# Coverage for pygeodesy/simplify.py : 96%

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 | # -*- coding: utf-8 -*- u'''Seven functions to I{simplify} or linearize a path of C{LatLon} points. Each of the I{simplify} functions is based on a different algorithm and produces different simplified results in (very) different run times for the same path of C{LatLon} points. Function L{simplify1} eliminates points based on edge lengths shorter than a given tolerance. The functions L{simplifyRDP} and L{simplifyRDPm} use the original, respectively modified Ramer-Douglas-Peucker (RDP) algorithm, iteratively finding the point farthest from each path edge. The difference is that function L{simplifyRDP} exhaustively searches the most distant point in each iteration, while modified L{simplifyRDPm} stops at the first point exceeding the distance tolerance. Function L{simplifyRW} use the Reumann-Witkam method, sliding a "pipe" over each path edge, removing all subsequent points within, closer than the pipe radius up to the first point outside the pipe. Functions L{simplifyVW} and L{simplifyVWm} are based on the original, respectively modified Visvalingam-Whyatt (VW) method using the area of the triangle formed by three neigboring points. Function L{simplifyVW} removes only a single point per iteration, while modified L{simplifyVWm} eliminates in each iteration all points with a triangular area not exceeding the tolerance. Functions L{simplifyRDP}, L{simplifyRDPm} and L{simplifyRW} provide keyword argument I{shortest} to select the computation of the distance between a point and a path edge. If C{True}, use the shortest distance to the path edge or path end points, if C{False} use the perpendicular distance to the extended path edge line. Keyword argument B{C{radius}} of all fuctions is set to the mean earth radius in meter. Other units can be choosen, provided that the radius and tolerance are always specified in the same units. Use keyword argument B{C{indices}}=C{True} in any function to return a list of simplified point I{indices} instead of the simplified points. The first and last index are always the first and last original index. Finally, any additional keyword arguments B{C{options}} to all functions are passed thru to function L{equirectangular_} to specify the distance approximation. To process C{NumPy} arrays containing rows of lat-, longitude and possibly other values, use class L{Numpy2LatLon} to wrap the C{NumPy} array into I{on-the-fly-LatLon} points. Pass the L{Numpy2LatLon} instance to any I{simplify} function and the returned result will be a C{NumPy} array containing the simplified subset, a partial copy of the original C{NumPy} array. Use keyword argument B{C{indices}}=C{True} to return a list of array row indices inlieu of the simplified array subset. See: - U{https://Bost.Ocks.org/mike/simplify} - U{https://WikiPedia.org/wiki/Ramer-Douglas-Peucker_algorithm} - U{https://hydra.Hull.ac.UK/resources/hull:8338} - U{https://psimpl.SourceForge.net/reumann-witkam.html} - U{https://www.CS.UBC.CA/cgi-bin/tr/1992/TR-92-07.pdf} - U{https://GitHub.com/FlorianWilhelm/gps_data_with_python} - U{https://www.BDCC.co.UK/Gmaps/GDouglasPeuker.js} - U{https://GitHub.com/mourner/simplify-js} - U{https://GitHub.com/OmarEstrella/simplify.py} - U{https://PyPI.org/project/rdp} - U{https://PyPI.org/project/visvalingam} - U{https://PyPI.org/project/simplification} @newfield example: Example, Examples ''' from pygeodesy.basics import EPS, R_M, len2 from pygeodesy.formy import equirectangular_ from pygeodesy.lazily import _ALL_LAZY from pygeodesy.utily import isNumpy2, isTuple2 from math import degrees, radians, sqrt __all__ = _ALL_LAZY.simplify __version__ = '20.03.19' # try: # from collections import namedtuple # _T2 = namedtuple('_T2', 'ix, h2') # except ImportError: # class _T2(object): # ... # namedtuple not used because (a) values can not # be updated and (b) it produces PyChecker warning # "<string>:28: self is not first method argument" # which can not be suppressed by option --stdlib class _T2(object): '''(INTERNAL) VW 2-tuple (index, area). ''' __slots__ = ('ix', 'h2') def __init__(self, ix, h2): self.ix = ix self.h2 = h2 class _Sy(object): '''(INTERNAL) Simplify state. ''' d2i = None # d2iP or d2iS d2yxse = () eps = EPS # system epsilon indices = False n = 0 options = {} pts = [] radius = R_M # mean earth radius r = {} # RDP indices or VW 2-tuples s2 = EPS # tolerance squared s2e = EPS # sentinel subset = None # isNumpy2 or isTuple2 def __init__(self, points, tolerance, radius, shortest, indices, **options): '''New C{Simplify} state. ''' n, self.pts = len2(points) if n > 0: self.n = n self.r = {0: True, n-1: True} # dict to avoid duplicates if isNumpy2(points) or isTuple2(points): # NOT self.pts self.subset = points.subset if indices: self.indices = True if radius: self.radius = float(radius) if self.radius < self.eps: raise ValueError('%s too small: %.6e' % ('radius', radius)) if options: self.options = options # tolerance converted to degrees squared self.s2 = degrees(tolerance / self.radius)**2 if min(self.s2, tolerance) < self.eps: raise ValueError('%s too small: %.6e' % ('tolerance', tolerance)) self.s2e = self.s2 + 1 # sentinel # compute either the shortest or perpendicular distance self.d2i = self.d2iS if shortest else self.d2iP # PYCHOK false def d21(self, s, e): '''Set path edge or line thru points[s] to -[e]. ''' d21, y21, x21, _ = self.d2yxu(s, e) self.d2yxse = d21, y21, x21, s, e return d21 > self.eps def d2ih(self, n, m, brk): '''Find the tallest distance among all points[n..m] to points[s] exceeding the tolerance. ''' _, _, _, s, _ = self.d2yxse eps, d2yxu = self.eps, self.d2yxu t2, t = self.s2, 0 # tallest for i in range(n, m): d2, _, _, _ = d2yxu(s, i) if d2 > t2: t2, t = d2, i if brk and d2 > eps: break return t2, t def d2iP(self, n, m, brk): '''Find the tallest perpendicular distance among all points[n..m] to the path edge or line thru points[s] to -[e] exceeding the tolerance. ''' d21, y21, x21, s, _ = self.d2yxse eps, d2yxu = self.eps, self.d2yxu t2, t = self.s2, 0 # tallest for i in range(n, m): d2, y01, x01, _ = d2yxu(s, i) if d2 > eps: # perpendicular distance squared d2 = (y01 * x21 - x01 * y21)**2 / d21 if d2 > t2: t2, t = d2, i if brk: break return t2, t def d2iS(self, n, m, brk): '''Find the tallest shortest distance among all points[n..m] to the path edge or line thru points[s] to -[e] exceeding the tolerance. ''' # point (x, y) on axis rotated by angle a ccw: # x' = y * sin(a) + x * cos(a) # y' = y * cos(a) - x * sin(a) # # distance (w) along and perpendicular (h) to # a line thru point (dx, dy) and the origin: # w = (y * dy + x * dx) / hypot(dx, dy) # h = (y * dx - x * dy) / hypot(dx, dy) d21, y21, x21, s, e = self.d2yxse eps, d2yxu = self.eps, self.d2yxu t2, t = self.s2, 0 # tallest for i in range(n, m): # distance points[i] to -[s] d2, y01, x01, _ = d2yxu(s, i) if d2 > eps: w = y01 * y21 + x01 * x21 if w > 0: if w < d21: # perpendicular distance squared d2 = (y01 * x21 - x01 * y21)**2 / d21 else: # distance points[i] to -[e] d2, _, _, _ = d2yxu(e, i) if d2 > t2: t2, t = d2, i if brk: break return t2, t def d2yxu(self, i, j): '''Return distance squared, points[i] to -[j] deltas and longitudinal unrollment. ''' p1 = self.pts[i] p2 = self.pts[j] return equirectangular_(p1.lat, p1.lon, p2.lat, p2.lon, **self.options) def h2t(self, i1, i0, i2): '''Compute the Visvalingam-Whyatt triangular area, points[i0] is the top and points[i1] to -[i2] form the base of the triangle. ''' d21, y21, x21 , _= self.d2yxu(i1, i2) if d21 > self.eps: d01, y01, x01, _ = self.d2yxu(i1, i0) if d01 > self.eps: h2 = abs(y01 * x21 - x01 * y21) # triangle height h = h2 / sqrt(d21) and # the area = h * sqrt(d21) / 2 == h2 / 2 return h2 # double triangle area return 0 def points(self, r): '''Return the list of simplified points or indices. ''' r = sorted(r.keys()) if self.indices: return list(r) elif self.subset: return self.subset(r) else: return [self.pts[i] for i in r] def rdp(self, modified): '''Ramer-Douglas-Peucker (RDP) simplification of a path of C{LatLon} points. @arg modified: Use modified RDP (C{bool}). ''' n, r = self.n, self.r if n > 1: s2, d21 = self.s2, self.d21 d2i, d2ih = self.d2i, self.d2ih se = [(0, n-1)] while se: s, e = se.pop() if e > (s + 1): if d21(s, e): # points[] to edge [s, e] d2, i = d2i(s+1, e, modified) else: # points[] to point [s] d2, i = d2ih(s+1, e, modified) if d2 > s2 and i > 0: r[s] = r[i] = True se.append((i, e)) if not modified: se.append((s, i)) else: r[s] = True return self.points(r) def rm1(self, m, tol): '''Eliminate one Visvalingam-Whyatt point and recomputes the trangular area of both neighboring points, but removes those too unless the recomputed area exceeds the tolerance. ''' h2t, r = self.h2t, self.r r.pop(m) for n in (m, m - 1): while 0 < n < (len(r) - 1): h2 = h2t(r[n-1].ix, r[n].ix, r[n+1].ix) if h2 > tol: r[n].h2 = h2 break # while else: r.pop(n) def rm2(self, tol): '''Eliminate all Visvalingam-Whyatt points with a triangular area not exceeding the tolerance. ''' r, rm1 = self.r, self.rm1 i = len(r) - 1 while i > 1: i -= 1 if r[i].h2 <= tol: rm1(i, tol) i = min(i, len(r) - 1) def vwn(self): '''Initialize Visvalingam-Whyatt as list of 2-tuples _T2(ix, h2) where ix is the points[] index and h2 is the triangular area I{(times 2)} of that point. ''' n, h2t, s2e = self.n, self.h2t, self.s2e if n > 2: self.r = [_T2(0, s2e)] self.r.extend(_T2(i, h2t(i-1, i, i+1)) for i in range(1, n-1)) self.r.append(_T2(n-1, s2e)) elif n > 0: self.r = [_T2(i, s2e) for i in range(0, n)] # PYCHOK false else: self.r = [] return len(self.r) def vwr(self, attr): '''Return the Visvalingam-Whyatt results, optionally including the triangular area (in meters) as attribute attr to each simplified point. ''' pts, r = self.pts, self.r # double check the minimal triangular area assert min(t2.h2 for t2 in r) > self.s2 > 0 if attr: # return the trangular area (actually # the sqrt of double the triangular area) # converted back from degrees to meter if isNumpy2(pts): raise AttributeError('%r invalid' % (attr,)) m = radians(1.0) * self.radius r[0].h2 = r[-1].h2 = 0 # zap sentinels for t2 in r: # convert back to meter setattr(pts[t2.ix], attr, sqrt(t2.h2) * m) # double check for duplicates n = len(r) r = dict((t2.ix, True) for t2 in r) assert len(r) == n return self.points(r) def simplify1(points, distance, radius=R_M, indices=False, **options): '''Basic simplification of a path of C{LatLon} points. Eliminates any points closer together than the given distance tolerance. @arg points: Path points (C{LatLon}[]). @arg distance: Tolerance (C{meter}, same units as B{C{radius}}). @kwarg radius: Mean earth radius (C{meter}). @kwarg indices: Optionally return the simplified point indices instead of the simplified points (C{bool}). @kwarg options: Optional keyword arguments passed thru to function L{equirectangular_}. @return: Simplified points (C{LatLon}[]). @raise LimitError: Lat- and/or longitudinal delta exceeds the B{C{limit}}, see function L{equirectangular_}. @raise ValueError: Tolerance B{C{distance}} or B{C{radius}} too small. ''' S = _Sy(points, distance, radius, True, indices, **options) n, r = S.n, S.r if n > 1: s2, d2yxu = S.s2, S.d2yxu i = 0 for j in range(1, n): d2, _, _, _= d2yxu(i, j) if d2 > s2: r[j] = True i = j return S.points(r) def simplifyRDP(points, distance, radius=R_M, shortest=False, indices=False, **options): '''Ramer-Douglas-Peucker (RDP) simplification of a path of C{LatLon} points. Eliminates any points too close together or closer to an edge than the given distance tolerance. This C{RDP} method exhaustively searches for the point with the largest distance, resulting in worst-case complexity M{O(n**2)} where M{n} is the number of points. @arg points: Path points (C{LatLon}[]). @arg distance: Tolerance (C{meter}, same units as B{C{radius}}). @kwarg radius: Mean earth radius (C{meter}). @kwarg shortest: Optional, shortest or perpendicular distance (C{bool}). @kwarg indices: Optionally return the simplified point indices instead of the simplified points (C{bool}). @kwarg options: Optional keyword arguments passed thru to function L{equirectangular_}. @return: Simplified points (C{LatLon}[]). @raise LimitError: Lat- and/or longitudinal delta exceeds the B{C{limit}}, see function L{equirectangular_}. @raise ValueError: Tolerance B{C{distance}} or B{C{radius}} too small. ''' S = _Sy(points, distance, radius, shortest, indices, **options) return S.rdp(False) def simplifyRDPm(points, distance, radius=R_M, shortest=False, indices=False, **options): '''Modified Ramer-Douglas-Peucker (RDPm) simplification of a path of C{LatLon} points. Eliminates any points too close together or closer to an edge than the given distance tolerance. This C{RDPm} method stops at the first point farther than the given distance tolerance, significantly reducing the run time (but producing results different from the original C{RDP} method). @arg points: Path points (C{LatLon}[]). @arg distance: Tolerance (C{meter}, same units as B{C{radius}}). @kwarg radius: Mean earth radius (C{meter}). @kwarg shortest: Optional, shortest or perpendicular distance (C{bool}). @kwarg indices: Optionally return the simplified point indices instead of the simplified points (C{bool}). @kwarg options: Optional keyword arguments passed thru to function L{equirectangular_}. @return: Simplified points (C{LatLon}[]). @raise LimitError: Lat- and/or longitudinal delta exceeds the B{C{limit}}, see function L{equirectangular_}. @raise ValueError: Tolerance B{C{distance}} or B{C{radius}} too small. ''' S = _Sy(points, distance, radius, shortest, indices, **options) return S.rdp(True) def simplifyRW(points, pipe, radius=R_M, shortest=False, indices=False, **options): '''Reumann-Witkam (RW) simplification of a path of C{LatLon} points. Eliminates any points too close together or within the given pipe tolerance along an edge. @arg points: Path points (C{LatLon}[]). @arg pipe: Half pipe width (C{meter}, same units as B{C{radius}}). @kwarg radius: Mean earth radius (C{meter}). @kwarg shortest: Optional, shortest or perpendicular distance (C{bool}). @kwarg indices: Optionally return the simplified point indices instead of the simplified points (C{bool}). @kwarg options: Optional keyword arguments passed thru to function L{equirectangular_}. @return: Simplified points (C{LatLon}[]). @raise LimitError: Lat- and/or longitudinal delta exceeds the B{C{limit}}, see function L{equirectangular_}. @raise ValueError: Tolerance B{C{pipe}} or B{C{radius}} too small. ''' S = _Sy(points, pipe, radius, shortest, indices, **options) n, r = S.n, S.r if n > 1: s2, d21, d2i = S.s2, S.d21, S.d2i s, e = 0, 1 while s < e < n: if d21(s, e): d2, i = d2i(e + 1, n, True) if d2 > s2 and i > 0: r[s] = r[i] = True s, e = i, i + 1 else: r[s] = True # r[n-1] = True break # while loop else: # drop points[e] e += 1 return S.points(r) def simplifyVW(points, area, radius=R_M, attr=None, indices=False, **options): '''Visvalingam-Whyatt (VW) simplification of a path of C{LatLon} points. Eliminates any points too close together or with a triangular area not exceeding the given area tolerance (squared). This C{VW} method exhaustively searches for the single point with the smallest triangular area, resulting in worst-case complexity M{O(n**2)} where M{n} is the number of points. @arg points: Path points (C{LatLon}[]). @arg area: Tolerance (C{meter}, same units as B{C{radius}}). @kwarg radius: Mean earth radius (C{meter}). @kwarg attr: Optional, points attribute save area value (C{str}). @kwarg indices: Optionally return the simplified point indices instead of the simplified points (C{bool}). @kwarg options: Optional keyword arguments passed thru to function L{equirectangular_}. @return: Simplified points (C{LatLon}[]). @raise AttributeError: If an B{C{attr}} is specified for I{Numpy2} B{C{points}}. @raise LimitError: Lat- and/or longitudinal delta exceeds the B{C{limit}}, see function L{equirectangular_}. @raise ValueError: Tolerance B{C{area}} or B{C{radius}} too small. ''' S = _Sy(points, area, radius, False, indices, **options) if S.vwn() > 2: # remove any points too close or # with a zero triangular area S.rm2(0) r, s2, s2e = S.r, S.s2, S.s2e # keep removing the point with the smallest # area until latter exceeds the tolerance while len(r) > 2: m, m2 = 0, s2e for i in range(1, len(r) - 1): h2 = r[i].h2 if h2 < m2: m, m2 = i, h2 if m2 > s2: break S.rm1(m, 0) return S.vwr(attr) def simplifyVWm(points, area, radius=R_M, attr=None, indices=False, **options): '''Modified Visvalingam-Whyatt (VWm) simplification of a path of C{LatLon} points. Eliminates any points too close together or with a triangular area not exceeding the given area tolerance (squared). This C{VWm} method removes all points with a triangular area below the tolerance in each iteration, significantly reducing the run time (but producing results different from the original C{VW} method). @arg points: Path points (C{LatLon}[]). @arg area: Tolerance (C{meter}, same units as B{C{radius}}). @kwarg radius: Mean earth radius (C{meter}). @kwarg attr: Optional attribute to save the area value (C{str}). @kwarg indices: Optionally return the simplified point indices instead of the simplified points (C{bool}). @kwarg options: Optional keyword arguments passed thru to function L{equirectangular_}. @return: Simplified points (C{LatLon}[]). @raise AttributeError: If an B{C{attr}} is specified for I{Numpy2} B{C{points}}. @raise LimitError: Lat- and/or longitudinal delta exceeds the B{C{limit}}, see function L{equirectangular_}. @raise ValueError: Tolerance B{C{area}} or B{C{radius}} too small. ''' S = _Sy(points, area, radius, False, indices, **options) if S.vwn() > 2: # remove all points with an area # not exceeding the tolerance S.rm2(S.s2) return S.vwr(attr) # **) MIT License # # Copyright (C) 2016-2020 -- mrJean1 at Gmail -- All Rights Reserved. # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included # in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS # OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL # THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR # OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, # ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR # OTHER DEALINGS IN THE SOFTWARE.