 15 | #define E1 param[0]
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| 16 | #define E2 param[1]
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| 17 | #define V1 param[2]
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| 18 | #define V2 param[3]
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| 19 | #define W1 param[4]
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| 20 | #define W2 param[5]
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| 21 | #define Z1 param[6]
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| 22 | #define Z2 param[7]
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| 23 | #define Y1 param[8]
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| 24 | #define Y2 param[9]
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| 25 |
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| 26 | static Tcl_CmdProc SplineCmd;
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| 27 |
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| 28 | /*
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| 29 | * -----------------------------------------------------------------------
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| 30 | *
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| 31 | * Search --
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| 32 | *
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| 33 | * Conducts a binary search for a value. This routine is called
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| 34 | * only if key is between x(0) and x(len - 1).
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| 35 | *
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| 36 | * Results:
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| 37 | * Returns the index of the largest value in xtab for which
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| 38 | * x[i] < key.
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| 39 | *
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| 40 | * -----------------------------------------------------------------------
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| 41 | */
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| 42 | static int
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| 43 | Search(points, nPoints, key, foundPtr)
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| 44 | Point2D points[]; /* Contains the abscissas of the data
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| 45 | * points of interpolation. */
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| 46 | int nPoints; /* Dimension of x. */
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| 47 | double key; /* Value whose relative position in
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| 48 | * x is to be located. */
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| 49 | int *foundPtr; /* (out) Returns 1 if s is found in
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| 50 | * x and 0 otherwise. */
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| 51 | {
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| 52 | int high, low, mid;
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| 53 |
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| 54 | low = 0;
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| 55 | high = nPoints - 1;
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| 56 |
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| 57 | while (high >= low) {
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| 58 | mid = (high + low) / 2;
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| 59 | if (key > points[mid].x) {
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| 60 | low = mid + 1;
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| 61 | } else if (key < points[mid].x) {
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| 62 | high = mid - 1;
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| 63 | } else {
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| 64 | *foundPtr = 1;
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| 65 | return mid;
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| 66 | }
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| 67 | }
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| 68 | *foundPtr = 0;
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| 69 | return low;
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| 70 | }
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| 71 |
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| 72 | /*
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| 73 | *-----------------------------------------------------------------------
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| 74 | *
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| 75 | * QuadChoose --
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| 76 | *
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| 77 | * Determines the case needed for the computation of the parame-
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| 78 | * ters of the quadratic spline.
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| 79 | *
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| 80 | * Results:
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| 81 | * Returns a case number (1-4) which controls how the parameters
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| 82 | * of the quadratic spline are evaluated.
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| 83 | *
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| 84 | *-----------------------------------------------------------------------
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| 85 | */
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| 86 | static int
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| 87 | QuadChoose(p, q, m1, m2, epsilon)
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| 88 | Point2D *p; /* Coordinates of one of the points of
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| 89 | * interpolation */
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| 90 | Point2D *q; /* Coordinates of one of the points of
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| 91 | * interpolation */
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| 92 | double m1; /* Derivative condition at point P */
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| 93 | double m2; /* Derivative condition at point Q */
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| 94 | double epsilon; /* Error tolerance used to distinguish
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| 95 | * cases when m1 or m2 is relatively
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| 96 | * close to the slope or twice the
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| 97 | * slope of the line segment joining
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| 98 | * the points P and Q. If
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| 99 | * epsilon is not 0.0, then epsilon
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| 100 | * should be greater than or equal to
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| 101 | * machine epsilon. */
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| 102 | {
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| 103 | double slope;
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| 104 |
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| 105 | /* Calculate the slope of the line joining P and Q. */
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| 106 | slope = (q->y - p->y) / (q->x - p->x);
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| 107 |
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| 108 | if (slope != 0.0) {
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| 109 | double relerr;
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| 110 | double mref, mref1, mref2, prod1, prod2;
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| 111 |
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| 112 | prod1 = slope * m1;
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| 113 | prod2 = slope * m2;
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| 114 |
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| 115 | /* Find the absolute values of the slopes slope, m1, and m2. */
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| 116 | mref = FABS(slope);
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| 117 | mref1 = FABS(m1);
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| 118 | mref2 = FABS(m2);
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| 119 |
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| 120 | /*
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| 121 | * If the relative deviation of m1 or m2 from slope is less than
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| 122 | * epsilon, then choose case 2 or case 3.
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| 123 | */
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| 124 | relerr = epsilon * mref;
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| 125 | if ((FABS(slope - m1) > relerr) && (FABS(slope - m2) > relerr) &&
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| 126 | (prod1 >= 0.0) && (prod2 >= 0.0)) {
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| 127 | double prod;
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| 128 |
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| 129 | prod = (mref - mref1) * (mref - mref2);
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| 130 | if (prod < 0.0) {
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| 131 | /*
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| 132 | * l1, the line through (x1,y1) with slope m1, and l2,
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| 133 | * the line through (x2,y2) with slope m2, intersect
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| 134 | * at a point whose abscissa is between x1 and x2.
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| 135 | * The abscissa becomes a knot of the spline.
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| 136 | */
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| 137 | return 1;
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| 138 | }
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| 139 | if (mref1 > (mref * 2.0)) {
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| 140 | if (mref2 <= ((2.0 - epsilon) * mref)) {
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| 141 | return 3;
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| 142 | }
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| 143 | } else if (mref2 <= (mref * 2.0)) {
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| 144 | /*
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| 145 | * Both l1 and l2 cross the line through
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| 146 | * (x1+x2)/2.0,y1 and (x1+x2)/2.0,y2, which is the
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| 147 | * midline of the rectangle formed by P and Q or both
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| 148 | * m1 and m2 have signs different than the sign of
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| 149 | * slope, or one of m1 and m2 has opposite sign from
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| 150 | * slope and l1 and l2 intersect to the left of x1 or
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| 151 | * to the right of x2. The point (x1+x2)/2. is a knot
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| 152 | * of the spline.
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| 153 | */
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| 154 | return 2;
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| 155 | } else if (mref1 <= ((2.0 - epsilon) * mref)) {
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| 156 | /*
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| 157 | * In cases 3 and 4, sign(m1)=sign(m2)=sign(slope).
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| 158 | * Either l1 or l2 crosses the midline, but not both.
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| 159 | * Choose case 4 if mref1 is greater than
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| 160 | * (2.-epsilon)*mref; otherwise, choose case 3.
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| 161 | */
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| 162 | return 3;
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| 163 | }
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| 164 | /*
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| 165 | * If neither l1 nor l2 crosses the midline, the spline
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| 166 | * requires two knots between x1 and x2.
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| 167 | */
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| 168 | return 4;
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| 169 | } else {
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| 170 | /*
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| 171 | * The sign of at least one of the slopes m1 or m2 does not
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| 172 | * agree with the sign of *slope*.
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| 173 | */
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| 174 | if ((prod1 < 0.0) && (prod2 < 0.0)) {
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| 175 | return 2;
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| 176 | } else if (prod1 < 0.0) {
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| 177 | if (mref2 > ((epsilon + 1.0) * mref)) {
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| 178 | return 1;
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| 179 | } else {
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| 180 | return 2;
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| 181 | }
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| 182 | } else if (mref1 > ((epsilon + 1.0) * mref)) {
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| 183 | return 1;
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| 184 | } else {
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| 185 | return 2;
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| 186 | }
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| 187 | }
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| 188 | } else if ((m1 * m2) >= 0.0) {
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| 189 | return 2;
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| 190 | } else {
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| 191 | return 1;
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| 192 | }
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| 193 | }
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| 194 |
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| 195 | /*
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| 196 | * -----------------------------------------------------------------------
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| 197 | *
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| 198 | * QuadCases --
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| 199 | *
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| 200 | * Computes the knots and other parameters of the spline on the
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| 201 | * interval PQ.
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| 202 | *
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| 203 | *
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| 204 | * On input--
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| 205 | *
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| 206 | * P and Q are the coordinates of the points of interpolation.
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| 207 | *
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| 208 | * m1 is the slope at P.
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| 209 | *
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| 210 | * m2 is the slope at Q.
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| 211 | *
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| 212 | * ncase controls the number and location of the knots.
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| 213 | *
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| 214 | *
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| 215 | * On output--
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| 216 | *
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| 217 | * (v1,v2),(w1,w2),(z1,z2), and (e1,e2) are the coordinates of
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| 218 | * the knots and other parameters of the spline on P.
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| 219 | * (e1,e2) and Q are used only if ncase=4.
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| 220 | *
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| 221 | * -----------------------------------------------------------------------
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| 222 | */
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| 223 | static void
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| 224 | QuadCases(p, q, m1, m2, param, which)
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| 225 | Point2D *p, *q;
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| 226 | double m1, m2;
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| 227 | double param[];
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| 228 | int which;
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| 229 | {
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| 230 | if ((which == 3) || (which == 4)) { /* Parameters used in both 3 and 4 */
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| 231 | double mbar1, mbar2, mbar3, c1, d1, h1, j1, k1;
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| 232 |
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| 233 | c1 = p->x + (q->y - p->y) / m1;
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| 234 | d1 = q->x + (p->y - q->y) / m2;
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| 235 | h1 = c1 * 2.0 - p->x;
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| 236 | j1 = d1 * 2.0 - q->x;
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| 237 | mbar1 = (q->y - p->y) / (h1 - p->x);
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| 238 | mbar2 = (p->y - q->y) / (j1 - q->x);
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| 239 |
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| 240 | if (which == 4) { /* Case 4. */
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| 241 | Y1 = (p->x + c1) / 2.0;
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| 242 | V1 = (p->x + Y1) / 2.0;
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| 243 | V2 = m1 * (V1 - p->x) + p->y;
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| 244 | Z1 = (d1 + q->x) / 2.0;
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| 245 | W1 = (q->x + Z1) / 2.0;
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| 246 | W2 = m2 * (W1 - q->x) + q->y;
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| 247 | mbar3 = (W2 - V2) / (W1 - V1);
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| 248 | Y2 = mbar3 * (Y1 - V1) + V2;
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| 249 | Z2 = mbar3 * (Z1 - V1) + V2;
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| 250 | E1 = (Y1 + Z1) / 2.0;
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| 251 | E2 = mbar3 * (E1 - V1) + V2;
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| 252 | } else { /* Case 3. */
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| 253 | k1 = (p->y - q->y + q->x * mbar2 - p->x * mbar1) / (mbar2 - mbar1);
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| 254 | if (FABS(m1) > FABS(m2)) {
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| 255 | Z1 = (k1 + p->x) / 2.0;
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| 256 | } else {
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| 257 | Z1 = (k1 + q->x) / 2.0;
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| 258 | }
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| 259 | V1 = (p->x + Z1) / 2.0;
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| 260 | V2 = p->y + m1 * (V1 - p->x);
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| 261 | W1 = (q->x + Z1) / 2.0;
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| 262 | W2 = q->y + m2 * (W1 - q->x);
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| 263 | Z2 = V2 + (W2 - V2) / (W1 - V1) * (Z1 - V1);
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| 264 | }
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| 265 | } else if (which == 2) { /* Case 2. */
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| 266 | Z1 = (p->x + q->x) / 2.0;
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| 267 | V1 = (p->x + Z1) / 2.0;
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| 268 | V2 = p->y + m1 * (V1 - p->x);
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| 269 | W1 = (Z1 + q->x) / 2.0;
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| 270 | W2 = q->y + m2 * (W1 - q->x);
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| 271 | Z2 = (V2 + W2) / 2.0;
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| 272 | } else { /* Case 1. */
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| 273 | double ztwo;
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| 274 |
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| 275 | Z1 = (p->y - q->y + m2 * q->x - m1 * p->x) / (m2 - m1);
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| 276 | ztwo = p->y + m1 * (Z1 - p->x);
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| 277 | V1 = (p->x + Z1) / 2.0;
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| 278 | V2 = (p->y + ztwo) / 2.0;
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| 279 | W1 = (Z1 + q->x) / 2.0;
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| 280 | W2 = (ztwo + q->y) / 2.0;
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| 281 | Z2 = V2 + (W2 - V2) / (W1 - V1) * (Z1 - V1);
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| 282 | }
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| 283 | }
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| 284 |
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| 285 | static int
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| 286 | QuadSelect(p, q, m1, m2, epsilon, param)
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| 287 | Point2D *p, *q;
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| 288 | double m1, m2;
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| 289 | double epsilon;
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| 290 | double param[];
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| 291 | {
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| 292 | int ncase;
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| 293 |
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| 294 | ncase = QuadChoose(p, q, m1, m2, epsilon);
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| 295 | QuadCases(p, q, m1, m2, param, ncase);
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| 296 | return ncase;
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| 297 | }
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| 298 |
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| 299 | /*
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| 300 | * -----------------------------------------------------------------------
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| 301 | *
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| 302 | * QuadGetImage --
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| 303 | *
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| 304 | * -----------------------------------------------------------------------
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| 305 | */
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| 306 | INLINE static double
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| 307 | QuadGetImage(p1, p2, p3, x1, x2, x3)
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| 308 | double p1, p2, p3;
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| 309 | double x1, x2, x3;
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| 310 | {
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| 311 | double A, B, C;
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| 312 | double y;
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| 313 |
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| 314 | A = x1 - x2;
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| 315 | B = x2 - x3;
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| 316 | C = x1 - x3;
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| 317 |
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| 318 | y = (p1 * (A * A) + p2 * 2.0 * B * A + p3 * (B * B)) / (C * C);
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| 319 | return y;
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| 320 | }
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| 321 |
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| 322 | /*
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| 323 | * -----------------------------------------------------------------------
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| 324 | *
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| 325 | * QuadSpline --
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| 326 | *
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| 327 | * Finds the image of a point in x.
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| 328 | *
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| 329 | * On input
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| 330 | *
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| 331 | * x Contains the value at which the spline is evaluated.
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| 332 | * leftX, leftY
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| 333 | * Coordinates of the left-hand data point used in the
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| 334 | * evaluation of x values.
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| 335 | * rightX, rightY
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| 336 | * Coordinates of the right-hand data point used in the
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| 337 | * evaluation of x values.
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| 338 | * Z1, Z2, Y1, Y2, E2, W2, V2
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| 339 | * Parameters of the spline.
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| 340 | * ncase Controls the evaluation of the spline by indicating
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| 341 | * whether one or two knots were placed in the interval
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| 342 | * (xtabs,xtabs1).
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| 343 | *
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| 344 | * Results:
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| 345 | * The image of the spline at x.
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| 346 | *
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| 347 | * -----------------------------------------------------------------------
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| 348 | */
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| 349 | static void
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| 350 | QuadSpline(intp, left, right, param, ncase)
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| 351 | Point2D *intp; /* Value at which spline is evaluated */
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| 352 | Point2D *left; /* Point to the left of the data point to
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| 353 | * be evaluated */
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| 354 | Point2D *right; /* Point to the right of the data point to
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| 355 | * be evaluated */
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| 356 | double param[]; /* Parameters of the spline */
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| 357 | int ncase; /* Controls the evaluation of the
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| 358 | * spline by indicating whether one or
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| 359 | * two knots were placed in the
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| 360 | * interval (leftX,rightX) */
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| 361 | {
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| 362 | double y;
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| 363 |
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| 364 | if (ncase == 4) {
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| 365 | /*
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| 366 | * Case 4: More than one knot was placed in the interval.
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| 367 | */
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| 368 |
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| 369 | /*
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| 370 | * Determine the location of data point relative to the 1st knot.
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| 371 | */
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| 372 | if (Y1 > intp->x) {
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| 373 | y = QuadGetImage(left->y, V2, Y2, Y1, intp->x, left->x);
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| 374 | } else if (Y1 < intp->x) {
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| 375 | /*
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| 376 | * Determine the location of the data point relative to
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| 377 | * the 2nd knot.
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| 378 | */
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| 379 | if (Z1 > intp->x) {
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| 380 | y = QuadGetImage(Y2, E2, Z2, Z1, intp->x, Y1);
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| 381 | } else if (Z1 < intp->x) {
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| 382 | y = QuadGetImage(Z2, W2, right->y, right->x, intp->x, Z1);
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| 383 | } else {
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| 384 | y = Z2;
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| 385 | }
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| 386 | } else {
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| 387 | y = Y2;
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| 388 | }
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| 389 | } else {
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| 390 |
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| 391 | /*
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| 392 | * Cases 1, 2, or 3:
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| 393 | *
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| 394 | * Determine the location of the data point relative to the
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| 395 | * knot.
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| 396 | */
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| 397 | if (Z1 < intp->x) {
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| 398 | y = QuadGetImage(Z2, W2, right->y, right->x, intp->x, Z1);
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| 399 | } else if (Z1 > intp->x) {
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| 400 | y = QuadGetImage(left->y, V2, Z2, Z1, intp->x, left->x);
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| 401 | } else {
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| 402 | y = Z2;
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| 403 | }
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| 404 | }
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| 405 | intp->y = y;
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| 406 | }
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| 407 |
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| 408 | /*
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| 409 | * -----------------------------------------------------------------------
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| 410 | *
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| 411 | * QuadSlopes --
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| 412 | *
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| 413 | * Calculates the derivative at each of the data points. The
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| 414 | * slopes computed will insure that an osculatory quadratic
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| 415 | * spline will have one additional knot between two adjacent
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| 416 | * points of interpolation. Convexity and monotonicity are
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| 417 | * preserved wherever these conditions are compatible with the
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| 418 | * data.
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| 419 | *
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| 420 | * Results:
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| 421 | * The output array "m" is filled with the derivates at each
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| 422 | * data point.
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| 423 | *
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| 424 | * -----------------------------------------------------------------------
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| 425 | */
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| 426 | static void
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| 427 | QuadSlopes(points, m, nPoints)
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| 428 | Point2D points[];
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| 429 | double *m; /* (out) To be filled with the first
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| 430 | * derivative at each data point. */
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| 431 | int nPoints; /* Number of data points (dimension of
|
---|
| 432 | * x, y, and m). */
|
---|
| 433 | {
|
---|
| 434 | double xbar, xmid, xhat, ydif1, ydif2;
|
---|
| 435 | double yxmid;
|
---|
| 436 | double m1, m2;
|
---|
| 437 | double m1s, m2s;
|
---|
| 438 | register int i, n, l;
|
---|
| 439 |
|
---|
| 440 | m1s = m2s = m1 = m2 = 0;
|
---|
| 441 | for (l = 0, i = 1, n = 2; i < (nPoints - 1); l++, i++, n++) {
|
---|
| 442 | /*
|
---|
| 443 | * Calculate the slopes of the two lines joining three
|
---|
| 444 | * consecutive data points.
|
---|
| 445 | */
|
---|
| 446 | ydif1 = points[i].y - points[l].y;
|
---|
| 447 | ydif2 = points[n].y - points[i].y;
|
---|
| 448 | m1 = ydif1 / (points[i].x - points[l].x);
|
---|
| 449 | m2 = ydif2 / (points[n].x - points[i].x);
|
---|
| 450 | if (i == 1) {
|
---|
| 451 | m1s = m1, m2s = m2; /* Save slopes of starting point */
|
---|
| 452 | }
|
---|
| 453 | /*
|
---|
| 454 | * If one of the preceding slopes is zero or if they have opposite
|
---|
| 455 | * sign, assign the value zero to the derivative at the middle
|
---|
| 456 | * point.
|
---|
| 457 | */
|
---|
| 458 | if ((m1 == 0.0) || (m2 == 0.0) || ((m1 * m2) <= 0.0)) {
|
---|
| 459 | m[i] = 0.0;
|
---|
| 460 | } else if (FABS(m1) > FABS(m2)) {
|
---|
| 461 | /*
|
---|
| 462 | * Calculate the slope by extending the line with slope m1.
|
---|
| 463 | */
|
---|
| 464 | xbar = ydif2 / m1 + points[i].x;
|
---|
| 465 | xhat = (xbar + points[n].x) / 2.0;
|
---|
| 466 | m[i] = ydif2 / (xhat - points[i].x);
|
---|
| 467 | } else {
|
---|
| 468 | /*
|
---|
| 469 | * Calculate the slope by extending the line with slope m2.
|
---|
| 470 | */
|
---|
| 471 | xbar = -ydif1 / m2 + points[i].x;
|
---|
| 472 | xhat = (points[l].x + xbar) / 2.0;
|
---|
| 473 | m[i] = ydif1 / (points[i].x - xhat);
|
---|
| 474 | }
|
---|
| 475 | }
|
---|
| 476 |
|
---|
| 477 | /* Calculate the slope at the last point, x(n). */
|
---|
| 478 | i = nPoints - 2;
|
---|
| 479 | n = nPoints - 1;
|
---|
| 480 | if ((m1 * m2) < 0.0) {
|
---|
| 481 | m[n] = m2 * 2.0;
|
---|
| 482 | } else {
|
---|
| 483 | xmid = (points[i].x + points[n].x) / 2.0;
|
---|
| 484 | yxmid = m[i] * (xmid - points[i].x) + points[i].y;
|
---|
| 485 | m[n] = (points[n].y - yxmid) / (points[n].x - xmid);
|
---|
| 486 | if ((m[n] * m2) < 0.0) {
|
---|
| 487 | m[n] = 0.0;
|
---|
| 488 | }
|
---|
| 489 | }
|
---|
| 490 |
|
---|
| 491 | /* Calculate the slope at the first point, x(0). */
|
---|
| 492 | if ((m1s * m2s) < 0.0) {
|
---|
| 493 | m[0] = m1s * 2.0;
|
---|
| 494 | } else {
|
---|
| 495 | xmid = (points[0].x + points[1].x) / 2.0;
|
---|
| 496 | yxmid = m[1] * (xmid - points[1].x) + points[1].y;
|
---|
| 497 | m[0] = (yxmid - points[0].y) / (xmid - points[0].x);
|
---|
| 498 | if ((m[0] * m1s) < 0.0) {
|
---|
| 499 | m[0] = 0.0;
|
---|
| 500 | }
|
---|
| 501 | }
|
---|
| 502 |
|
---|
| 503 | }
|
---|
| 504 |
|
---|
| 505 | /*
|
---|
| 506 | * -----------------------------------------------------------------------
|
---|
| 507 | *
|
---|
| 508 | * QuadEval --
|
---|
| 509 | *
|
---|
| 510 | * QuadEval controls the evaluation of an osculatory quadratic
|
---|
| 511 | * spline. The user may provide his own slopes at the points of
|
---|
| 512 | * interpolation or use the subroutine 'QuadSlopes' to calculate
|
---|
| 513 | * slopes which are consistent with the shape of the data.
|
---|
| 514 | *
|
---|
| 515 | * ON INPUT--
|
---|
| 516 | * intpPts must be a nondecreasing vector of points at which the
|
---|
| 517 | * spline will be evaluated.
|
---|
| 518 | * origPts contains the abscissas of the data points to be
|
---|
| 519 | * interpolated. xtab must be increasing.
|
---|
| 520 | * y contains the ordinates of the data points to be
|
---|
| 521 | * interpolated.
|
---|
| 522 | * m contains the slope of the spline at each point of
|
---|
| 523 | * interpolation.
|
---|
| 524 | * nPoints number of data points (dimension of xtab and y).
|
---|
| 525 | * numEval is the number of points of evaluation (dimension of
|
---|
| 526 | * xval and yval).
|
---|
| 527 | * epsilon is a relative error tolerance used in subroutine
|
---|
| 528 | * 'QuadChoose' to distinguish the situation m(i) or
|
---|
| 529 | * m(i+1) is relatively close to the slope or twice
|
---|
| 530 | * the slope of the linear segment between xtab(i) and
|
---|
| 531 | * xtab(i+1). If this situation occurs, roundoff may
|
---|
| 532 | * cause a change in convexity or monotonicity of the
|
---|
| 533 | * resulting spline and a change in the case number
|
---|
| 534 | * provided by 'QuadChoose'. If epsilon is not equal to zero,
|
---|
| 535 | * then epsilon should be greater than or equal to machine
|
---|
| 536 | * epsilon.
|
---|
| 537 | * ON OUTPUT--
|
---|
| 538 | * yval contains the images of the points in xval.
|
---|
| 539 | * err is one of the following error codes:
|
---|
| 540 | * 0 - QuadEval ran normally.
|
---|
| 541 | * 1 - xval(i) is less than xtab(1) for at least one
|
---|
| 542 | * i or xval(i) is greater than xtab(num) for at
|
---|
| 543 | * least one i. QuadEval will extrapolate to provide
|
---|
| 544 | * function values for these abscissas.
|
---|
| 545 | * 2 - xval(i+1) < xval(i) for some i.
|
---|
| 546 | *
|
---|
| 547 | *
|
---|
| 548 | * QuadEval calls the following subroutines or functions:
|
---|
| 549 | * Search
|
---|
| 550 | * QuadCases
|
---|
| 551 | * QuadChoose
|
---|
| 552 | * QuadSpline
|
---|
| 553 | * -----------------------------------------------------------------------
|
---|
| 554 | */
|
---|
| 555 | static int
|
---|
| 556 | QuadEval(origPts, nOrigPts, intpPts, nIntpPts, m, epsilon)
|
---|
| 557 | Point2D origPts[];
|
---|
| 558 | int nOrigPts;
|
---|
| 559 | Point2D intpPts[];
|
---|
| 560 | int nIntpPts;
|
---|
| 561 | double *m; /* Slope of the spline at each point
|
---|
| 562 | * of interpolation. */
|
---|
| 563 | double epsilon; /* Relative error tolerance (see choose) */
|
---|
| 564 | {
|
---|
| 565 | int error;
|
---|
| 566 | register int i, j;
|
---|
| 567 | double param[10];
|
---|
| 568 | int ncase;
|
---|
| 569 | int start, end;
|
---|
| 570 | int l, p;
|
---|
| 571 | register int n;
|
---|
| 572 | int found;
|
---|
| 573 |
|
---|
| 574 | /* Initialize indices and set error result */
|
---|
| 575 | error = 0;
|
---|
| 576 | l = nOrigPts - 1;
|
---|
| 577 | p = l - 1;
|
---|
| 578 | ncase = 1;
|
---|
| 579 |
|
---|
| 580 | /*
|
---|
| 581 | * Determine if abscissas of new vector are non-decreasing.
|
---|
| 582 | */
|
---|
| 583 | for (j = 1; j < nIntpPts; j++) {
|
---|
| 584 | if (intpPts[j].x < intpPts[j - 1].x) {
|
---|
| 585 | return 2;
|
---|
| 586 | }
|
---|
| 587 | }
|
---|
| 588 | /*
|
---|
| 589 | * Determine if any of the points in xval are LESS than the
|
---|
| 590 | * abscissa of the first data point.
|
---|
| 591 | */
|
---|
| 592 | for (start = 0; start < nIntpPts; start++) {
|
---|
| 593 | if (intpPts[start].x >= origPts[0].x) {
|
---|
| 594 | break;
|
---|
| 595 | }
|
---|
| 596 | }
|
---|
| 597 | /*
|
---|
| 598 | * Determine if any of the points in xval are GREATER than the
|
---|
| 599 | * abscissa of the l data point.
|
---|
| 600 | */
|
---|
| 601 | for (end = nIntpPts - 1; end >= 0; end--) {
|
---|
| 602 | if (intpPts[end].x <= origPts[l].x) {
|
---|
| 603 | break;
|
---|
| 604 | }
|
---|
| 605 | }
|
---|
| 606 |
|
---|
| 607 | if (start > 0) {
|
---|
| 608 | error = 1; /* Set error value to indicate that
|
---|
| 609 | * extrapolation has occurred. */
|
---|
| 610 | /*
|
---|
| 611 | * Calculate the images of points of evaluation whose abscissas
|
---|
| 612 | * are less than the abscissa of the first data point.
|
---|
| 613 | */
|
---|
| 614 | ncase = QuadSelect(origPts, origPts + 1, m[0], m[1], epsilon, param);
|
---|
| 615 | for (j = 0; j < (start - 1); j++) {
|
---|
| 616 | QuadSpline(intpPts + j, origPts, origPts + 1, param, ncase);
|
---|
| 617 | }
|
---|
| 618 | if (nIntpPts == 1) {
|
---|
| 619 | return error;
|
---|
| 620 | }
|
---|
| 621 | }
|
---|
| 622 | if ((nIntpPts == 1) && (end != (nIntpPts - 1))) {
|
---|
| 623 | goto noExtrapolation;
|
---|
| 624 | }
|
---|
| 625 |
|
---|
| 626 | /*
|
---|
| 627 | * Search locates the interval in which the first in-range
|
---|
| 628 | * point of evaluation lies.
|
---|
| 629 | */
|
---|
| 630 |
|
---|
| 631 | i = Search(origPts, nOrigPts, intpPts[start].x, &found);
|
---|
| 632 |
|
---|
| 633 | n = i + 1;
|
---|
| 634 | if (n >= nOrigPts) {
|
---|
| 635 | n = nOrigPts - 1;
|
---|
| 636 | i = nOrigPts - 2;
|
---|
| 637 | }
|
---|
| 638 | /*
|
---|
| 639 | * If the first in-range point of evaluation is equal to one
|
---|
| 640 | * of the data points, assign the appropriate value from y.
|
---|
| 641 | * Continue until a point of evaluation is found which is not
|
---|
| 642 | * equal to a data point.
|
---|
| 643 | */
|
---|
| 644 | if (found) {
|
---|
| 645 | do {
|
---|
| 646 | intpPts[start].y = origPts[i].y;
|
---|
| 647 | start++;
|
---|
| 648 | if (start >= nIntpPts) {
|
---|
| 649 | return error;
|
---|
| 650 | }
|
---|
| 651 | } while (intpPts[start - 1].x == intpPts[start].x);
|
---|
| 652 |
|
---|
| 653 | for (;;) {
|
---|
| 654 | if (intpPts[start].x < origPts[n].x) {
|
---|
| 655 | break; /* Break out of for-loop */
|
---|
| 656 | }
|
---|
| 657 | if (intpPts[start].x == origPts[n].x) {
|
---|
| 658 | do {
|
---|
| 659 | intpPts[start].y = origPts[n].y;
|
---|
| 660 | start++;
|
---|
| 661 | if (start >= nIntpPts) {
|
---|
| 662 | return error;
|
---|
| 663 | }
|
---|
| 664 | } while (intpPts[start].x == intpPts[start - 1].x);
|
---|
| 665 | }
|
---|
| 666 | i++;
|
---|
| 667 | n++;
|
---|
| 668 | }
|
---|
| 669 | }
|
---|
| 670 | /*
|
---|
| 671 | * Calculate the images of all the points which lie within
|
---|
| 672 | * range of the data.
|
---|
| 673 | */
|
---|
| 674 | if ((i > 0) || (error != 1)) {
|
---|
| 675 | ncase = QuadSelect(origPts + i, origPts + n, m[i], m[n],
|
---|
| 676 | epsilon, param);
|
---|
| 677 | }
|
---|
| 678 | for (j = start; j <= end; j++) {
|
---|
| 679 | /*
|
---|
| 680 | * If xx(j) - x(n) is negative, do not recalculate
|
---|
| 681 | * the parameters for this section of the spline since
|
---|
| 682 | * they are already known.
|
---|
| 683 | */
|
---|
| 684 | if (intpPts[j].x == origPts[n].x) {
|
---|
| 685 | intpPts[j].y = origPts[n].y;
|
---|
| 686 | continue;
|
---|
| 687 | } else if (intpPts[j].x > origPts[n].x) {
|
---|
| 688 | double delta;
|
---|
| 689 |
|
---|
| 690 | /* Determine that the routine is in the correct part of
|
---|
| 691 | the spline. */
|
---|
| 692 | do {
|
---|
| 693 | i++, n++;
|
---|
| 694 | delta = intpPts[j].x - origPts[n].x;
|
---|
| 695 | } while (delta > 0.0);
|
---|
| 696 |
|
---|
| 697 | if (delta < 0.0) {
|
---|
| 698 | ncase = QuadSelect(origPts + i, origPts + n, m[i],
|
---|
| 699 | m[n], epsilon, param);
|
---|
| 700 | } else if (delta == 0.0) {
|
---|
| 701 | intpPts[j].y = origPts[n].y;
|
---|
| 702 | continue;
|
---|
| 703 | }
|
---|
| 704 | }
|
---|
| 705 | QuadSpline(intpPts + j, origPts + i, origPts + n, param, ncase);
|
---|
| 706 | }
|
---|
| 707 |
|
---|
| 708 | if (end == (nIntpPts - 1)) {
|
---|
| 709 | return error;
|
---|
| 710 | }
|
---|
| 711 | if ((n == l) && (intpPts[end].x != origPts[l].x)) {
|
---|
| 712 | goto noExtrapolation;
|
---|
| 713 | }
|
---|
| 714 |
|
---|
| 715 | error = 1; /* Set error value to indicate that
|
---|
| 716 | * extrapolation has occurred. */
|
---|
| 717 | ncase = QuadSelect(origPts + p, origPts + l, m[p], m[l], epsilon, param);
|
---|
| 718 |
|
---|
| 719 | noExtrapolation:
|
---|
| 720 | /*
|
---|
| 721 | * Calculate the images of the points of evaluation whose
|
---|
| 722 | * abscissas are greater than the abscissa of the last data point.
|
---|
| 723 | */
|
---|
| 724 | for (j = (end + 1); j < nIntpPts; j++) {
|
---|
| 725 | QuadSpline(intpPts + j, origPts + p, origPts + l, param, ncase);
|
---|
| 726 | }
|
---|
| 727 | return error;
|
---|
| 728 | }
|
---|
| 729 |
|
---|
| 730 | /*
|
---|
| 731 | * -----------------------------------------------------------------------
|
---|
| 732 | *
|
---|
| 733 | * Shape preserving quadratic splines
|
---|
| 734 | * by D.F.Mcallister & J.A.Roulier
|
---|
| 735 | * Coded by S.L.Dodd & M.Roulier
|
---|
| 736 | * N.C.State University
|
---|
| 737 | *
|
---|
| 738 | * -----------------------------------------------------------------------
|
---|
| 739 | */
|
---|
| 740 | /*
|
---|
| 741 | * Driver routine for quadratic spline package
|
---|
| 742 | * On input--
|
---|
| 743 | * X,Y Contain n-long arrays of data (x is increasing)
|
---|
| 744 | * XM Contains m-long array of x values (increasing)
|
---|
| 745 | * eps Relative error tolerance
|
---|
| 746 | * n Number of input data points
|
---|
| 747 | * m Number of output data points
|
---|
| 748 | * On output--
|
---|
| 749 | * work Contains the value of the first derivative at each data point
|
---|
| 750 | * ym Contains the interpolated spline value at each data point
|
---|
| 751 | */
|
---|
| 752 | int
|
---|
| 753 | Blt_QuadraticSpline(origPts, nOrigPts, intpPts, nIntpPts)
|
---|
| 754 | Point2D origPts[];
|
---|
| 755 | int nOrigPts;
|
---|
| 756 | Point2D intpPts[];
|
---|
| 757 | int nIntpPts;
|
---|
| 758 | {
|
---|
| 759 | double epsilon;
|
---|
| 760 | double *work;
|
---|
| 761 | int result;
|
---|
| 762 |
|
---|
| 763 | work = Blt_Malloc(nOrigPts * sizeof(double));
|
---|
| 764 | assert(work);
|
---|
| 765 |
|
---|
| 766 | epsilon = 0.0; /* TBA: adjust error via command-line option */
|
---|
| 767 | /* allocate space for vectors used in calculation */
|
---|
| 768 | QuadSlopes(origPts, work, nOrigPts);
|
---|
| 769 | result = QuadEval(origPts, nOrigPts, intpPts, nIntpPts, work, epsilon);
|
---|
| 770 | Blt_Free(work);
|
---|
| 771 | if (result > 1) {
|
---|
| 772 | return FALSE;
|
---|
| 773 | }
|
---|
| 774 | return TRUE;
|
---|
| 775 | }
|
---|
| 776 |
|
---|
| 777 | /*
|
---|
| 778 | * ------------------------------------------------------------------------
|
---|
| 779 | *
|
---|
| 780 | * Reference:
|
---|
| 781 | * Numerical Analysis, R. Burden, J. Faires and A. Reynolds.
|
---|
| 782 | * Prindle, Weber & Schmidt 1981 pp 112
|
---|
| 783 | *
|
---|
| 784 | * Parameters:
|
---|
| 785 | * origPts - vector of points, assumed to be sorted along x.
|
---|
| 786 | * intpPts - vector of new points.
|
---|
| 787 | *
|
---|
| 788 | * ------------------------------------------------------------------------
|
---|
| 789 | */
|
---|
| 790 | int
|
---|
| 791 | Blt_NaturalSpline(origPts, nOrigPts, intpPts, nIntpPts)
|
---|
| 792 | Point2D origPts[];
|
---|
| 793 | int nOrigPts;
|
---|
| 794 | Point2D intpPts[];
|
---|
| 795 | int nIntpPts;
|
---|
| 796 | {
|
---|
| 797 | Cubic2D *eq;
|
---|
| 798 | Point2D *iPtr, *endPtr;
|
---|
| 799 | TriDiagonalMatrix *A;
|
---|
| 800 | double *dx; /* vector of deltas in x */
|
---|
| 801 | double x, dy, alpha;
|
---|
| 802 | int isKnot;
|
---|
| 803 | register int i, j, n;
|
---|
| 804 |
|
---|
| 805 | dx = Blt_Malloc(sizeof(double) * nOrigPts);
|
---|
| 806 | /* Calculate vector of differences */
|
---|
| 807 | for (i = 0, j = 1; j < nOrigPts; i++, j++) {
|
---|
| 808 | dx[i] = origPts[j].x - origPts[i].x;
|
---|
| 809 | if (dx[i] < 0.0) {
|
---|
| 810 | return 0;
|
---|
| 811 | }
|
---|
| 812 | }
|
---|
| 813 | n = nOrigPts - 1; /* Number of intervals. */
|
---|
| 814 | A = Blt_Malloc(sizeof(TriDiagonalMatrix) * nOrigPts);
|
---|
| 815 | if (A == NULL) {
|
---|
| 816 | Blt_Free(dx);
|
---|
| 817 | return 0;
|
---|
| 818 | }
|
---|
| 819 | /* Vectors to solve the tridiagonal matrix */
|
---|
| 820 | A[0][0] = A[n][0] = 1.0;
|
---|
| 821 | A[0][1] = A[n][1] = 0.0;
|
---|
| 822 | A[0][2] = A[n][2] = 0.0;
|
---|
| 823 |
|
---|
| 824 | /* Calculate the intermediate results */
|
---|
| 825 | for (i = 0, j = 1; j < n; j++, i++) {
|
---|
| 826 | alpha = 3.0 * ((origPts[j + 1].y / dx[j]) - (origPts[j].y / dx[i]) -
|
---|
| 827 | (origPts[j].y / dx[j]) + (origPts[i].y / dx[i]));
|
---|
| 828 | A[j][0] = 2 * (dx[j] + dx[i]) - dx[i] * A[i][1];
|
---|
| 829 | A[j][1] = dx[j] / A[j][0];
|
---|
| 830 | A[j][2] = (alpha - dx[i] * A[i][2]) / A[j][0];
|
---|
| 831 | }
|
---|
| 832 | eq = Blt_Malloc(sizeof(Cubic2D) * nOrigPts);
|
---|
| 833 |
|
---|
| 834 | if (eq == NULL) {
|
---|
| 835 | Blt_Free(A);
|
---|
| 836 | Blt_Free(dx);
|
---|
| 837 | return FALSE;
|
---|
| 838 | }
|
---|
| 839 | eq[0].c = eq[n].c = 0.0;
|
---|
| 840 | for (j = n, i = n - 1; i >= 0; i--, j--) {
|
---|
| 841 | eq[i].c = A[i][2] - A[i][1] * eq[j].c;
|
---|
| 842 | dy = origPts[i+1].y - origPts[i].y;
|
---|
| 843 | eq[i].b = (dy) / dx[i] - dx[i] * (eq[j].c + 2.0 * eq[i].c) / 3.0;
|
---|
| 844 | eq[i].d = (eq[j].c - eq[i].c) / (3.0 * dx[i]);
|
---|
| 845 | }
|
---|
| 846 | Blt_Free(A);
|
---|
| 847 | Blt_Free(dx);
|
---|
| 848 |
|
---|
| 849 | endPtr = intpPts + nIntpPts;
|
---|
| 850 | /* Now calculate the new values */
|
---|
| 851 | for (iPtr = intpPts; iPtr < endPtr; iPtr++) {
|
---|
| 852 | iPtr->y = 0.0;
|
---|
| 853 | x = iPtr->x;
|
---|
| 854 |
|
---|
| 855 | /* Is it outside the interval? */
|
---|
| 856 | if ((x < origPts[0].x) || (x > origPts[n].x)) {
|
---|
| 857 | continue;
|
---|
| 858 | }
|
---|
| 859 | /* Search for the interval containing x in the point array */
|
---|
| 860 | i = Search(origPts, nOrigPts, x, &isKnot);
|
---|
| 861 | if (isKnot) {
|
---|
| 862 | iPtr->y = origPts[i].y;
|
---|
| 863 | } else {
|
---|
| 864 | i--;
|
---|
| 865 | x -= origPts[i].x;
|
---|
| 866 | iPtr->y = origPts[i].y +
|
---|
| 867 | x * (eq[i].b + x * (eq[i].c + x * eq[i].d));
|
---|
| 868 | }
|
---|
| 869 | }
|
---|
| 870 | Blt_Free(eq);
|
---|
| 871 | return TRUE;
|
---|
| 872 | }
|
---|
| 873 |
|
---|
| 874 | static Blt_OpSpec splineOps[] =
|
---|
| 875 | {
|
---|
| 876 | {"natural", 1, (Blt_Op)Blt_NaturalSpline, 6, 6, "x y splx sply",},
|
---|
| 877 | {"quadratic", 1, (Blt_Op)Blt_QuadraticSpline, 6, 6, "x y splx sply",},
|
---|
| 878 | };
|
---|
| 879 | static int nSplineOps = sizeof(splineOps) / sizeof(Blt_OpSpec);
|
---|
| 880 |
|
---|
| 881 | /*ARGSUSED*/
|
---|
| 882 | static int
|
---|
| 883 | SplineCmd(clientData, interp, argc, argv)
|
---|
| 884 | ClientData clientData; /* Not used. */
|
---|
| 885 | Tcl_Interp *interp;
|
---|
| 886 | int argc;
|
---|
| 887 | char **argv;
|
---|
| 888 | {
|
---|
| 889 | Blt_Op proc;
|
---|
| 890 | Blt_Vector *x, *y, *splX, *splY;
|
---|
| 891 | double *xArr, *yArr;
|
---|
| 892 | register int i;
|
---|
| 893 | Point2D *origPts, *intpPts;
|
---|
| 894 | int nOrigPts, nIntpPts;
|
---|
| 895 |
|
---|
| 896 | proc = Blt_GetOp(interp, nSplineOps, splineOps, BLT_OP_ARG1, argc, argv,0);
|
---|
| 897 | if (proc == NULL) {
|
---|
| 898 | return TCL_ERROR;
|
---|
| 899 | }
|
---|
| 900 | if ((Blt_GetVector(interp, argv[2], &x) != TCL_OK) ||
|
---|
| 901 | (Blt_GetVector(interp, argv[3], &y) != TCL_OK) ||
|
---|
| 902 | (Blt_GetVector(interp, argv[4], &splX) != TCL_OK)) {
|
---|
| 903 | return TCL_ERROR;
|
---|
| 904 | }
|
---|
| 905 | nOrigPts = Blt_VecLength(x);
|
---|
| 906 | if (nOrigPts < 3) {
|
---|
| 907 | Tcl_AppendResult(interp, "length of vector \"", argv[2], "\" is < 3",
|
---|
| 908 | (char *)NULL);
|
---|
| 909 | return TCL_ERROR;
|
---|
| 910 | }
|
---|
| 911 | for (i = 1; i < nOrigPts; i++) {
|
---|
| 912 | if (Blt_VecData(x)[i] < Blt_VecData(x)[i - 1]) {
|
---|
| 913 | Tcl_AppendResult(interp, "x vector \"", argv[2],
|
---|
| 914 | "\" must be monotonically increasing", (char *)NULL);
|
---|
| 915 | return TCL_ERROR;
|
---|
| 916 | }
|
---|
| 917 | }
|
---|
| 918 | /* Check that all the data points aren't the same. */
|
---|
| 919 | if (Blt_VecData(x)[i - 1] <= Blt_VecData(x)[0]) {
|
---|
| 920 | Tcl_AppendResult(interp, "x vector \"", argv[2],
|
---|
| 921 | "\" must be monotonically increasing", (char *)NULL);
|
---|
| 922 | return TCL_ERROR;
|
---|
| 923 | }
|
---|
| 924 | if (nOrigPts != Blt_VecLength(y)) {
|
---|
| 925 | Tcl_AppendResult(interp, "vectors \"", argv[2], "\" and \"", argv[3],
|
---|
| 926 | " have different lengths", (char *)NULL);
|
---|
| 927 | return TCL_ERROR;
|
---|
| 928 | }
|
---|
| 929 | nIntpPts = Blt_VecLength(splX);
|
---|
| 930 | if (Blt_GetVector(interp, argv[5], &splY) != TCL_OK) {
|
---|
| 931 | /*
|
---|
| 932 | * If the named vector to hold the ordinates of the spline
|
---|
| 933 | * doesn't exist, create one the same size as the vector
|
---|
| 934 | * containing the abscissas.
|
---|
| 935 | */
|
---|
| 936 | if (Blt_CreateVector(interp, argv[5], nIntpPts, &splY) != TCL_OK) {
|
---|
| 937 | return TCL_ERROR;
|
---|
| 938 | }
|
---|
| 939 | } else if (nIntpPts != Blt_VecLength(splY)) {
|
---|
| 940 | /*
|
---|
| 941 | * The x and y vectors differ in size. Make the number of ordinates
|
---|
| 942 | * the same as the number of abscissas.
|
---|
| 943 | */
|
---|
| 944 | if (Blt_ResizeVector(splY, nIntpPts) != TCL_OK) {
|
---|
| 945 | return TCL_ERROR;
|
---|
| 946 | }
|
---|
| 947 | }
|
---|
| 948 | origPts = Blt_Malloc(sizeof(Point2D) * nOrigPts);
|
---|
| 949 | if (origPts == NULL) {
|
---|
| 950 | Tcl_AppendResult(interp, "can't allocate \"", Blt_Itoa(nOrigPts),
|
---|
| 951 | "\" points", (char *)NULL);
|
---|
| 952 | return TCL_ERROR;
|
---|
| 953 | }
|
---|
| 954 | intpPts = Blt_Malloc(sizeof(Point2D) * nIntpPts);
|
---|
| 955 | if (intpPts == NULL) {
|
---|
| 956 | Tcl_AppendResult(interp, "can't allocate \"", Blt_Itoa(nIntpPts),
|
---|
| 957 | "\" points", (char *)NULL);
|
---|
| 958 | Blt_Free(origPts);
|
---|
| 959 | return TCL_ERROR;
|
---|
| 960 | }
|
---|
| 961 | xArr = Blt_VecData(x);
|
---|
| 962 | yArr = Blt_VecData(y);
|
---|
| 963 | for (i = 0; i < nOrigPts; i++) {
|
---|
| 964 | origPts[i].x = xArr[i];
|
---|
| 965 | origPts[i].y = yArr[i];
|
---|
| 966 | }
|
---|
| 967 | xArr = Blt_VecData(splX);
|
---|
| 968 | yArr = Blt_VecData(splY);
|
---|
| 969 | for (i = 0; i < nIntpPts; i++) {
|
---|
| 970 | intpPts[i].x = xArr[i];
|
---|
| 971 | intpPts[i].y = yArr[i];
|
---|
| 972 | }
|
---|
| 973 | if (!(*proc) (origPts, nOrigPts, intpPts, nIntpPts)) {
|
---|
| 974 | Tcl_AppendResult(interp, "error generating spline for \"",
|
---|
| 975 | Blt_NameOfVector(splY), "\"", (char *)NULL);
|
---|
| 976 | Blt_Free(origPts);
|
---|
| 977 | Blt_Free(intpPts);
|
---|
| 978 | return TCL_ERROR;
|
---|
| 979 | }
|
---|
| 980 | yArr = Blt_VecData(splY);
|
---|
| 981 | for (i = 0; i < nIntpPts; i++) {
|
---|
| 982 | yArr[i] = intpPts[i].y;
|
---|
| 983 | }
|
---|
| 984 | Blt_Free(origPts);
|
---|
| 985 | Blt_Free(intpPts);
|
---|
| 986 |
|
---|
| 987 | /* Finally update the vector. The size of the vector hasn't
|
---|
| 988 | * changed, just the data. Reset the vector using TCL_STATIC to
|
---|
| 989 | * indicate this. */
|
---|
| 990 | if (Blt_ResetVector(splY, Blt_VecData(splY), Blt_VecLength(splY),
|
---|
| 991 | Blt_VecSize(splY), TCL_STATIC) != TCL_OK) {
|
---|
| 992 | return TCL_ERROR;
|
---|
| 993 | }
|
---|
| 994 | return TCL_OK;
|
---|
| 995 | }
|
---|
| 996 |
|
---|
| 997 | int
|
---|
| 998 | Blt_SplineInit(interp)
|
---|
| 999 | Tcl_Interp *interp;
|
---|
| 1000 | {
|
---|
| 1001 | static Blt_CmdSpec cmdSpec =
|
---|
| 1002 | {"spline", SplineCmd,};
|
---|
| 1003 |
|
---|
| 1004 | if (Blt_InitCmd(interp, "blt", &cmdSpec) == NULL) {
|
---|
| 1005 | return TCL_ERROR;
|
---|
| 1006 | }
|
---|
| 1007 | return TCL_OK;
|
---|
| 1008 | }
|
---|
| 1009 |
|
---|
| 1010 |
|
---|
| 1011 | #define SQR(x) ((x)*(x))
|
---|
| 1012 |
|
---|
| 1013 | typedef struct {
|
---|
| 1014 | double t; /* Arc length of interval. */
|
---|
| 1015 | double x; /* 2nd derivative of X with respect to T */
|
---|
| 1016 | double y; /* 2nd derivative of Y with respect to T */
|
---|
| 1017 | } CubicSpline;
|
---|
| 1018 |
|
---|
| 1019 |
|
---|
| 1020 | /*
|
---|
| 1021 | * The following two procedures solve the special linear system which arise
|
---|
| 1022 | * in cubic spline interpolation. If x is assumed cyclic ( x[i]=x[n+i] ) the
|
---|
| 1023 | * equations can be written as (i=0,1,...,n-1):
|
---|
| 1024 | * m[i][0] * x[i-1] + m[i][1] * x[i] + m[i][2] * x[i+1] = b[i] .
|
---|
| 1025 | * In matrix notation one gets A * x = b, where the matrix A is tridiagonal
|
---|
| 1026 | * with additional elements in the upper right and lower left position:
|
---|
| 1027 | * A[i][0] = A_{i,i-1} for i=1,2,...,n-1 and m[0][0] = A_{0,n-1} ,
|
---|
| 1028 | * A[i][1] = A_{i, i } for i=0,1,...,n-1
|
---|
| 1029 | * A[i][2] = A_{i,i+1} for i=0,1,...,n-2 and m[n-1][2] = A_{n-1,0}.
|
---|
| 1030 | * A should be symmetric (A[i+1][0] == A[i][2]) and positive definite.
|
---|
| 1031 | * The size of the system is given in n (n>=1).
|
---|
| 1032 | *
|
---|
| 1033 | * In the first procedure the Cholesky decomposition A = C^T * D * C
|
---|
| 1034 | * (C is upper triangle with unit diagonal, D is diagonal) is calculated.
|
---|
| 1035 | * Return TRUE if decomposition exist.
|
---|
| 1036 | */
|
---|
| 1037 | static int
|
---|
| 1038 | SolveCubic1(A, n)
|
---|
| 1039 | TriDiagonalMatrix A[];
|
---|
| 1040 | int n;
|
---|
| 1041 | {
|
---|
| 1042 | int i;
|
---|
| 1043 | double m_ij, m_n, m_nn, d;
|
---|
| 1044 |
|
---|
| 1045 | if (n < 1) {
|
---|
| 1046 | return FALSE; /* Dimension should be at least 1 */
|
---|
| 1047 | }
|
---|
| 1048 | d = A[0][1]; /* D_{0,0} = A_{0,0} */
|
---|
| 1049 | if (d <= 0.0) {
|
---|
| 1050 | return FALSE; /* A (or D) should be positive definite */
|
---|
| 1051 | }
|
---|
| 1052 | m_n = A[0][0]; /* A_{0,n-1} */
|
---|
| 1053 | m_nn = A[n - 1][1]; /* A_{n-1,n-1} */
|
---|
| 1054 | for (i = 0; i < n - 2; i++) {
|
---|
| 1055 | m_ij = A[i][2]; /* A_{i,1} */
|
---|
| 1056 | A[i][2] = m_ij / d; /* C_{i,i+1} */
|
---|
| 1057 | A[i][0] = m_n / d; /* C_{i,n-1} */
|
---|
| 1058 | m_nn -= A[i][0] * m_n; /* to get C_{n-1,n-1} */
|
---|
| 1059 | m_n = -A[i][2] * m_n; /* to get C_{i+1,n-1} */
|
---|
| 1060 | d = A[i + 1][1] - A[i][2] * m_ij; /* D_{i+1,i+1} */
|
---|
| 1061 | if (d <= 0.0) {
|
---|
| 1062 | return FALSE; /* Elements of D should be positive */
|
---|
| 1063 | }
|
---|
| 1064 | A[i + 1][1] = d;
|
---|
| 1065 | }
|
---|
| 1066 | if (n >= 2) { /* Complete last column */
|
---|
| 1067 | m_n += A[n - 2][2]; /* add A_{n-2,n-1} */
|
---|
| 1068 | A[n - 2][0] = m_n / d; /* C_{n-2,n-1} */
|
---|
| 1069 | A[n - 1][1] = d = m_nn - A[n - 2][0] * m_n; /* D_{n-1,n-1} */
|
---|
| 1070 | if (d <= 0.0) {
|
---|
| 1071 | return FALSE;
|
---|
| 1072 | }
|
---|
| 1073 | }
|
---|
| 1074 | return TRUE;
|
---|
| 1075 | }
|
---|
| 1076 |
|
---|
| 1077 | /*
|
---|
| 1078 | * The second procedure solves the linear system, with the Cholesky
|
---|
| 1079 | * decomposition calculated above (in m[][]) and the right side b given
|
---|
| 1080 | * in x[]. The solution x overwrites the right side in x[].
|
---|
| 1081 | */
|
---|
| 1082 | static void
|
---|
| 1083 | SolveCubic2(A, spline, nIntervals)
|
---|
| 1084 | TriDiagonalMatrix A[];
|
---|
| 1085 | CubicSpline spline[];
|
---|
| 1086 | int nIntervals;
|
---|
| 1087 | {
|
---|
| 1088 | int i;
|
---|
| 1089 | double x, y;
|
---|
| 1090 | int n, m;
|
---|
| 1091 |
|
---|
| 1092 | n = nIntervals - 2;
|
---|
| 1093 | m = nIntervals - 1;
|
---|
| 1094 |
|
---|
| 1095 | /* Division by transpose of C : b = C^{-T} * b */
|
---|
| 1096 | x = spline[m].x;
|
---|
| 1097 | y = spline[m].y;
|
---|
| 1098 | for (i = 0; i < n; i++) {
|
---|
| 1099 | spline[i + 1].x -= A[i][2] * spline[i].x; /* C_{i,i+1} * x(i) */
|
---|
| 1100 | spline[i + 1].y -= A[i][2] * spline[i].y; /* C_{i,i+1} * x(i) */
|
---|
| 1101 | x -= A[i][0] * spline[i].x; /* C_{i,n-1} * x(i) */
|
---|
| 1102 | y -= A[i][0] * spline[i].y; /* C_{i,n-1} * x(i) */
|
---|
| 1103 | }
|
---|
| 1104 | if (n >= 0) {
|
---|
| 1105 | /* C_{n-2,n-1} * x_{n-1} */
|
---|
| 1106 | spline[m].x = x - A[n][0] * spline[n].x;
|
---|
| 1107 | spline[m].y = y - A[n][0] * spline[n].y;
|
---|
| 1108 | }
|
---|
| 1109 | /* Division by D: b = D^{-1} * b */
|
---|
| 1110 | for (i = 0; i < nIntervals; i++) {
|
---|
| 1111 | spline[i].x /= A[i][1];
|
---|
| 1112 | spline[i].y /= A[i][1];
|
---|
| 1113 | }
|
---|
| 1114 |
|
---|
| 1115 | /* Division by C: b = C^{-1} * b */
|
---|
| 1116 | x = spline[m].x;
|
---|
| 1117 | y = spline[m].y;
|
---|
| 1118 | if (n >= 0) {
|
---|
| 1119 | /* C_{n-2,n-1} * x_{n-1} */
|
---|
| 1120 | spline[n].x -= A[n][0] * x;
|
---|
| 1121 | spline[n].y -= A[n][0] * y;
|
---|
| 1122 | }
|
---|
| 1123 | for (i = (n - 1); i >= 0; i--) {
|
---|
| 1124 | /* C_{i,i+1} * x_{i+1} + C_{i,n-1} * x_{n-1} */
|
---|
| 1125 | spline[i].x -= A[i][2] * spline[i + 1].x + A[i][0] * x;
|
---|
| 1126 | spline[i].y -= A[i][2] * spline[i + 1].y + A[i][0] * y;
|
---|
| 1127 | }
|
---|
| 1128 | }
|
---|
| 1129 |
|
---|
| 1130 | /*
|
---|
| 1131 | * Find second derivatives (x''(t_i),y''(t_i)) of cubic spline interpolation
|
---|
| 1132 | * through list of points (x_i,y_i). The parameter t is calculated as the
|
---|
| 1133 | * length of the linear stroke. The number of points must be at least 3.
|
---|
| 1134 | * Note: For CLOSED_CONTOURs the first and last point must be equal.
|
---|
| 1135 | */
|
---|
| 1136 | static CubicSpline *
|
---|
| 1137 | CubicSlopes(points, nPoints, isClosed, unitX, unitY)
|
---|
| 1138 | Point2D points[];
|
---|
| 1139 | int nPoints; /* Number of points (nPoints>=3) */
|
---|
| 1140 | int isClosed; /* CLOSED_CONTOUR or OPEN_CONTOUR */
|
---|
| 1141 | double unitX, unitY; /* Unit length in x and y (norm=1) */
|
---|
| 1142 | {
|
---|
| 1143 | CubicSpline *spline;
|
---|
| 1144 | register CubicSpline *s1, *s2;
|
---|
| 1145 | int n, i;
|
---|
| 1146 | double norm, dx, dy;
|
---|
| 1147 | TriDiagonalMatrix *A; /* The tri-diagonal matrix is saved here. */
|
---|
| 1148 |
|
---|
| 1149 | spline = Blt_Malloc(sizeof(CubicSpline) * nPoints);
|
---|
| 1150 | if (spline == NULL) {
|
---|
| 1151 | return NULL;
|
---|
| 1152 | }
|
---|
| 1153 | A = Blt_Malloc(sizeof(TriDiagonalMatrix) * nPoints);
|
---|
| 1154 | if (A == NULL) {
|
---|
| 1155 | Blt_Free(spline);
|
---|
| 1156 | return NULL;
|
---|
| 1157 | }
|
---|
| 1158 | /*
|
---|
| 1159 | * Calculate first differences in (dxdt2[i], y[i]) and interval lengths
|
---|
| 1160 | * in dist[i]:
|
---|
| 1161 | */
|
---|
| 1162 | s1 = spline;
|
---|
| 1163 | for (i = 0; i < nPoints - 1; i++) {
|
---|
| 1164 | s1->x = points[i+1].x - points[i].x;
|
---|
| 1165 | s1->y = points[i+1].y - points[i].y;
|
---|
| 1166 |
|
---|
| 1167 | /*
|
---|
| 1168 | * The Norm of a linear stroke is calculated in "normal coordinates"
|
---|
| 1169 | * and used as interval length:
|
---|
| 1170 | */
|
---|
| 1171 | dx = s1->x / unitX;
|
---|
| 1172 | dy = s1->y / unitY;
|
---|
| 1173 | s1->t = sqrt(dx * dx + dy * dy);
|
---|
| 1174 |
|
---|
| 1175 | s1->x /= s1->t; /* first difference, with unit norm: */
|
---|
| 1176 | s1->y /= s1->t; /* || (dxdt2[i], y[i]) || = 1 */
|
---|
| 1177 | s1++;
|
---|
| 1178 | }
|
---|
| 1179 |
|
---|
| 1180 | /*
|
---|
| 1181 | * Setup linear System: Ax = b
|
---|
| 1182 | */
|
---|
| 1183 | n = nPoints - 2; /* Without first and last point */
|
---|
| 1184 | if (isClosed) {
|
---|
| 1185 | /* First and last points must be equal for CLOSED_CONTOURs */
|
---|
| 1186 | spline[nPoints - 1].t = spline[0].t;
|
---|
| 1187 | spline[nPoints - 1].x = spline[0].x;
|
---|
| 1188 | spline[nPoints - 1].y = spline[0].y;
|
---|
| 1189 | n++; /* Add last point (= first point) */
|
---|
| 1190 | }
|
---|
| 1191 | s1 = spline, s2 = s1 + 1;
|
---|
| 1192 | for (i = 0; i < n; i++) {
|
---|
| 1193 | /* Matrix A, mainly tridiagonal with cyclic second index
|
---|
| 1194 | ("j = j+n mod n")
|
---|
| 1195 | */
|
---|
| 1196 | A[i][0] = s1->t; /* Off-diagonal element A_{i,i-1} */
|
---|
| 1197 | A[i][1] = 2.0 * (s1->t + s2->t); /* A_{i,i} */
|
---|
| 1198 | A[i][2] = s2->t; /* Off-diagonal element A_{i,i+1} */
|
---|
| 1199 |
|
---|
| 1200 | /* Right side b_x and b_y */
|
---|
| 1201 | s1->x = (s2->x - s1->x) * 6.0;
|
---|
| 1202 | s1->y = (s2->y - s1->y) * 6.0;
|
---|
| 1203 |
|
---|
| 1204 | /*
|
---|
| 1205 | * If the linear stroke shows a cusp of more than 90 degree,
|
---|
| 1206 | * the right side is reduced to avoid oscillations in the
|
---|
| 1207 | * spline:
|
---|
| 1208 | */
|
---|
| 1209 | /*
|
---|
| 1210 | * The Norm of a linear stroke is calculated in "normal coordinates"
|
---|
| 1211 | * and used as interval length:
|
---|
| 1212 | */
|
---|
| 1213 | dx = s1->x / unitX;
|
---|
| 1214 | dy = s1->y / unitY;
|
---|
| 1215 | norm = sqrt(dx * dx + dy * dy) / 8.5;
|
---|
| 1216 | if (norm > 1.0) {
|
---|
| 1217 | /* The first derivative will not be continuous */
|
---|
| 1218 | s1->x /= norm;
|
---|
| 1219 | s1->y /= norm;
|
---|
| 1220 | }
|
---|
| 1221 | s1++, s2++;
|
---|
| 1222 | }
|
---|
| 1223 |
|
---|
| 1224 | if (!isClosed) {
|
---|
| 1225 | /* Third derivative is set to zero at both ends */
|
---|
| 1226 | A[0][1] += A[0][0]; /* A_{0,0} */
|
---|
| 1227 | A[0][0] = 0.0; /* A_{0,n-1} */
|
---|
| 1228 | A[n-1][1] += A[n-1][2]; /* A_{n-1,n-1} */
|
---|
| 1229 | A[n-1][2] = 0.0; /* A_{n-1,0} */
|
---|
| 1230 | }
|
---|
| 1231 | /* Solve linear systems for dxdt2[] and y[] */
|
---|
| 1232 |
|
---|
| 1233 | if (SolveCubic1(A, n)) { /* Cholesky decomposition */
|
---|
| 1234 | SolveCubic2(A, spline, n); /* A * dxdt2 = b_x */
|
---|
| 1235 | } else { /* Should not happen, but who knows ... */
|
---|
| 1236 | Blt_Free(A);
|
---|
| 1237 | Blt_Free(spline);
|
---|
| 1238 | return NULL;
|
---|
| 1239 | }
|
---|
| 1240 | /* Shift all second derivatives one place right and update the ends. */
|
---|
| 1241 | s2 = spline + n, s1 = s2 - 1;
|
---|
| 1242 | for (/* empty */; s2 > spline; s2--, s1--) {
|
---|
| 1243 | s2->x = s1->x;
|
---|
| 1244 | s2->y = s1->y;
|
---|
| 1245 | }
|
---|
| 1246 | if (isClosed) {
|
---|
| 1247 | spline[0].x = spline[n].x;
|
---|
| 1248 | spline[0].y = spline[n].y;
|
---|
| 1249 | } else {
|
---|
| 1250 | /* Third derivative is 0.0 for the first and last interval. */
|
---|
| 1251 | spline[0].x = spline[1].x;
|
---|
| 1252 | spline[0].y = spline[1].y;
|
---|
| 1253 | spline[n + 1].x = spline[n].x;
|
---|
| 1254 | spline[n + 1].y = spline[n].y;
|
---|
| 1255 | }
|
---|
| 1256 | Blt_Free( A);
|
---|
| 1257 | return spline;
|
---|
| 1258 | }
|
---|
| 1259 |
|
---|
| 1260 |
|
---|
| 1261 | /*
|
---|
| 1262 | * Calculate interpolated values of the spline function (defined via p_cntr
|
---|
| 1263 | * and the second derivatives dxdt2[] and dydt2[]). The number of tabulated
|
---|
| 1264 | * values is n. On an equidistant grid n_intpol values are calculated.
|
---|
| 1265 | */
|
---|
| 1266 | static int
|
---|
| 1267 | CubicEval(origPts, nOrigPts, intpPts, nIntpPts, spline)
|
---|
| 1268 | Point2D origPts[];
|
---|
| 1269 | int nOrigPts;
|
---|
| 1270 | Point2D intpPts[];
|
---|
| 1271 | int nIntpPts;
|
---|
| 1272 | CubicSpline spline[];
|
---|
| 1273 | {
|
---|
| 1274 | double t, tSkip, tMax;
|
---|
| 1275 | Point2D p, q;
|
---|
| 1276 | double d, hx, dx0, dx01, hy, dy0, dy01;
|
---|
| 1277 | register int i, j, count;
|
---|
| 1278 |
|
---|
| 1279 | /* Sum the lengths of all the segments (intervals). */
|
---|
| 1280 | tMax = 0.0;
|
---|
| 1281 | for (i = 0; i < nOrigPts - 1; i++) {
|
---|
| 1282 | tMax += spline[i].t;
|
---|
| 1283 | }
|
---|
| 1284 |
|
---|
| 1285 | /* Need a better way of doing this... */
|
---|
| 1286 |
|
---|
| 1287 | /* The distance between interpolated points */
|
---|
| 1288 | tSkip = (1. - 1e-7) * tMax / (nIntpPts - 1);
|
---|
| 1289 |
|
---|
| 1290 | t = 0.0; /* Spline parameter value. */
|
---|
| 1291 | q = origPts[0];
|
---|
| 1292 | count = 0;
|
---|
| 1293 |
|
---|
| 1294 | intpPts[count++] = q; /* First point. */
|
---|
| 1295 | t += tSkip;
|
---|
| 1296 |
|
---|
| 1297 | for (i = 0, j = 1; j < nOrigPts; i++, j++) {
|
---|
| 1298 | d = spline[i].t; /* Interval length */
|
---|
| 1299 | p = q;
|
---|
| 1300 | q = origPts[i+1];
|
---|
| 1301 | hx = (q.x - p.x) / d;
|
---|
| 1302 | hy = (q.y - p.y) / d;
|
---|
| 1303 | dx0 = (spline[j].x + 2 * spline[i].x) / 6.0;
|
---|
| 1304 | dy0 = (spline[j].y + 2 * spline[i].y) / 6.0;
|
---|
| 1305 | dx01 = (spline[j].x - spline[i].x) / (6.0 * d);
|
---|
| 1306 | dy01 = (spline[j].y - spline[i].y) / (6.0 * d);
|
---|
| 1307 | while (t <= spline[i].t) { /* t in current interval ? */
|
---|
| 1308 | p.x += t * (hx + (t - d) * (dx0 + t * dx01));
|
---|
| 1309 | p.y += t * (hy + (t - d) * (dy0 + t * dy01));
|
---|
| 1310 | intpPts[count++] = p;
|
---|
| 1311 | t += tSkip;
|
---|
| 1312 | }
|
---|
| 1313 | /* Parameter t relative to start of next interval */
|
---|
| 1314 | t -= spline[i].t;
|
---|
| 1315 | }
|
---|
| 1316 | return count;
|
---|
| 1317 | }
|
---|
| 1318 |
|
---|
| 1319 | /*
|
---|
| 1320 | * Generate a cubic spline curve through the points (x_i,y_i) which are
|
---|
| 1321 | * stored in the linked list p_cntr.
|
---|
| 1322 | * The spline is defined as a 2d-function s(t) = (x(t),y(t)), where the
|
---|
| 1323 | * parameter t is the length of the linear stroke.
|
---|
| 1324 | */
|
---|
| 1325 | int
|
---|
| 1326 | Blt_NaturalParametricSpline(origPts, nOrigPts, extsPtr, isClosed,
|
---|
| 1327 | intpPts, nIntpPts)
|
---|
| 1328 | Point2D origPts[];
|
---|
| 1329 | int nOrigPts;
|
---|
| 1330 | Extents2D *extsPtr;
|
---|
| 1331 | int isClosed;
|
---|
| 1332 | Point2D *intpPts;
|
---|
| 1333 | int nIntpPts;
|
---|
| 1334 | {
|
---|
| 1335 | double unitX, unitY; /* To define norm (x,y)-plane */
|
---|
| 1336 | CubicSpline *spline;
|
---|
| 1337 | int result;
|
---|
| 1338 |
|
---|
| 1339 | if (nOrigPts < 3) {
|
---|
| 1340 | return 0;
|
---|
| 1341 | }
|
---|
| 1342 | if (isClosed) {
|
---|
| 1343 | origPts[nOrigPts].x = origPts[0].x;
|
---|
| 1344 | origPts[nOrigPts].y = origPts[0].y;
|
---|
| 1345 | nOrigPts++;
|
---|
| 1346 | }
|
---|
| 1347 | /* Width and height of the grid is used at unit length (2d-norm) */
|
---|
| 1348 | unitX = extsPtr->right - extsPtr->left;
|
---|
| 1349 | unitY = extsPtr->bottom - extsPtr->top;
|
---|
| 1350 |
|
---|
| 1351 | if (unitX < FLT_EPSILON) {
|
---|
| 1352 | unitX = FLT_EPSILON;
|
---|
| 1353 | }
|
---|
| 1354 | if (unitY < FLT_EPSILON) {
|
---|
| 1355 | unitY = FLT_EPSILON;
|
---|
| 1356 | }
|
---|
| 1357 | /* Calculate parameters for cubic spline:
|
---|
| 1358 | * t = arc length of interval.
|
---|
| 1359 | * dxdt2 = second derivatives of x with respect to t,
|
---|
| 1360 | * dydt2 = second derivatives of y with respect to t,
|
---|
| 1361 | */
|
---|
| 1362 | spline = CubicSlopes(origPts, nOrigPts, isClosed, unitX, unitY);
|
---|
| 1363 | if (spline == NULL) {
|
---|
| 1364 | return 0;
|
---|
| 1365 | }
|
---|
| 1366 | result= CubicEval(origPts, nOrigPts, intpPts, nIntpPts, spline);
|
---|
| 1367 | Blt_Free(spline);
|
---|
| 1368 | return result;
|
---|
| 1369 | }
|
---|
| 1370 |
|
---|
| 1371 | static void
|
---|
| 1372 | CatromCoeffs(p, a, b, c, d)
|
---|
| 1373 | Point2D *p;
|
---|
| 1374 | Point2D *a, *b, *c, *d;
|
---|
| 1375 | {
|
---|
| 1376 | a->x = -p[0].x + 3.0 * p[1].x - 3.0 * p[2].x + p[3].x;
|
---|
| 1377 | b->x = 2.0 * p[0].x - 5.0 * p[1].x + 4.0 * p[2].x - p[3].x;
|
---|
| 1378 | c->x = -p[0].x + p[2].x;
|
---|
| 1379 | d->x = 2.0 * p[1].x;
|
---|
| 1380 | a->y = -p[0].y + 3.0 * p[1].y - 3.0 * p[2].y + p[3].y;
|
---|
| 1381 | b->y = 2.0 * p[0].y - 5.0 * p[1].y + 4.0 * p[2].y - p[3].y;
|
---|
| 1382 | c->y = -p[0].y + p[2].y;
|
---|
| 1383 | d->y = 2.0 * p[1].y;
|
---|
| 1384 | }
|
---|
| 1385 |
|
---|
| 1386 | /*
|
---|
| 1387 | *----------------------------------------------------------------------
|
---|
| 1388 | *
|
---|
| 1389 | * Blt_ParametricCatromSpline --
|
---|
| 1390 | *
|
---|
| 1391 | * Computes a spline based upon the data points, returning a new
|
---|
| 1392 | * (larger) coordinate array or points.
|
---|
| 1393 | *
|
---|
| 1394 | * Results:
|
---|
| 1395 | * None.
|
---|
| 1396 | *
|
---|
| 1397 | *----------------------------------------------------------------------
|
---|
| 1398 | */
|
---|
| 1399 | int
|
---|
| 1400 | Blt_CatromParametricSpline(points, nPoints, intpPts, nIntpPts)
|
---|
| 1401 | Point2D *points;
|
---|
| 1402 | int nPoints;
|
---|
| 1403 | Point2D *intpPts;
|
---|
| 1404 | int nIntpPts;
|
---|
| 1405 | {
|
---|
| 1406 | register int i;
|
---|
| 1407 | Point2D *origPts;
|
---|
| 1408 | double t;
|
---|
| 1409 | int interval;
|
---|
| 1410 | Point2D a, b, c, d;
|
---|
| 1411 |
|
---|
| 1412 | assert(nPoints > 0);
|
---|
| 1413 | /*
|
---|
| 1414 | * The spline is computed in screen coordinates instead of data
|
---|
| 1415 | * points so that we can select the abscissas of the interpolated
|
---|
| 1416 | * points from each pixel horizontally across the plotting area.
|
---|
| 1417 | */
|
---|
| 1418 | origPts = Blt_Malloc((nPoints + 4) * sizeof(Point2D));
|
---|
| 1419 | memcpy(origPts + 1, points, sizeof(Point2D) * nPoints);
|
---|
| 1420 |
|
---|
| 1421 | origPts[0] = origPts[1];
|
---|
| 1422 | origPts[nPoints + 2] = origPts[nPoints + 1] = origPts[nPoints];
|
---|
| 1423 |
|
---|
| 1424 | for (i = 0; i < nIntpPts; i++) {
|
---|
| 1425 | interval = (int)intpPts[i].x;
|
---|
| 1426 | t = intpPts[i].y;
|
---|
| 1427 | assert(interval < nPoints);
|
---|
| 1428 | CatromCoeffs(origPts + interval, &a, &b, &c, &d);
|
---|
| 1429 | intpPts[i].x = (d.x + t * (c.x + t * (b.x + t * a.x))) / 2.0;
|
---|
| 1430 | intpPts[i].y = (d.y + t * (c.y + t * (b.y + t * a.y))) / 2.0;
|
---|
| 1431 | }
|
---|
| 1432 | Blt_Free(origPts);
|
---|
| 1433 | return 1;
|
---|
| 1434 | }
|
---|