LSSTApplications  20.0.0
LSSTDataManagementBasePackage
ChebyshevBoundedField.cc
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23 
24 #include <memory>
25 
26 #include "ndarray/eigen.h"
35 
36 namespace lsst {
37 namespace afw {
38 
39 template std::shared_ptr<math::ChebyshevBoundedField> table::io::PersistableFacade<
40  math::ChebyshevBoundedField>::dynamicCast(std::shared_ptr<table::io::Persistable> const&);
41 
42 namespace math {
43 
45 
46 // ------------------ Constructors and helpers ---------------------------------------------------------------
47 
48 namespace {
49 
50 // Compute an affine transform that maps an arbitrary box to [-1,1]x[-1,1]
51 lsst::geom::AffineTransform makeChebyshevRangeTransform(lsst::geom::Box2D const bbox) {
53  lsst::geom::LinearTransform::makeScaling(2.0 / bbox.getWidth(), 2.0 / bbox.getHeight()),
54  lsst::geom::Extent2D(-(2.0 * bbox.getCenterX()) / bbox.getWidth(),
55  -(2.0 * bbox.getCenterY()) / bbox.getHeight()));
56 }
57 
58 } // namespace
59 
61  ndarray::Array<double const, 2, 2> const& coefficients)
62  : BoundedField(bbox),
63  _toChebyshevRange(makeChebyshevRangeTransform(lsst::geom::Box2D(bbox))),
64  _coefficients(coefficients) {}
65 
67  : BoundedField(bbox), _toChebyshevRange(makeChebyshevRangeTransform(lsst::geom::Box2D(bbox))) {}
68 
69 ChebyshevBoundedField::ChebyshevBoundedField(ChebyshevBoundedField const&) = default;
70 ChebyshevBoundedField::ChebyshevBoundedField(ChebyshevBoundedField&&) = default;
72 
73 // ------------------ fit() and helpers ---------------------------------------------------------------------
74 
75 namespace {
76 
78 typedef detail::TrapezoidalPacker Packer;
79 
80 // fill an array with 1-d Chebyshev functions of the 1st kind T(x), evaluated at the given point x
81 void evaluateBasis1d(ndarray::Array<double, 1, 1> const& t, double x) {
82  int const n = t.getSize<0>();
83  if (n > 0) {
84  t[0] = 1.0;
85  }
86  if (n > 1) {
87  t[1] = x;
88  }
89  for (int i = 2; i < n; ++i) {
90  t[i] = 2.0 * x * t[i - 1] - t[i - 2];
91  }
92 }
93 
94 // Create a matrix of 2-d Chebyshev functions evaluated at a set of positions, with
95 // Chebyshev order along columns and evaluation positions along rows. We pack the
96 // 2-d functions using the TrapezoidalPacker class, because we don't want any columns
97 // that correspond to coefficients that should be set to zero.
98 ndarray::Array<double, 2, 2> makeMatrix(ndarray::Array<double const, 1> const& x,
99  ndarray::Array<double const, 1> const& y,
100  lsst::geom::AffineTransform const& toChebyshevRange,
101  Packer const& packer, Control const& ctrl) {
102  int const nPoints = x.getSize<0>();
103  ndarray::Array<double, 1, 1> tx = ndarray::allocate(packer.nx);
104  ndarray::Array<double, 1, 1> ty = ndarray::allocate(packer.ny);
105  ndarray::Array<double, 2, 2> out = ndarray::allocate(nPoints, packer.size);
106  // Loop over x and y together, computing T_i(x) and T_j(y) arrays for each point,
107  // then packing them together.
108  for (int p = 0; p < nPoints; ++p) {
109  lsst::geom::Point2D sxy = toChebyshevRange(lsst::geom::Point2D(x[p], y[p]));
110  evaluateBasis1d(tx, sxy.getX());
111  evaluateBasis1d(ty, sxy.getY());
112  packer.pack(out[p], tx, ty); // this sets a row of out to the packed outer product of tx and ty
113  }
114  return out;
115 }
116 
117 // Create a matrix of 2-d Chebyshev functions evaluated on a grid of positions, with
118 // Chebyshev order along columns and evaluation positions along rows. We pack the
119 // 2-d functions using the TrapezoidalPacker class, because we don't want any columns
120 // that correspond to coefficients that should be set to zero.
121 ndarray::Array<double, 2, 2> makeMatrix(lsst::geom::Box2I const& bbox,
122  lsst::geom::AffineTransform const& toChebyshevRange,
123  Packer const& packer, Control const& ctrl) {
124  // Create a 2-d array that contains T_j(x) for each x value, with x values in rows and j in columns
125  ndarray::Array<double, 2, 2> tx = ndarray::allocate(bbox.getWidth(), packer.nx);
126  for (int x = bbox.getBeginX(), p = 0; p < bbox.getWidth(); ++p, ++x) {
127  evaluateBasis1d(tx[p], toChebyshevRange[lsst::geom::AffineTransform::XX] * x +
128  toChebyshevRange[lsst::geom::AffineTransform::X]);
129  }
130 
131  // Loop over y values, and at each point, compute T_i(y), then loop over x and multiply by the T_j(x)
132  // we already computed and stored above.
133  ndarray::Array<double, 2, 2> out = ndarray::allocate(bbox.getArea(), packer.size);
134  ndarray::Array<double, 2, 2>::Iterator outIter = out.begin();
135  ndarray::Array<double, 1, 1> ty = ndarray::allocate(ctrl.orderY + 1);
136  for (int y = bbox.getBeginY(), i = 0; i < bbox.getHeight(); ++i, ++y) {
137  evaluateBasis1d(ty, toChebyshevRange[lsst::geom::AffineTransform::YY] * y +
138  toChebyshevRange[lsst::geom::AffineTransform::Y]);
139  for (int j = 0; j < bbox.getWidth(); ++j, ++outIter) {
140  // this sets a row of out to the packed outer product of tx and ty
141  packer.pack(*outIter, tx[j], ty);
142  }
143  }
144  return out;
145 }
146 
147 } // namespace
148 
150  ndarray::Array<double const, 1> const& x,
151  ndarray::Array<double const, 1> const& y,
152  ndarray::Array<double const, 1> const& z,
153  Control const& ctrl) {
154  // Initialize the result object, so we can make use of the AffineTransform it builds
156  // This packer object knows how to map the 2-d Chebyshev functions onto a 1-d array,
157  // using only those that the control says should have nonzero coefficients.
158  Packer const packer(ctrl);
159  // Create a "design matrix" for the linear least squares problem (A in min||Ax-b||)
160  ndarray::Array<double, 2, 2> matrix = makeMatrix(x, y, result->_toChebyshevRange, packer, ctrl);
161  // Solve the linear least squares problem.
163  // Unpack the solution into a 2-d matrix, with zeros for values we didn't fit.
164  result->_coefficients = packer.unpack(lstsq.getSolution());
165  return result;
166 }
167 
169  ndarray::Array<double const, 1> const& x,
170  ndarray::Array<double const, 1> const& y,
171  ndarray::Array<double const, 1> const& z,
172  ndarray::Array<double const, 1> const& w,
173  Control const& ctrl) {
174  // Initialize the result object, so we can make use of the AffineTransform it builds
176  // This packer object knows how to map the 2-d Chebyshev functions onto a 1-d array,
177  // using only those that the control says should have nonzero coefficients.
178  Packer const packer(ctrl);
179  // Create a "design matrix" for the linear least squares problem ('A' in min||Ax-b||)
180  ndarray::Array<double, 2, 2> matrix = makeMatrix(x, y, result->_toChebyshevRange, packer, ctrl);
181  // We want to do weighted least squares, so we multiply both the data vector 'b' and the
182  // matrix 'A' by the weights.
183  ndarray::asEigenArray(matrix).colwise() *= ndarray::asEigenArray(w);
184  ndarray::Array<double, 1, 1> wz = ndarray::copy(z);
185  ndarray::asEigenArray(wz) *= ndarray::asEigenArray(w);
186  // Solve the linear least squares problem.
188  // Unpack the solution into a 2-d matrix, with zeros for values we didn't fit.
189  result->_coefficients = packer.unpack(lstsq.getSolution());
190  return result;
191 }
192 
193 template <typename T>
195  Control const& ctrl) {
196  // Initialize the result object, so we can make use of the AffineTransform it builds
199  // This packer object knows how to map the 2-d Chebyshev functions onto a 1-d array,
200  // using only those that the control says should have nonzero coefficients.
201  Packer const packer(ctrl);
202  ndarray::Array<double, 2, 2> matrix = makeMatrix(bbox, result->_toChebyshevRange, packer, ctrl);
203  // Flatten the data image into a 1-d vector.
204  ndarray::Array<double, 2, 2> imgCopy = ndarray::allocate(img.getArray().getShape());
205  imgCopy.deep() = img.getArray();
206  ndarray::Array<double const, 1, 1> z = ndarray::flatten<1>(imgCopy);
207  // Solve the linear least squares problem.
209  // Unpack the solution into a 2-d matrix, with zeros for values we didn't fit.
210  result->_coefficients = packer.unpack(lstsq.getSolution());
211  return result;
212 }
213 
214 // ------------------ modifier factories ---------------------------------------------------------------
215 
217  if (static_cast<std::size_t>(ctrl.orderX) >= _coefficients.getSize<1>()) {
219  (boost::format("New x order (%d) exceeds old x order (%d)") % ctrl.orderX %
220  (_coefficients.getSize<1>() - 1))
221  .str());
222  }
223  if (static_cast<std::size_t>(ctrl.orderY) >= _coefficients.getSize<0>()) {
225  (boost::format("New y order (%d) exceeds old y order (%d)") % ctrl.orderY %
226  (_coefficients.getSize<0>() - 1))
227  .str());
228  }
229  ndarray::Array<double, 2, 2> coefficients = ndarray::allocate(ctrl.orderY + 1, ctrl.orderX + 1);
230  coefficients.deep() = _coefficients[ndarray::view(0, ctrl.orderY + 1)(0, ctrl.orderX + 1)];
231  if (ctrl.triangular) {
232  Packer packer(ctrl);
233  ndarray::Array<double, 1, 1> packed = ndarray::allocate(packer.size);
234  packer.pack(packed, coefficients);
235  packer.unpack(coefficients, packed);
236  }
237  return std::make_shared<ChebyshevBoundedField>(getBBox(), coefficients);
238 }
239 
241  return std::make_shared<ChebyshevBoundedField>(bbox, _coefficients);
242 }
243 
244 // ------------------ evaluate() and helpers ---------------------------------------------------------------
245 
246 namespace {
247 
248 // To evaluate a 1-d Chebyshev function without needing to have workspace, we use the
249 // Clenshaw algorith, which is like going through the recurrence relation in reverse.
250 // The CoeffGetter argument g is something that behaves like an array, providing access
251 // to the coefficients.
252 template <typename CoeffGetter>
253 double evaluateFunction1d(CoeffGetter g, double x, int size) {
254  double b_kp2 = 0.0, b_kp1 = 0.0;
255  for (int k = (size - 1); k > 0; --k) {
256  double b_k = g[k] + 2 * x * b_kp1 - b_kp2;
257  b_kp2 = b_kp1;
258  b_kp1 = b_k;
259  }
260  return g[0] + x * b_kp1 - b_kp2;
261 }
262 
263 // This class imitates a 1-d array, by running evaluateFunction1d on a nested dimension;
264 // this lets us reuse the logic in evaluateFunction1d for both dimensions. Essentially,
265 // we run evaluateFunction1d on a column of coefficients to evaluate T_i(x), then pass
266 // the result of that to evaluateFunction1d with the results as the "coefficients" associated
267 // with the T_j(y) functions.
268 struct RecursionArrayImitator {
269  double operator[](int i) const {
270  return evaluateFunction1d(coefficients[i], x, coefficients.getSize<1>());
271  }
272 
273  RecursionArrayImitator(ndarray::Array<double const, 2, 2> const& coefficients_, double x_)
274  : coefficients(coefficients_), x(x_) {}
275 
276  ndarray::Array<double const, 2, 2> coefficients;
277  double x;
278 };
279 
280 } // namespace
281 
283  lsst::geom::Point2D p = _toChebyshevRange(position);
284  return evaluateFunction1d(RecursionArrayImitator(_coefficients, p.getX()), p.getY(),
285  _coefficients.getSize<0>());
286 }
287 
288 // The integral of T_n(x) over [-1,1]:
289 // https://en.wikipedia.org/wiki/Chebyshev_polynomials#Differentiation_and_integration
290 double integrateTn(int n) {
291  if (n % 2 == 1)
292  return 0;
293  else
294  return 2.0 / (1.0 - double(n * n));
295 }
296 
298  double result = 0;
299  double determinant = getBBox().getArea() / 4.0;
300  for (ndarray::Size j = 0; j < _coefficients.getSize<0>(); j++) {
301  for (ndarray::Size i = 0; i < _coefficients.getSize<1>(); i++) {
302  result += _coefficients[j][i] * integrateTn(i) * integrateTn(j);
303  }
304  }
305  return result * determinant;
306 }
307 
308 double ChebyshevBoundedField::mean() const { return integrate() / getBBox().getArea(); }
309 
310 // ------------------ persistence ---------------------------------------------------------------------------
311 
312 namespace {
313 
314 struct PersistenceHelper {
315  table::Schema schema;
316  table::Key<int> orderX;
318  table::Key<table::Array<double> > coefficients;
319 
320  PersistenceHelper(int nx, int ny)
321  : schema(),
322  orderX(schema.addField<int>("order_x", "maximum Chebyshev function order in x")),
323  bbox(table::Box2IKey::addFields(schema, "bbox", "bounding box", "pixel")),
324  coefficients(schema.addField<table::Array<double> >(
325  "coefficients", "Chebyshev function coefficients, ordered by y then x", nx * ny)) {}
326 
327  PersistenceHelper(table::Schema const& s)
328  : schema(s), orderX(s["order_x"]), bbox(s["bbox"]), coefficients(s["coefficients"]) {}
329 };
330 
331 class ChebyshevBoundedFieldFactory : public table::io::PersistableFactory {
332 public:
333  explicit ChebyshevBoundedFieldFactory(std::string const& name)
334  : afw::table::io::PersistableFactory(name) {}
335 
336  std::shared_ptr<table::io::Persistable> read(InputArchive const& archive,
337  CatalogVector const& catalogs) const override {
338  LSST_ARCHIVE_ASSERT(catalogs.size() == 1u);
339  LSST_ARCHIVE_ASSERT(catalogs.front().size() == 1u);
340  table::BaseRecord const& record = catalogs.front().front();
341  PersistenceHelper const keys(record.getSchema());
342  lsst::geom::Box2I bbox(record.get(keys.bbox));
343  int nx = record.get(keys.orderX) + 1;
344  int ny = keys.coefficients.getSize() / nx;
345  LSST_ARCHIVE_ASSERT(nx * ny == keys.coefficients.getSize());
346  ndarray::Array<double, 2, 2> coefficients = ndarray::allocate(ny, nx);
347  ndarray::flatten<1>(coefficients) = record.get(keys.coefficients);
348  return std::make_shared<ChebyshevBoundedField>(bbox, coefficients);
349  }
350 };
351 
352 std::string getChebyshevBoundedFieldPersistenceName() { return "ChebyshevBoundedField"; }
353 
354 ChebyshevBoundedFieldFactory registration(getChebyshevBoundedFieldPersistenceName());
355 
356 } // namespace
357 
359  return getChebyshevBoundedFieldPersistenceName();
360 }
361 
362 std::string ChebyshevBoundedField::getPythonModule() const { return "lsst.afw.math"; }
363 
365  PersistenceHelper const keys(_coefficients.getSize<1>(), _coefficients.getSize<0>());
366  table::BaseCatalog catalog = handle.makeCatalog(keys.schema);
367  std::shared_ptr<table::BaseRecord> record = catalog.addNew();
368  record->set(keys.orderX, _coefficients.getSize<1>() - 1);
369  record->set(keys.bbox, getBBox());
370  (*record)[keys.coefficients].deep() = ndarray::flatten<1>(_coefficients);
371  handle.saveCatalog(catalog);
372 }
373 
374 // ------------------ operators -----------------------------------------------------------------------------
375 
377  return std::make_shared<ChebyshevBoundedField>(getBBox(), ndarray::copy(getCoefficients() * scale));
378 }
379 
381  auto rhsCasted = dynamic_cast<ChebyshevBoundedField const*>(&rhs);
382  if (!rhsCasted) return false;
383 
384  return (getBBox() == rhsCasted->getBBox()) &&
385  (_coefficients.getShape() == rhsCasted->_coefficients.getShape()) &&
386  all(equal(_coefficients, rhsCasted->_coefficients));
387 }
388 
389 std::string ChebyshevBoundedField::toString() const {
391  os << "ChebyshevBoundedField (" << _coefficients.getShape() << " coefficients in y,x)";
392  return os.str();
393 }
394 
395 // ------------------ explicit instantiation ----------------------------------------------------------------
396 
397 #ifndef DOXYGEN
398 
399 #define INSTANTIATE(T) \
400  template std::shared_ptr<ChebyshevBoundedField> ChebyshevBoundedField::fit(image::Image<T> const& image, \
401  Control const& ctrl)
402 
403 INSTANTIATE(float);
404 INSTANTIATE(double);
405 
406 #endif
407 } // namespace math
408 } // namespace afw
409 } // namespace lsst
y
int y
Definition: SpanSet.cc:49
lsst::afw::math::ChebyshevBoundedField::Control
ChebyshevBoundedFieldControl Control
Definition: ChebyshevBoundedField.h:79
lsst::afw::math::ChebyshevBoundedFieldControl
A control object used when fitting ChebyshevBoundedField to data (see ChebyshevBoundedField::fit)
Definition: ChebyshevBoundedField.h:38
std::string
STL class.
std::shared_ptr
STL class.
lsst::afw::math::ChebyshevBoundedFieldControl::orderX
int orderX
"maximum Chebyshev function order in x" ;
Definition: ChebyshevBoundedField.h:42
lsst::afw::math::BoundedField
An abstract base class for 2-d functions defined on an integer bounding boxes.
Definition: BoundedField.h:55
coefficients
ndarray::Array< double const, 2, 2 > coefficients
Definition: ChebyshevBoundedField.cc:276
lsst::afw::math::ChebyshevBoundedField::integrate
double integrate() const override
Compute the integral of this function over its bounding-box.
Definition: ChebyshevBoundedField.cc:297
lsst::afw::table::io::OutputArchiveHandle
An object passed to Persistable::write to allow it to persist itself.
Definition: OutputArchive.h:118
Persistable.cc
lsst::afw::math::ChebyshevBoundedField::truncate
std::shared_ptr< ChebyshevBoundedField > truncate(Control const &ctrl) const
Return a new ChebyshevBoudedField with maximum orders set by the given control object.
Definition: ChebyshevBoundedField.cc:216
lsst::afw::math::ChebyshevBoundedField::~ChebyshevBoundedField
~ChebyshevBoundedField() override
lsst::afw::table::io::OutputArchiveHandle::saveCatalog
void saveCatalog(BaseCatalog const &catalog)
Save a catalog in the archive.
Definition: OutputArchive.cc:211
pex.config.history.format
def format(config, name=None, writeSourceLine=True, prefix="", verbose=False)
Definition: history.py:174
lsst::afw
Definition: imageAlgorithm.dox:1
lsst::afw::math::ChebyshevBoundedField::fit
static std::shared_ptr< ChebyshevBoundedField > fit(lsst::geom::Box2I const &bbox, ndarray::Array< double const, 1 > const &x, ndarray::Array< double const, 1 > const &y, ndarray::Array< double const, 1 > const &z, Control const &ctrl)
Fit a Chebyshev approximation to non-gridded data with equal weights.
Definition: ChebyshevBoundedField.cc:149
lsst::afw::math::integrateTn
double integrateTn(int n)
Definition: ChebyshevBoundedField.cc:290
astshim.keyMap.keyMapContinued.keys
def keys(self)
Definition: keyMapContinued.py:6
lsst::afw::math::ChebyshevBoundedField::mean
double mean() const override
Compute the mean of this function over its bounding-box.
Definition: ChebyshevBoundedField.cc:308
lsst::afw::math::ChebyshevBoundedField::getPersistenceName
std::string getPersistenceName() const override
Return the unique name used to persist this object and look up its factory.
Definition: ChebyshevBoundedField.cc:358
CatalogVector.h
lsst::afw::math::detail::TrapezoidalPacker
A helper class ChebyshevBoundedField, for mapping trapezoidal matrices to 1-d arrays.
Definition: TrapezoidalPacker.h:90
INSTANTIATE
#define INSTANTIATE(FROMSYS, TOSYS)
Definition: Detector.cc:484
lsst::afw::geom.transform.transformContinued.name
string name
Definition: transformContinued.py:32
aggregates.h
lsst::afw::math::ChebyshevBoundedField::operator*
std::shared_ptr< BoundedField > operator*(double const scale) const override
Return a scaled BoundedField.
Definition: ChebyshevBoundedField.cc:376
bbox
table::Box2IKey bbox
Definition: ChebyshevBoundedField.cc:317
lsst::afw::math::LeastSquares
Solver for linear least-squares problems.
Definition: LeastSquares.h:67
lsst::afw::math::ChebyshevBoundedField::getCoefficients
ndarray::Array< double const, 2, 2 > getCoefficients() const
Return the coefficient matrix.
Definition: ChebyshevBoundedField.h:180
lsst::geom::LinearTransform::makeScaling
static LinearTransform makeScaling(double s) noexcept
Definition: LinearTransform.h:94
lsst::afw::math::ChebyshevBoundedField
A BoundedField based on 2-d Chebyshev polynomials of the first kind.
Definition: ChebyshevBoundedField.h:77
lsst::afw::math::ChebyshevBoundedField::getPythonModule
std::string getPythonModule() const override
Return the fully-qualified Python module that should be imported to guarantee that its factory is reg...
Definition: ChebyshevBoundedField.cc:362
lsst::afw::math::ChebyshevBoundedField::evaluate
double evaluate(lsst::geom::Point2D const &position) const override
Evaluate the field at the given point.
Definition: ChebyshevBoundedField.cc:282
lsst::geom::all
bool all(CoordinateExpr< N > const &expr) noexcept
Return true if all elements are true.
Definition: CoordinateExpr.h:81
lsst::afw::table::io::OutputArchiveHandle::makeCatalog
BaseCatalog makeCatalog(Schema const &schema)
Return a new, empty catalog with the given schema.
Definition: OutputArchive.cc:207
LSST_ARCHIVE_ASSERT
#define LSST_ARCHIVE_ASSERT(EXPR)
An assertion macro used to validate the structure of an InputArchive.
Definition: Persistable.h:48
lsst::geom::AffineTransform
An affine coordinate transformation consisting of a linear transformation and an offset.
Definition: AffineTransform.h:75
lsst::afw::math::LeastSquares::NORMAL_EIGENSYSTEM
@ NORMAL_EIGENSYSTEM
Use the normal equations with a symmetric Eigensystem decomposition.
Definition: LeastSquares.h:72
lsst::geom::AffineTransform::YY
@ YY
Definition: AffineTransform.h:77
orderX
table::Key< int > orderX
Definition: ChebyshevBoundedField.cc:316
lsst::afw::math::ChebyshevBoundedField::relocate
std::shared_ptr< ChebyshevBoundedField > relocate(lsst::geom::Box2I const &bbox) const
Return a new ChebyshevBoundedField with domain set to the given bounding box.
Definition: ChebyshevBoundedField.cc:240
lsst::afw::table::Box2IKey
BoxKey< lsst::geom::Box2I > Box2IKey
Definition: aggregates.h:201
z
double z
Definition: Match.cc:44
x
double x
Definition: ChebyshevBoundedField.cc:277
lsst::pex::exceptions::LengthError
Reports attempts to exceed implementation-defined length limits for some classes.
Definition: Runtime.h:76
lsst::afw::math::detail::TrapezoidalPacker::size
int size
Definition: TrapezoidalPacker.h:107
lsst::jointcal::Iterator
FastFinder::Iterator Iterator
Definition: FastFinder.cc:178
TrapezoidalPacker.h
lsst::geom::AffineTransform::XX
@ XX
Definition: AffineTransform.h:77
lsst::geom::Box2I::getArea
int getArea() const
Definition: Box.h:189
lsst::afw::image::ImageBase::getArray
Array getArray()
Definition: ImageBase.h:513
lsst::afw::math::ChebyshevBoundedFieldControl::orderY
int orderY
"maximum Chebyshev function order in y" ;
Definition: ChebyshevBoundedField.h:44
LeastSquares.h
result
py::object result
Definition: _schema.cc:429
lsst
A base class for image defects.
Definition: imageAlgorithm.dox:1
lsst::afw::math::ChebyshevBoundedFieldControl::triangular
bool triangular
"if true, only include terms where the sum of the x and y order " "is less than or equal to max(order...
Definition: ChebyshevBoundedField.h:48
LSST_EXCEPT
#define LSST_EXCEPT(type,...)
Create an exception with a given type.
Definition: Exception.h:48
lsst::afw::math::BoundedField::getBBox
lsst::geom::Box2I getBBox() const
Return the bounding box that defines the region where the field is valid.
Definition: BoundedField.h:112
lsst::afw::math::ChebyshevBoundedField::ChebyshevBoundedField
ChebyshevBoundedField(lsst::geom::Box2I const &bbox, ndarray::Array< double const, 2, 2 > const &coefficients)
Initialize the field from its bounding box an coefficients.
Definition: ChebyshevBoundedField.cc:60
std::ostringstream
STL class.
lsst::geom
Definition: geomOperators.dox:4
lsst::afw::math::ChebyshevBoundedFieldControl::computeSize
int computeSize() const
Return the number of nonzero coefficients in the Chebyshev function defined by this object.
Definition: ChebyshevBoundedField.cc:44
os
std::ostream * os
Definition: Schema.cc:746
lsst::geom::AffineTransform::Y
@ Y
Definition: AffineTransform.h:77
lsst::geom::Point< double, 2 >
lsst::afw::math::ChebyshevBoundedField::operator==
bool operator==(BoundedField const &rhs) const override
BoundedFields (of the same sublcass) are equal if their bounding boxes and parameters are equal.
Definition: ChebyshevBoundedField.cc:380
ChebyshevBoundedField.h
lsst::geom::Box2I
An integer coordinate rectangle.
Definition: Box.h:55
lsst::afw.display.ds9.scale
def scale(algorithm, min, max=None, frame=None)
Definition: ds9.py:109
lsst::afw::image::PARENT
@ PARENT
Definition: ImageBase.h:94
lsst::afw::math::LeastSquares::getSolution
ndarray::Array< double const, 1, 1 > getSolution()
Return the vector solution to the least squares problem.
Definition: LeastSquares.cc:317
lsst::geom::AffineTransform::X
@ X
Definition: AffineTransform.h:77
w
double w
Definition: CoaddPsf.cc:69
InputArchive.h
std::size_t
lsst::afw::table::CatalogT::addNew
std::shared_ptr< RecordT > addNew()
Create a new record, add it to the end of the catalog, and return a pointer to it.
Definition: Catalog.h:485
lsst::afw::math::LeastSquares::fromDesignMatrix
static LeastSquares fromDesignMatrix(ndarray::Array< T1, 2, C1 > const &design, ndarray::Array< T2, 1, C2 > const &data, Factorization factorization=NORMAL_EIGENSYSTEM)
Initialize from the design matrix and data vector given as ndarrays.
Definition: LeastSquares.h:100
lsst::afw::image::ImageBase::getBBox
lsst::geom::Box2I getBBox(ImageOrigin origin=PARENT) const
Definition: ImageBase.h:482
lsst::geom::Box2D
A floating-point coordinate rectangle geometry.
Definition: Box.h:413
lsst::afw::image::Image
A class to represent a 2-dimensional array of pixels.
Definition: Image.h:58
lsst::afw::math::ChebyshevBoundedField::write
void write(OutputArchiveHandle &handle) const override
Write the object to one or more catalogs.
Definition: ChebyshevBoundedField.cc:364
schema
table::Schema schema
Definition: ChebyshevBoundedField.cc:315
lsst::ip::diffim.Control
Control
Definition: __init__.py:49
lsst::afw::table::CatalogT< BaseRecord >
lsst::geom::Extent< double, 2 >
OutputArchive.h