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doc/developer/overview.rst
r3d40839 r2a7e20e 185 185 jitter applied before particle orientation. 186 186 187 When computing the orientation dispersity integral, the weights for 188 the individual points depends on the map projection used to translate jitter 189 angles into latitude/longitude. The choice of projection is set by 190 *sasmodels.generate.PROJECTION*, with the default *PROJECTION=1* for 191 equirectangular and *PROJECTION=2* for sinusoidal. The more complicated 192 Guyou and Postel projections are not implemented. See explore.jitter.draw_mesh 193 for details. 194 187 195 For numerical integration within form factors etc. sasmodels is mostly using 188 196 Gaussian quadrature with 20, 76 or 150 points depending on the model. It also … … 199 207 Useful testing routines include: 200 208 201 :mod:`asymint` a direct implementation of the surface integral for certain 202 models to get a more trusted value for the 1D integral using a 203 reimplementation of the 2D kernel in python and mpmath (which computes math 204 functions to arbitrary precision). It uses $\theta$ ranging from 0 to $\pi$ 205 and $\phi$ ranging from 0 to $2\pi$. It perhaps would benefit from including 206 the U-substitution for $\theta$. 207 208 :mod:`check1d` uses sasmodels 1D integration and compares that with a 209 The *sascomp* utility is used to view and compare models with different 210 parameters and calculation engines. The usual case is to simply plot a 211 model that you are developing:: 212 213 python sascomp path/to/model.py 214 215 Once the obvious problems are addressed, check the numerical precision 216 across a variety of randomly generated inputs:: 217 218 python sascomp -engine=single,double path/to/model.py -sets=10 219 220 You can compare different parameter values for the same or different models. 221 For example when looking along the long axis of a cylinder ($\theta=0$), 222 dispersity in $\theta$ should be equivalent to dispersity in $\phi$ 223 when $\phi=90$:: 224 225 python sascomp -2d cylinder theta=0 phi=0,90 theta_pd_type=rectangle \\ 226 phi_pd_type=rectangle phi_pd=10,1 theta_pd=1,10 length=500 radius=10 227 228 It turns out that they are not because the equirectangular map projection 229 weights the points by $\cos(\theta)$ so $\Delta\theta$ is not identical 230 to $\Delta\phi$. Setting *PROJECTION=2* in :mod:`sasmodels.generate` helps 231 somewhat. Postel would help even more in this case, though leading 232 to distortions elsewhere. See :mod:`sasmodels.compare` for many more details. 233 234 *sascomp -ngauss=n* allows you to set the number of quadrature points used 235 for the 1D integration for any model. For example, a carbon nanotube with 236 length 10 $\mu$\ m and radius 1 nm is not computed correctly at high $q$:: 237 238 python sascomp cylinder length=100000 radius=10 -ngauss=76,500 -double -highq 239 240 Note: ticket 702 gives some forms for long rods and thin disks that may 241 be used in place of the integration, depending on $q$, radius and length; if 242 the cylinder model is updated with these corrections then above call will show 243 no difference. 244 245 *explore/check1d.py* uses sasmodels 1D integration and compares that with a 209 246 rectangle distribution in $\theta$ and $\phi$, with $\theta$ limits set to 210 247 $\pm 90/\sqrt(3)$ and $\phi$ limits set to $\pm 180/\sqrt(3)$ [The rectangle … … 214 251 similar reasoning.] This should rotate the sample through the entire 215 252 $\theta$-$\phi$ surface according to the pattern that you see in jitter.py when 216 you modify it to use 'rectangle' rather than 'gaussian' for its distribution217 without changing the viewing angle. In order to match the 1-D pattern for 218 an arbitraryviewing angle on triaxial shapes, we need to integrate253 you use 'rectangle' rather than 'gaussian' for its distribution without 254 changing the viewing angle. In order to match the 1-D pattern for an arbitrary 255 viewing angle on triaxial shapes, we need to integrate 219 256 over $\theta$, $\phi$ and $\Psi$. 220 257 221 When computing the dispersity integral, weights are scaled by 222 $|\cos(\delta \theta)|$ to account for the points in $\phi$ getting closer 223 together as $\delta \theta$ increases. 224 [This will probably change so that instead of adjusting the weights, we will 225 adjust $\delta\theta$-$\delta\phi$ mesh so that the point density in 226 $\delta\phi$ is lower at larger $\delta\theta$. The flag USE_SCALED_PHI in 227 *kernel_iq.c* selects an alternative algorithm.] 228 229 The integrated dispersion is computed at a set of $(qx, qy)$ points $(q 230 \cos(\alpha), q \sin(\alpha))$ at some angle $\alpha$ (currently angle=0) for 231 each $q$ used in the 1-D integration. The individual $q$ points should be 232 equivalent to asymint rect-n when the viewing angle is set to 233 $(\theta,\phi,\Psi) = (90, 0, 0)$. Such tests can help to validate that 2d 234 models are consistent with 1d models. 235 236 :mod:`sascomp -sphere=n` uses the same rectangular distribution as check1d to 237 compute the pattern of the $q_x$-$q_y$ grid. 238 239 The :mod:`sascomp` utility can be used for 2d as well as 1d calculations to 240 compare results for two sets of parameters or processor types, for example 241 these two oriented cylinders here should be equivalent. 242 243 :mod:`\./sascomp -2d cylinder theta=0 phi=0,90 theta_pd_type=rectangle phi_pd_type=rectangle phi_pd=10,1 theta_pd=1,10 length=500 radius=10` 244 258 *sascomp -sphere=n* uses the same rectangular distribution as check1d to 259 compute the pattern of the $q_x$-$q_y$ grid. This ought to produce a 260 spherically symmetric pattern. 261 262 *explore/precision.py* investigates the accuracy of individual functions 263 on the different execution platforms. This includes the basic special 264 functions as well as more complex expressions used in scattering. In many 265 cases the OpenCL function in sasmodels will use a polynomial approximation 266 over part of the range to improve accuracy, as shown in:: 267 268 python explore/precision.py 3j1/x 269 270 *explore/realspace.py* allows you to set up a Monte Carlo simulation of your 271 model by sampling random points within and computing the 1D and 2D scattering 272 patterns. This was used to check the core shell parallelepiped example. This 273 is similar to the general sas calculator in sasview, though it uses different 274 code. 275 276 *explore/jitter.py* is for exploring different options for handling 277 orientation and orientation dispersity. It uses *explore/guyou.py* to 278 generate the Guyou projection. 279 280 *explore/asymint.py* is a direct implementation of the 1D integration for 281 a number of different models. It calculates the integral for a particular 282 $q$ using several different integration schemes, including mpmath with 100 283 bits of precision (33 digits), so you can use it to check the target values 284 for the 1D model tests. This is not a general purpose tool; you will need to 285 edit the file to change the model parameters. It does not currently 286 apply the $u=cos(\theta)$ substitution that many models are using 287 internally so the 76-point gaussian quadrature may not match the value 288 produced by the eqivalent model from sasmodels. 289 290 *explore/symint.py* is for rotationally symmetric models (just cylinder for 291 now), so it can compute an entire curve rather than a single $q$ point. It 292 includes code to compare the long cylinder approximation to cylinder. 293 294 *explore/rpa.py* is for checking different implementations of the RPA model 295 against calculations for specific blends. This is a work in (suspended) 296 progress. 297 298 There are a few modules left over in *explore* that can probably be removed. 299 *angular_pd.py* was an early version of *jitter.py*. *sc.py* and *sc.c* 300 was used to explore different calculations for paracrystal models; it has 301 been absorbed into *asymint.py*. *transform_angles.py* translates orientation 302 parameters from the SasView 3.x definition to sasmodels. 303 304 *explore/angles.py* generates code for the view and jitter transformations. 305 Keep this around since it may be needed if we add new projections. 245 306 246 307 Testing -
doc/guide/orientation/orientation.rst
r82592da r5fb0634 4 4 ================== 5 5 6 With two dimensional small angle diffraction data SasViewwill calculate6 With two dimensional small angle diffraction data sasmodels will calculate 7 7 scattering from oriented particles, applicable for example to shear flow 8 8 or orientation in a magnetic field. 9 9 10 10 In general we first need to define the reference orientation 11 of the particles with respect to the incoming neutron or X-ray beam. This 12 is done using three angles: $\theta$ and $\phi$ define the orientation of 13 the axis of the particle, angle $\Psi$ is defined as the orientation of 14 the major axis of the particle cross section with respect to its starting 15 position along the beam direction. The figures below are for an elliptical 16 cross section cylinder, but may be applied analogously to other shapes of 17 particle. 11 of the particle's $a$-$b$-$c$ axes with respect to the incoming 12 neutron or X-ray beam. This is done using three angles: $\theta$ and $\phi$ 13 define the orientation of the $c$-axis of the particle, and angle $\Psi$ is 14 defined as the orientation of the major axis of the particle cross section 15 with respect to its starting position along the beam direction (or 16 equivalently, as rotation about the $c$ axis). There is an unavoidable 17 ambiguity when $c$ is aligned with $z$ in that $\phi$ and $\Psi$ both 18 serve to rotate the particle about $c$, but this symmetry is destroyed 19 when $\theta$ is not a multiple of 180. 20 21 The figures below are for an elliptical cross section cylinder, but may 22 be applied analogously to other shapes of particle. 18 23 19 24 .. note:: … … 29 34 30 35 Definition of angles for oriented elliptical cylinder, where axis_ratio 31 b/a is shown >1 ,Note that rotation $\theta$, initially in the $x$-$z$36 b/a is shown >1. Note that rotation $\theta$, initially in the $x$-$z$ 32 37 plane, is carried out first, then rotation $\phi$ about the $z$-axis, 33 38 finally rotation $\Psi$ is around the axis of the cylinder. The neutron 34 or X-ray beam is along the $ z$ axis.39 or X-ray beam is along the $-z$ axis. 35 40 36 41 .. figure:: … … 40 45 with $\Psi$ = 0. 41 46 42 Having established the mean direction of the particle we can then apply 43 angular orientation distributions. This is done by a numerical integration 44 over a range of angles in a similar way to particle size dispersity. 45 In the current version of sasview the orientational dispersity is defined 46 with respect to the axes of the particle. 47 Having established the mean direction of the particle (the view) we can then 48 apply angular orientation distributions (jitter). This is done by a numerical 49 integration over a range of angles in a similar way to particle size 50 dispersity. The orientation dispersity is defined with respect to the 51 $a$-$b$-$c$ axes of the particle, with roll angle $\Psi$ about the $c$-axis, 52 yaw angle $\theta$ about the $b$-axis and pitch angle $\phi$ about the 53 $a$-axis. 54 55 More formally, starting with axes $a$-$b$-$c$ of the particle aligned 56 with axes $x$-$y$-$z$ of the laboratory frame, the orientation dispersity 57 is applied first, using the 58 `Tait-Bryan <https://en.wikipedia.org/wiki/Euler_angles#Conventions_2>`_ 59 $x$-$y'$-$z''$ convention with angles $\Delta\phi$-$\Delta\theta$-$\Delta\Psi$. 60 The reference orientation then follows, using the 61 `Euler angles <https://en.wikipedia.org/wiki/Euler_angles#Conventions>`_ 62 $z$-$y'$-$z''$ with angles $\phi$-$\theta$-$\Psi$. This is implemented 63 using rotation matrices as 64 65 .. math:: 66 67 R = R_z(\phi)\, R_y(\theta)\, R_z(\Psi)\, 68 R_x(\Delta\phi)\, R_y(\Delta\theta)\, R_z(\Delta\Psi) 69 70 To transform detector $(q_x, q_y)$ values into $(q_a, q_b, q_c)$ for the 71 shape in its canonical orientation, use 72 73 .. math:: 74 75 [q_a, q_b, q_c]^T = R^{-1} \, [q_x, q_y, 0]^T 76 77 78 The inverse rotation is easily calculated by rotating the opposite directions 79 in the reverse order, so 80 81 .. math:: 82 83 R^{-1} = R_z(-\Delta\Psi)\, R_y(-\Delta\theta)\, R_x(-\Delta\phi)\, 84 R_z(-\Psi)\, R_y(-\theta)\, R_z(-\phi) 85 47 86 48 87 The $\theta$ and $\phi$ orientation parameters for the cylinder only appear 49 when fitting 2d data. On introducing "Orientational Distribution" in 50 theangles, "distribution of theta" and "distribution of phi" parameters will88 when fitting 2d data. On introducing "Orientational Distribution" in the 89 angles, "distribution of theta" and "distribution of phi" parameters will 51 90 appear. These are actually rotations about the axes $\delta_1$ and $\delta_2$ 52 of the cylinder, the $b$ and $a$ axes of the cylinder cross section. (When 53 $\theta = \phi = 0$ these are parallel to the $Y$ and $X$ axes of the 54 instrument.) The third orientation distribution, in $\Psi$, is about the $c$ 55 axis of the particle. Some experimentation may be required to understand the 56 2d patterns fully. A number of different shapes of distribution are 57 available, as described for polydispersity, see :ref:`polydispersityhelp` . 91 of the cylinder, which correspond to the $b$ and $a$ axes of the cylinder 92 cross section. (When $\theta = \phi = 0$ these are parallel to the $Y$ and 93 $X$ axes of the instrument.) The third orientation distribution, in $\Psi$, 94 is about the $c$ axis of the particle. Some experimentation may be required 95 to understand the 2d patterns fully. A number of different shapes of 96 distribution are available, as described for size dispersity, see 97 :ref:`polydispersityhelp`. 58 98 59 Earlier versions of SasView had numerical integration issues in some 60 circumstances when distributions passed through 90 degrees. The distributions 61 in particle coordinates are more robust, but should still be approached with 62 care for large ranges of angle. 99 Given that the angular dispersion distribution is defined in cartesian space, 100 over a cube defined by 101 102 .. math:: 103 104 [-\Delta \theta, \Delta \theta] \times 105 [-\Delta \phi, \Delta \phi] \times 106 [-\Delta \Psi, \Delta \Psi] 107 108 but the orientation is defined over a sphere, we are left with a 109 `map projection <https://en.wikipedia.org/wiki/List_of_map_projections>`_ 110 problem, with different tradeoffs depending on how values in $\Delta\theta$ 111 and $\Delta\phi$ are translated into latitude/longitude on the sphere. 112 113 Sasmodels is using the 114 `equirectangular projection <https://en.wikipedia.org/wiki/Equirectangular_projection>`_. 115 In this projection, square patches in angular dispersity become wedge-shaped 116 patches on the sphere. To correct for the changing point density, there is a 117 scale factor of $\sin(\Delta\theta)$ that applies to each point in the 118 integral. This is not enough, though. Consider a shape which is tumbling 119 freely around the $b$ axis, with $\Delta\theta$ uniform in $[-180, 180]$. At 120 $\pm 90$, all points in $\Delta\phi$ map to the pole, so the jitter will have 121 a distinct angular preference. If the spin axis is along the beam (which 122 will be the case for $\theta=90$ and $\Psi=90$) the scattering pattern 123 should be circularly symmetric, but it will go to zero at $q_x = 0$ due to the 124 $\sin(\Delta\theta)$ correction. This problem does not appear for a shape 125 that is tumbling freely around the $a$ axis, with $\Delta\phi$ uniform in 126 $[-180, 180]$, so swap the $a$ and $b$ axes so $\Delta\theta < \Delta\phi$ 127 and adjust $\Psi$ by 90. This works with the current sasmodels shapes due to 128 symmetry. 129 130 Alternative projections were considered. 131 The `sinusoidal projection <https://en.wikipedia.org/wiki/Sinusoidal_projection>`_ 132 works by scaling $\Delta\phi$ as $\Delta\theta$ increases, and dropping those 133 points outside $[-180, 180]$. The distortions are a little less for middle 134 ranges of $\Delta\theta$, but they are still severe for large $\Delta\theta$ 135 and the model is much harder to explain. 136 The `azimuthal equidistance projection <https://en.wikipedia.org/wiki/Azimuthal_equidistant_projection>`_ 137 also improves on the equirectangular projection by extending the range of 138 reasonable values for the $\Delta\theta$ range, with $\Delta\phi$ forming a 139 wedge that cuts to the opposite side of the sphere rather than cutting to the 140 pole. This projection has the nice property that distance from the center are 141 preserved, and that $\Delta\theta$ and $\Delta\phi$ act the same. 142 The `azimuthal equal area projection <https://en.wikipedia.org/wiki/Lambert_azimuthal_equal-area_projection>`_ 143 is like the azimuthal equidistance projection, but it preserves area instead 144 of distance. It also has the same behaviour for $\Delta\theta$ and $\Delta\phi$. 145 The `Guyou projection <https://en.wikipedia.org/wiki/Guyou_hemisphere-in-a-square_projection>`_ 146 has an excellent balance with reasonable distortion in both $\Delta\theta$ 147 and $\Delta\phi$, as well as preserving small patches. However, it requires 148 considerably more computational overhead, and we have not yet derived the 149 formula for the distortion correction, measuring the degree of stretch at 150 the point $(\Delta\theta, \Delta\phi)$ on the map. 63 151 64 152 .. note:: 65 Note that the form factors for oriented particles are also performing 66 numerical integrations over one or more variables, so care should be taken, 67 especially with very large particles or more extreme aspect ratios. In such 68 cases results may not be accurate, particularly at very high Q, unless the model 69 has been specifically coded to use limiting forms of the scattering equations. 70 71 For best numerical results keep the $\theta$ distribution narrower than the $\phi$ 72 distribution. Thus for asymmetric particles, such as elliptical_cylinder, you may 73 need to reorder the sizes of the three axes to acheive the desired result. 74 This is due to the issues of mapping a rectangular distribution onto the 75 surface of a sphere. 153 Note that the form factors for oriented particles are performing 154 numerical integrations over one or more variables, so care should be 155 taken, especially with very large particles or more extreme aspect 156 ratios. In such cases results may not be accurate, particularly at very 157 high Q, unless the model has been specifically coded to use limiting 158 forms of the scattering equations. 76 159 77 Users can experiment with the values of *Npts* and *Nsigs*, the number of steps 78 used in the integration and the range spanned in number of standard deviations. 79 The standard deviation is entered in units of degrees. For a "rectangular" 80 distribution the full width should be $\pm \sqrt(3)$ ~ 1.73 standard deviations. 81 The new "uniform" distribution avoids this by letting you directly specify the 160 For best numerical results keep the $\theta$ distribution narrower than 161 the $\phi$ distribution. Thus for asymmetric particles, such as 162 elliptical_cylinder, you may need to reorder the sizes of the three axes 163 to acheive the desired result. This is due to the issues of mapping a 164 rectanglar distribution onto the surface of a sphere. 165 166 Users can experiment with the values of *Npts* and *Nsigs*, the number of steps 167 used in the integration and the range spanned in number of standard deviations. 168 The standard deviation is entered in units of degrees. For a "rectangular" 169 distribution the full width should be $\pm \sqrt(3)$ ~ 1.73 standard deviations. 170 The new "uniform" distribution avoids this by letting you directly specify the 82 171 half width. 83 172 84 The angular distributions will be truncated outside of the range -180 to +18085 degrees, so beware of using saying a broad Gaussian distribution with large value86 of *Nsigs*, as the array of *Npts* may be truncated to many fewer points than would 87 give a good integration,as well as becoming rather meaningless. (At some point 88 in the future the actual polydispersity arrays may be made available to the user 89 for inspection.)173 The angular distributions may be truncated outside of the range -180 to +180 174 degrees, so beware of using saying a broad Gaussian distribution with large 175 value of *Nsigs*, as the array of *Npts* may be truncated to many fewer 176 points than would give a good integration,as well as becoming rather 177 meaningless. (At some point in the future the actual dispersion arrays may be 178 made available to the user for inspection.) 90 179 91 180 Some more detailed technical notes are provided in the developer section of 92 181 this manual :ref:`orientation_developer` . 93 182 183 This definition of orientation is new to SasView 4.2. In earlier versions, 184 the orientation distribution appeared as a distribution of view angles. 185 This led to strange effects when $c$ was aligned with $z$, where changes 186 to the $\phi$ angle served only to rotate the shape about $c$, rather than 187 having a consistent interpretation as the pitch of the shape relative to 188 the flow field defining the reference orientation. Prior to SasView 4.1, 189 the reference orientation was defined using a Tait-Bryan convention, making 190 it difficult to control. Now, rotation in $\theta$ modifies the spacings 191 in the refraction pattern, and rotation in $\phi$ rotates it in the detector 192 plane. 193 194 94 195 *Document History* 95 196 96 197 | 2017-11-06 Richard Heenan 198 | 2017-12-20 Paul Kienzle -
doc/guide/plugin.rst
rd0dc9a3 r7e6bc45e 292 292 **Note: The order of the parameters in the definition will be the order of the 293 293 parameters in the user interface and the order of the parameters in Iq(), 294 Iqxy() and form_volume(). And** *scale* **and** *background* **parameters are 295 implicit to all models, so they do not need to be included in the parameter table.** 294 Iqac(), Iqabc() and form_volume(). And** *scale* **and** *background* 295 **parameters are implicit to all models, so they do not need to be included 296 in the parameter table.** 296 297 297 298 - **"name"** is the name of the parameter shown on the FitPage. … … 362 363 scattered intensity. 363 364 364 - "volume" parameters are passed to Iq(), Iqxy(), and form_volume(), and 365 have polydispersity loops generated automatically. 366 367 - "orientation" parameters are only passed to Iqxy(), and have angular 368 dispersion. 365 - "volume" parameters are passed to Iq(), Iqac(), Iqabc() and form_volume(), 366 and have polydispersity loops generated automatically. 367 368 - "orientation" parameters are not passed, but instead are combined with 369 orientation dispersity to translate *qx* and *qy* to *qa*, *qb* and *qc*. 370 These parameters should appear at the end of the table with the specific 371 names *theta*, *phi* and for asymmetric shapes *psi*, in that order. 369 372 370 373 Some models will have integer parameters, such as number of pearls in the … … 419 422 That is, the individual models do not need to include polydispersity 420 423 calculations, but instead rely on numerical integration to compute the 421 appropriately smeared pattern. Angular dispersion values over polar angle 422 $\theta$ requires an additional $\cos \theta$ weighting due to decreased 423 arc length for the equatorial angle $\phi$ with increasing latitude. 424 appropriately smeared pattern. 424 425 425 426 Python Models … … 468 469 barbell). If I(q; pars) is NaN for any $q$, then those parameters will be 469 470 ignored, and not included in the calculation of the weighted polydispersity. 470 471 Similar to *Iq*, you can define *Iqxy(qx, qy, par1, par2, ...)* where the472 parameter list includes any orientation parameters. If *Iqxy* is not defined,473 then it will default to *Iqxy = Iq(sqrt(qx**2+qy**2), par1, par2, ...)*.474 471 475 472 Models should define *form_volume(par1, par2, ...)* where the parameter … … 497 494 } 498 495 499 *Iqxy* is similar to *Iq*, except it uses parameters *qx, qy* instead of *q*,500 and it includes orientation parameters.501 502 496 *form_volume* defines the volume of the shape. As in python models, it 503 497 includes only the volume parameters. 504 498 505 *Iqxy* will default to *Iq(sqrt(qx**2 + qy**2), par1, ...)* and506 *form_volume* will default to 1.0.507 508 499 **source=['fn.c', ...]** includes the listed C source files in the 509 program before *Iq* and *Iqxy* are defined. This allows you to extend the 510 library of C functions available to your model. 500 program before *Iq* and *form_volume* are defined. This allows you to 501 extend the library of C functions available to your model. 502 503 *c_code* includes arbitrary C code into your kernel, which can be 504 handy for defining helper functions for *Iq* and *form_volume*. Note that 505 you can put the full function definition for *Iq* and *form_volume* 506 (include function declaration) into *c_code* as well, or put them into an 507 external C file and add that file to the list of sources. 511 508 512 509 Models are defined using double precision declarations for the … … 532 529 533 530 #define INVALID(v) (v.bell_radius < v.radius) 531 532 The INVALID define can go into *Iq*, or *c_code*, or an external C file 533 listed in *source*. 534 535 Oriented Shapes 536 ............... 537 538 If the scattering is dependent on the orientation of the shape, then you 539 will need to include *orientation* parameters *theta*, *phi* and *psi* 540 at the end of the parameter table. As described in the section 541 :ref:`orientation`, the individual $(q_x, q_y)$ points on the detector will 542 be rotated into $(q_a, q_b, q_c)$ points relative to the sample in its 543 canonical orientation with $a$-$b$-$c$ aligned with $x$-$y$-$z$ in the 544 laboratory frame and beam travelling along $-z$. 545 546 The oriented C model is called using *Iqabc(qa, qb, qc, par1, par2, ...)* where 547 *par1*, etc. are the parameters to the model. If the shape is rotationally 548 symmetric about *c* then *psi* is not needed, and the model is called 549 as *Iqac(qab, qc, par1, par2, ...)*. In either case, the orientation 550 parameters are not included in the function call. 551 552 For 1D oriented shapes, an integral over all angles is usually needed for 553 the *Iq* function. Given symmetry and the substitution $u = \cos(\alpha)$, 554 $du = -\sin(\alpha)\,d\alpha$ this becomes 555 556 .. math:: 557 558 I(q) &= \frac{1}{4\pi} \int_{-\pi/2}^{pi/2} \int_{-pi}^{pi} 559 F(q_a, q_b, q_c)^2 \sin(\alpha)\,d\beta\,d\alpha \\ 560 &= \frac{8}{4\pi} \int_{0}^{pi/2} \int_{0}^{\pi/2} 561 F^2 \sin(\alpha)\,d\beta\,d\alpha \\ 562 &= \frac{8}{4\pi} \int_1^0 \int_{0}^{\pi/2} - F^2 \,d\beta\,du \\ 563 &= \frac{8}{4\pi} \int_0^1 \int_{0}^{\pi/2} F^2 \,d\beta\,du 564 565 for 566 567 .. math:: 568 569 q_a &= q \sin(\alpha)\sin(\beta) = q \sqrt{1-u^2} \sin(\beta) \\ 570 q_b &= q \sin(\alpha)\cos(\beta) = q \sqrt{1-u^2} \cos(\beta) \\ 571 q_c &= q \cos(\alpha) = q u 572 573 Using the $z, w$ values for Gauss-Legendre integration in "lib/gauss76.c", the 574 numerical integration is then:: 575 576 double outer_sum = 0.0; 577 for (int i = 0; i < GAUSS_N; i++) { 578 const double cos_alpha = 0.5*GAUSS_Z[i] + 0.5; 579 const double sin_alpha = sqrt(1.0 - cos_alpha*cos_alpha); 580 const double qc = cos_alpha * q; 581 double inner_sum = 0.0; 582 for (int j = 0; j < GAUSS_N; j++) { 583 const double beta = M_PI_4 * GAUSS_Z[j] + M_PI_4; 584 double sin_beta, cos_beta; 585 SINCOS(beta, sin_beta, cos_beta); 586 const double qa = sin_alpha * sin_beta * q; 587 const double qb = sin_alpha * cos_beta * q; 588 const double form = Fq(qa, qb, qc, ...); 589 inner_sum += GAUSS_W[j] * form * form; 590 } 591 outer_sum += GAUSS_W[i] * inner_sum; 592 } 593 outer_sum *= 0.25; // = 8/(4 pi) * outer_sum * (pi/2) / 4 594 595 The *z* values for the Gauss-Legendre integration extends from -1 to 1, so 596 the double sum of *w[i]w[j]* explains the factor of 4. Correcting for the 597 average *dz[i]dz[j]* gives $(1-0) \cdot (\pi/2-0) = \pi/2$. The $8/(4 \pi)$ 598 factor comes from the integral over the quadrant. With less symmetry (eg., 599 in the bcc and fcc paracrystal models), then an integral over the entire 600 sphere may be necessary. 601 602 For simpler models which are rotationally symmetric a single integral 603 suffices: 604 605 .. math:: 606 607 I(q) &= \frac{1}{\pi}\int_{-\pi/2}^{\pi/2} 608 F(q_{ab}, q_c)^2 \sin(\alpha)\,d\alpha/\pi \\ 609 &= \frac{2}{\pi} \int_0^1 F^2\,du 610 611 for 612 613 .. math:: 614 615 q_{ab} &= q \sin(\alpha) = q \sqrt{1 - u^2} \\ 616 q_c &= q \cos(\alpha) = q u 617 618 619 with integration loop:: 620 621 double sum = 0.0; 622 for (int i = 0; i < GAUSS_N; i++) { 623 const double cos_alpha = 0.5*GAUSS_Z[i] + 0.5; 624 const double sin_alpha = sqrt(1.0 - cos_alpha*cos_alpha); 625 const double qab = sin_alpha * q; 626 const double qc = cos_alpha * q; 627 const double form = Fq(qab, qc, ...); 628 sum += GAUSS_W[j] * form * form; 629 } 630 sum *= 0.5; // = 2/pi * sum * (pi/2) / 2 631 632 Magnetism 633 ......... 634 635 Magnetism is supported automatically for all shapes by modifying the 636 effective SLD of particle according to the Halpern-Johnson vector 637 describing the interaction between neutron spin and magnetic field. All 638 parameters marked as type *sld* in the parameter table are treated as 639 possibly magnetic particles with magnitude *M0* and direction 640 *mtheta* and *mphi*. Polarization parameters are also provided 641 automatically for magnetic models to set the spin state of the measurement. 642 643 For more complicated systems where magnetism is not uniform throughout 644 the individual particles, you will need to write your own models. 645 You should not mark the nuclear sld as type *sld*, but instead leave 646 them unmarked and provide your own magnetism and polarization parameters. 647 For 2D measurements you will need $(q_x, q_y)$ values for the measurement 648 to compute the proper magnetism and orientation, which you can implement 649 using *Iqxy(qx, qy, par1, par2, ...)*. 534 650 535 651 Special Functions … … 796 912 show a 50x improvement or more over the equivalent pure python model. 797 913 798 External C Models799 .................800 801 External C models are very much like embedded C models, except that802 *Iq*, *Iqxy* and *form_volume* are defined in an external source file803 loaded using the *source=[...]* statement. You need to supply the function804 declarations for each of these that you need instead of building them805 automatically from the parameter table.806 807 914 808 915 .. _Form_Factors: … … 1006 1113 variable name *Rg* for example because $R_g$ is the right name for the model 1007 1114 parameter then ignore the lint errors. Also, ignore *missing-docstring* 1008 for standard model functions *Iq*, *Iq xy*, etc.1115 for standard model functions *Iq*, *Iqac*, etc. 1009 1116 1010 1117 We will have delinting sessions at the SasView Code Camps, where we can -
explore/jitter.py
rff10479 r8cfb486 165 165 # constants in kernel_iq.c 166 166 'equirectangular', 'sinusoidal', 'guyou', 'azimuthal_equidistance', 167 'azimuthal_equal_area', 167 168 ] 168 169 def draw_mesh(ax, view, jitter, radius=1.2, n=11, dist='gaussian', -
explore/precision.py
r2a602c7 r2a7e20e 345 345 ) 346 346 add_function( 347 name="(1/2 +(1-cos(x))/x^2-sin(x)/x)/x",347 name="(1/2-sin(x)/x+(1-cos(x))/x^2)/x", 348 348 mp_function=lambda x: (0.5 - mp.sin(x)/x + (1-mp.cos(x))/(x*x))/x, 349 349 np_function=lambda x: (0.5 - np.sin(x)/x + (1-np.cos(x))/(x*x))/x, … … 609 609 names = ", ".join(sorted(ALL_FUNCTIONS)) 610 610 print("""\ 611 usage: precision.py [-f/a/r] [-x<range>] name...611 usage: precision.py [-f/a/r] [-x<range>] "name" ... 612 612 where 613 613 -f indicates that the function value should be plotted, … … 620 620 zoom indicates linear stepping in [1000, 1010] 621 621 neg indicates linear stepping in [-100.1, 100.1] 622 and name is "all [first]" or one of:622 and name is "all" or one of: 623 623 """+names) 624 624 sys.exit(1) -
explore/realspace.py
ra1c32c2 r8fb2a94 44 44 """ 45 45 return Rx(phi)*Ry(theta)*Rz(psi) 46 47 def apply_view(points, view): 48 """ 49 Apply the view transform (theta, phi, psi) to a set of points. 50 51 Points are stored in a 3 x n numpy array. 52 53 View angles are in degrees. 54 """ 55 theta, phi, psi = view 56 return np.asarray((Rz(phi)*Ry(theta)*Rz(psi))*np.matrix(points.T)).T 57 58 59 def invert_view(qx, qy, view): 60 """ 61 Return (qa, qb, qc) for the (theta, phi, psi) view angle at detector 62 pixel (qx, qy). 63 64 View angles are in degrees. 65 """ 66 theta, phi, psi = view 67 q = np.vstack((qx.flatten(), qy.flatten(), 0*qx.flatten())) 68 return np.asarray((Rz(-psi)*Ry(-theta)*Rz(-phi))*np.matrix(q)) 69 46 70 47 71 class Shape: … … 219 243 values = self.value.repeat(points.shape[0]) 220 244 return values, self._adjust(points) 245 246 NUMBA = False 247 if NUMBA: 248 from numba import njit 249 @njit("f8[:](f8[:],f8[:],f8[:],f8[:],f8[:],f8[:],f8[:])") 250 def _Iqxy(values, x, y, z, qa, qb, qc): 251 Iq = np.zeros_like(qa) 252 for j in range(len(Iq)): 253 total = 0. + 0j 254 for k in range(len(Iq)): 255 total += values[k]*np.exp(1j*(qa[j]*x[k] + qb[j]*y[k] + qc[j]*z[k])) 256 Iq[j] = abs(total)**2 257 return Iq 258 259 def calc_Iqxy(qx, qy, rho, points, volume=1.0, view=(0, 0, 0)): 260 qx, qy = np.broadcast_arrays(qx, qy) 261 qa, qb, qc = invert_view(qx, qy, view) 262 rho, volume = np.broadcast_arrays(rho, volume) 263 values = rho*volume 264 x, y, z = points.T 265 266 # I(q) = |sum V(r) rho(r) e^(1j q.r)|^2 / sum V(r) 267 if NUMBA: 268 Iq = _Iqxy(values, x, y, z, qa.flatten(), qb.flatten(), qc.flatten()) 269 else: 270 Iq = [abs(np.sum(values*np.exp(1j*(qa_k*x + qb_k*y + qc_k*z))))**2 271 for qa_k, qb_k, qc_k in zip(qa.flat, qb.flat, qc.flat)] 272 return np.asarray(Iq).reshape(qx.shape) / np.sum(volume) 221 273 222 274 def _calc_Pr_nonuniform(r, rho, points): … … 239 291 print("processing %d of %d"%(k, len(rho)-1)) 240 292 Pr = extended_Pr[1:-1] 241 return Pr / Pr.max() 242 243 def calc_Pr(r, rho, points): 244 # P(r) with uniform steps in r is 3x faster; check if we are uniform 245 # before continuing 246 if np.max(np.abs(np.diff(r) - r[0])) > r[0]*0.01: 247 return _calc_Pr_nonuniform(r, rho, points) 248 293 return Pr 294 295 def _calc_Pr_uniform(r, rho, points): 249 296 # Make Pr a little be bigger than necessary so that only distances 250 297 # min < d < max end up in Pr 251 n_max =len(r)298 dr, n_max = r[0], len(r) 252 299 extended_Pr = np.zeros(n_max+1, 'd') 253 300 t0 = time.clock() 254 301 t_next = t0 + 3 255 row_zero = np.zeros(len(rho), 'i')256 302 for k, rho_k in enumerate(rho[:-1]): 257 303 distances = sqrt(np.sum((points[k] - points[k+1:])**2, axis=1)) 258 304 weights = rho_k * rho[k+1:] 259 index = np.minimum(np.asarray(distances/ r[0], 'i'), n_max)305 index = np.minimum(np.asarray(distances/dr, 'i'), n_max) 260 306 # Note: indices may be duplicated, so "Pr[index] += w" will not work!! 261 307 extended_Pr += np.bincount(index, weights, n_max+1) … … 269 315 # we are only accumulating the upper triangular distances. 270 316 #Pr = Pr * 2 / len(rho)**2 271 return Pr / Pr.max()317 return Pr 272 318 273 319 # Can get an additional 2x by going to C. Cuda/OpenCL will allow even … … 291 337 } 292 338 """ 339 340 if NUMBA: 341 @njit("f8[:](f8[:], f8[:], f8[:,:])") 342 def _calc_Pr_uniform_jit(r, rho, points): 343 dr = r[0] 344 n_max = len(r) 345 Pr = np.zeros_like(r) 346 for j in range(len(rho) - 1): 347 x, y, z = points[j, 0], points[j, 1], points[j, 2] 348 for k in range(j+1, len(rho)): 349 distance = sqrt((x - points[k, 0])**2 350 + (y - points[k, 1])**2 351 + (z - points[k, 2])**2) 352 index = int(distance/dr) 353 if index < n_max: 354 Pr[index] += rho[j] * rho[k] 355 # Make Pr independent of sampling density. The factor of 2 comes because 356 # we are only accumulating the upper triangular distances. 357 #Pr = Pr * 2 / len(rho)**2 358 return Pr 359 360 361 def calc_Pr(r, rho, points): 362 # P(r) with uniform steps in r is 3x faster; check if we are uniform 363 # before continuing 364 if np.max(np.abs(np.diff(r) - r[0])) > r[0]*0.01: 365 Pr = _calc_Pr_nonuniform(r, rho, points) 366 else: 367 if NUMBA: 368 Pr = _calc_Pr_uniform_jit(r, rho, points) 369 else: 370 Pr = _calc_Pr_uniform(r, rho, points) 371 return Pr / Pr.max() 372 293 373 294 374 def j0(x): … … 333 413 plt.legend() 334 414 415 def plot_calc_2d(qx, qy, Iqxy, theory=None): 416 import matplotlib.pyplot as plt 417 qx, qy = bin_edges(qx), bin_edges(qy) 418 #qx, qy = np.meshgrid(qx, qy) 419 if theory is not None: 420 plt.subplot(121) 421 plt.pcolormesh(qx, qy, np.log10(Iqxy)) 422 plt.xlabel('qx (1/A)') 423 plt.ylabel('qy (1/A)') 424 if theory is not None: 425 plt.subplot(122) 426 plt.pcolormesh(qx, qy, np.log10(theory)) 427 plt.xlabel('qx (1/A)') 428 335 429 def plot_points(rho, points): 336 430 import mpl_toolkits.mplot3d … … 343 437 pass 344 438 n = len(points) 345 index = np.random.choice(n, size=1000) if n > 1000 else slice(None, None) 439 #print("len points", n) 440 index = np.random.choice(n, size=500) if n > 500 else slice(None, None) 346 441 ax.scatter(points[index, 0], points[index, 1], points[index, 2], c=rho[index]) 347 442 #low, high = points.min(axis=0), points.max(axis=0) 348 443 #ax.axis([low[0], high[0], low[1], high[1], low[2], high[2]]) 349 444 ax.autoscale(True) 445 446 def check_shape(shape, fn=None): 447 rho_solvent = 0 448 q = np.logspace(-3, 0, 200) 449 r = shape.r_bins(q, r_step=0.01) 450 sampling_density = 6*5000 / shape.volume() 451 rho, points = shape.sample(sampling_density) 452 t0 = time.time() 453 Pr = calc_Pr(r, rho-rho_solvent, points) 454 print("calc Pr time", time.time() - t0) 455 Iq = calc_Iq(q, r, Pr) 456 theory = (q, fn(q)) if fn is not None else None 457 458 import pylab 459 #plot_points(rho, points); pylab.figure() 460 plot_calc(r, Pr, q, Iq, theory=theory) 461 pylab.show() 462 463 def check_shape_2d(shape, fn=None, view=(0, 0, 0)): 464 rho_solvent = 0 465 nq, qmax = 100, 1.0 466 qx = np.linspace(0.0, qmax, nq) 467 qy = np.linspace(0.0, qmax, nq) 468 Qx, Qy = np.meshgrid(qx, qy) 469 sampling_density = 50000 / shape.volume() 470 #t0 = time.time() 471 rho, points = shape.sample(sampling_density) 472 #print("sample time", time.time() - t0) 473 t0 = time.time() 474 Iqxy = calc_Iqxy(Qx, Qy, rho, points, view=view) 475 print("calc time", time.time() - t0) 476 theory = fn(Qx, Qy) if fn is not None else None 477 Iqxy += 0.001 * Iqxy.max() 478 if theory is not None: 479 theory += 0.001 * theory.max() 480 481 import pylab 482 #plot_points(rho, points); pylab.figure() 483 plot_calc_2d(qx, qy, Iqxy, theory=theory) 484 pylab.show() 485 486 def sas_sinx_x(x): 487 with np.errstate(all='ignore'): 488 retvalue = sin(x)/x 489 retvalue[x == 0.] = 1. 490 return retvalue 350 491 351 492 def sas_2J1x_x(x): … … 373 514 Iq = Iq/Iq[0] 374 515 return Iq 516 517 def cylinder_Iqxy(qx, qy, radius, length, view=(0, 0, 0)): 518 qa, qb, qc = invert_view(qx, qy, view) 519 qab = np.sqrt(qa**2 + qb**2) 520 Fq = sas_2J1x_x(qab*radius) * j0(qc*length/2) 521 Iq = Fq**2 522 return Iq.reshape(qx.shape) 375 523 376 524 def sphere_Iq(q, radius): … … 415 563 return Iq/Iq[0] 416 564 417 def check_shape(shape, fn=None): 418 rho_solvent = 0 419 q = np.logspace(-3, 0, 200) 420 r = shape.r_bins(q, r_step=0.01) 421 sampling_density = 15000 / shape.volume() 422 rho, points = shape.sample(sampling_density) 423 Pr = calc_Pr(r, rho-rho_solvent, points) 424 Iq = calc_Iq(q, r, Pr) 425 theory = (q, fn(q)) if fn is not None else None 426 427 import pylab 428 #plot_points(rho, points); pylab.figure() 429 plot_calc(r, Pr, q, Iq, theory=theory) 430 pylab.show() 565 def csbox_Iqxy(qx, qy, a, b, c, da, db, dc, slda, sldb, sldc, sld_core, view=(0,0,0)): 566 qa, qb, qc = invert_view(qx, qy, view) 567 568 sld_solvent = 0 569 overlapping = False 570 dr0 = sld_core - sld_solvent 571 drA, drB, drC = slda-sld_solvent, sldb-sld_solvent, sldc-sld_solvent 572 tA, tB, tC = a + 2*da, b + 2*db, c + 2*dc 573 siA = a*sas_sinx_x(a*qa/2) 574 siB = b*sas_sinx_x(b*qb/2) 575 siC = c*sas_sinx_x(c*qc/2) 576 siAt = tA*sas_sinx_x(tA*qa/2) 577 siBt = tB*sas_sinx_x(tB*qb/2) 578 siCt = tC*sas_sinx_x(tC*qc/2) 579 Fq = (dr0*siA*siB*siC 580 + drA*(siAt-siA)*siB*siC 581 + drB*siA*(siBt-siB)*siC 582 + drC*siA*siB*(siCt-siC)) 583 Iq = Fq**2 584 return Iq.reshape(qx.shape) 431 585 432 586 def check_cylinder(radius=25, length=125, rho=2.): … … 434 588 fn = lambda q: cylinder_Iq(q, radius, length) 435 589 check_shape(shape, fn) 590 591 def check_cylinder_2d(radius=25, length=125, rho=2., view=(0, 0, 0)): 592 shape = EllipticalCylinder(radius, radius, length, rho) 593 fn = lambda qx, qy, view=view: cylinder_Iqxy(qx, qy, radius, length, view=view) 594 check_shape_2d(shape, fn, view=view) 595 596 def check_cylinder_2d_lattice(radius=25, length=125, rho=2., 597 view=(0, 0, 0)): 598 nx, dx = 1, 2*radius 599 ny, dy = 30, 2*radius 600 nz, dz = 30, length 601 dx, dy, dz = 2*dx, 2*dy, 2*dz 602 def center(*args): 603 sigma = 0.333 604 space = 2 605 return [(space*n+np.random.randn()*sigma)*x for n, x in args] 606 shapes = [EllipticalCylinder(radius, radius, length, rho, 607 #center=(ix*dx, iy*dy, iz*dz) 608 orientation=np.random.randn(3)*0, 609 center=center((ix, dx), (iy, dy), (iz, dz)) 610 ) 611 for ix in range(nx) 612 for iy in range(ny) 613 for iz in range(nz)] 614 shape = Composite(shapes) 615 fn = lambda qx, qy, view=view: cylinder_Iqxy(qx, qy, radius, length, view=view) 616 check_shape_2d(shape, fn, view=view) 436 617 437 618 def check_sphere(radius=125, rho=2): … … 449 630 side_c2 = copy(side_c).shift(0, 0, -c-dc) 450 631 shape = Composite((core, side_a, side_b, side_c, side_a2, side_b2, side_c2)) 451 fn = lambda q: csbox_Iq(q, a, b, c, da, db, dc, slda, sldb, sldc, sld_core) 452 check_shape(shape, fn) 632 def fn(q): 633 return csbox_Iq(q, a, b, c, da, db, dc, slda, sldb, sldc, sld_core) 634 #check_shape(shape, fn) 635 636 view = (20, 30, 40) 637 def fn_xy(qx, qy): 638 return csbox_Iqxy(qx, qy, a, b, c, da, db, dc, 639 slda, sldb, sldc, sld_core, view=view) 640 check_shape_2d(shape, fn_xy, view=view) 453 641 454 642 if __name__ == "__main__": 455 643 check_cylinder(radius=10, length=40) 644 #check_cylinder_2d(radius=10, length=40, view=(90,30,0)) 645 #check_cylinder_2d_lattice(radius=10, length=50, view=(90,30,0)) 456 646 #check_sphere() 457 647 #check_csbox() -
sasmodels/compare.py
r2d81cfe r2a7e20e 92 92 -accuracy=Low accuracy of the resolution calculation Low, Mid, High, Xhigh 93 93 -neval=1 sets the number of evals for more accurate timing 94 -ngauss=0 overrides the number of points in the 1-D gaussian quadrature 94 95 95 96 === precision options === -
sasmodels/details.py
r2d81cfe r108e70e 258 258 # type: (...) -> Sequence[np.ndarray] 259 259 """ 260 **Deprecated** Theta weights will be computed in the kernel wrapper if 261 they are needed. 262 260 263 If there is a theta parameter, update the weights of that parameter so that 261 264 the cosine weighting required for polar integration is preserved. … … 272 275 Returns updated weights vectors 273 276 """ 274 # TODO: explain in a comment why scale and background are missing275 277 # Apparently the parameters.theta_offset similarly skips scale and 276 278 # and background, so the indexing works out, but they are still shipped … … 279 281 index = parameters.theta_offset 280 282 theta = dispersity[index] 281 # TODO: modify the dispersity vector to avoid the theta=-90,90,270,...282 283 theta_weight = abs(cos(radians(theta))) 283 284 weights = tuple(theta_weight*w if k == index else w -
sasmodels/generate.py
r2d81cfe r108e70e 7 7 particular dimensions averaged over all orientations. 8 8 9 *Iqxy(qx, qy, p1, p2, ...)* returns the scattering at qx, qy for a form 10 with particular dimensions for a single orientation. 11 12 *Imagnetic(qx, qy, result[], p1, p2, ...)* returns the scattering for the 13 polarized neutron spin states (up-up, up-down, down-up, down-down) for 14 a form with particular dimensions for a single orientation. 9 *Iqac(qab, qc, p1, p2, ...)* returns the scattering at qab, qc 10 for a rotationally symmetric form with particular dimensions. 11 qab, qc are determined from shape orientation and scattering angles. 12 This call is used if the shape has orientation parameters theta and phi. 13 14 *Iqabc(qa, qb, qc, p1, p2, ...)* returns the scattering at qa, qb, qc 15 for a form with particular dimensions. qa, qb, qc are determined from 16 shape orientation and scattering angles. This call is used if the shape 17 has orientation parameters theta, phi and psi. 18 19 *Iqxy(qx, qy, p1, p2, ...)* returns the scattering at qx, qy. Use this 20 to create an arbitrary 2D theory function, needed for q-dependent 21 background functions and for models with non-uniform magnetism. 15 22 16 23 *form_volume(p1, p2, ...)* returns the volume of the form with particular … … 31 38 scale and background parameters for each model. 32 39 33 *Iq*, *Iqxy*, *Imagnetic* and *form_volume* should be stylized C-99 34 functions written for OpenCL. All functions need prototype declarations 35 even if the are defined before they are used. OpenCL does not support 36 *#include* preprocessor directives, so instead the list of includes needs 37 to be given as part of the metadata in the kernel module definition. 38 The included files should be listed using a path relative to the kernel 39 module, or if using "lib/file.c" if it is one of the standard includes 40 provided with the sasmodels source. The includes need to be listed in 41 order so that functions are defined before they are used. 40 C code should be stylized C-99 functions written for OpenCL. All functions 41 need prototype declarations even if the are defined before they are used. 42 Although OpenCL supports *#include* preprocessor directives, the list of 43 includes should be given as part of the metadata in the kernel module 44 definition. The included files should be listed using a path relative to the 45 kernel module, or if using "lib/file.c" if it is one of the standard includes 46 provided with the sasmodels source. The includes need to be listed in order 47 so that functions are defined before they are used. 42 48 43 49 Floating point values should be declared as *double*. For single precision … … 107 113 present, the volume ratio is 1. 108 114 109 *form_volume*, *Iq*, *Iq xy*, *Imagnetic* are strings containing the110 C source code for the body of the volume, Iq, and Iqxyfunctions115 *form_volume*, *Iq*, *Iqac*, *Iqabc* are strings containing 116 the C source code for the body of the volume, Iq, and Iqac functions 111 117 respectively. These can also be defined in the last source file. 112 118 113 *Iq* and *Iqxy* also be instead be python functions defining the119 *Iq*, *Iqac*, *Iqabc* also be instead be python functions defining the 114 120 kernel. If they are marked as *Iq.vectorized = True* then the 115 121 kernel is passed the entire *q* vector at once, otherwise it is … … 168 174 from zlib import crc32 169 175 from inspect import currentframe, getframeinfo 176 import logging 170 177 171 178 import numpy as np # type: ignore … … 181 188 pass 182 189 # pylint: enable=unused-import 190 191 logger = logging.getLogger(__name__) 183 192 184 193 # jitter projection to use in the kernel code. See explore/jitter.py … … 626 635 627 636 """ 628 def _gen_fn( name, pars, body, filename, line):629 # type: ( str, List[Parameter], str, str, int) -> str637 def _gen_fn(model_info, name, pars): 638 # type: (ModelInfo, str, List[Parameter]) -> str 630 639 """ 631 640 Generate a function given pars and body. … … 639 648 """ 640 649 par_decl = ', '.join(p.as_function_argument() for p in pars) if pars else 'void' 650 body = getattr(model_info, name) 651 filename = model_info.filename 652 # Note: if symbol is defined strangely in the module then default it to 1 653 lineno = model_info.lineno.get(name, 1) 641 654 return _FN_TEMPLATE % { 642 655 'name': name, 'pars': par_decl, 'body': body, 643 'filename': filename.replace('\\', '\\\\'), 'line': line ,656 'filename': filename.replace('\\', '\\\\'), 'line': lineno, 644 657 } 645 658 … … 656 669 657 670 # type in IQXY pattern could be single, float, double, long double, ... 658 _IQXY_PATTERN = re.compile( "^((inline|static) )? *([a-z ]+ )? *Iqxy *([(]|$)",671 _IQXY_PATTERN = re.compile(r"(^|\s)double\s+I(?P<mode>q(ab?c|xy))\s*[(]", 659 672 flags=re.MULTILINE) 660 def _have_Iqxy(sources):673 def find_xy_mode(source): 661 674 # type: (List[str]) -> bool 662 675 """ 663 Return t rue if any file defines Iqxy.676 Return the xy mode as qa, qac, qabc or qxy. 664 677 665 678 Note this is not a C parser, and so can be easily confused by 666 679 non-standard syntax. Also, it will incorrectly identify the following 667 as having Iqxy::680 as having 2D models:: 668 681 669 682 /* 670 double Iq xy(qx, qy, ...) { ... fill this in later ... }683 double Iqac(qab, qc, ...) { ... fill this in later ... } 671 684 */ 672 685 673 If you want to comment out an Iqxy function, use // on the front of the 674 line instead. 675 """ 676 for _path, code in sources: 677 if _IQXY_PATTERN.search(code): 678 return True 679 return False 680 681 682 def _add_source(source, code, path): 686 If you want to comment out the function, use // on the front of the 687 line:: 688 689 /* 690 // double Iqac(qab, qc, ...) { ... fill this in later ... } 691 */ 692 693 """ 694 for code in source: 695 m = _IQXY_PATTERN.search(code) 696 if m is not None: 697 return m.group('mode') 698 return 'qa' 699 700 701 def _add_source(source, code, path, lineno=1): 683 702 """ 684 703 Add a file to the list of source code chunks, tagged with path and line. 685 704 """ 686 705 path = path.replace('\\', '\\\\') 687 source.append('#line 1 "%s"' % path)706 source.append('#line %d "%s"' % (lineno, path)) 688 707 source.append(code) 689 708 … … 716 735 user_code = [(f, open(f).read()) for f in model_sources(model_info)] 717 736 718 # What kind of 2D model do we need?719 xy_mode = ('qa' if not _have_Iqxy(user_code) and not isinstance(model_info.Iqxy, str)720 else 'qac' if not partable.is_asymmetric721 else 'qabc')722 723 737 # Build initial sources 724 738 source = [] … … 727 741 _add_source(source, code, path) 728 742 743 if model_info.c_code: 744 _add_source(source, model_info.c_code, model_info.filename, 745 lineno=model_info.lineno.get('c_code', 1)) 746 729 747 # Make parameters for q, qx, qy so that we can use them in declarations 730 q, qx, qy = [Parameter(name=v) for v in ('q', 'qx', 'qy')] 748 q, qx, qy, qab, qa, qb, qc \ 749 = [Parameter(name=v) for v in 'q qx qy qab qa qb qc'.split()] 731 750 # Generate form_volume function, etc. from body only 732 751 if isinstance(model_info.form_volume, str): 733 752 pars = partable.form_volume_parameters 734 source.append(_gen_fn('form_volume', pars, model_info.form_volume, 735 model_info.filename, model_info._form_volume_line)) 753 source.append(_gen_fn(model_info, 'form_volume', pars)) 736 754 if isinstance(model_info.Iq, str): 737 755 pars = [q] + partable.iq_parameters 738 source.append(_gen_fn('Iq', pars, model_info.Iq, 739 model_info.filename, model_info._Iq_line)) 756 source.append(_gen_fn(model_info, 'Iq', pars)) 740 757 if isinstance(model_info.Iqxy, str): 741 pars = [qx, qy] + partable.iqxy_parameters 742 source.append(_gen_fn('Iqxy', pars, model_info.Iqxy, 743 model_info.filename, model_info._Iqxy_line)) 758 pars = [qx, qy] + partable.iq_parameters + partable.orientation_parameters 759 source.append(_gen_fn(model_info, 'Iqxy', pars)) 760 if isinstance(model_info.Iqac, str): 761 pars = [qab, qc] + partable.iq_parameters 762 source.append(_gen_fn(model_info, 'Iqac', pars)) 763 if isinstance(model_info.Iqabc, str): 764 pars = [qa, qb, qc] + partable.iq_parameters 765 source.append(_gen_fn(model_info, 'Iqabc', pars)) 766 767 # What kind of 2D model do we need? Is it consistent with the parameters? 768 xy_mode = find_xy_mode(source) 769 if xy_mode == 'qabc' and not partable.is_asymmetric: 770 raise ValueError("asymmetric oriented models need to define Iqabc") 771 elif xy_mode == 'qac' and partable.is_asymmetric: 772 raise ValueError("symmetric oriented models need to define Iqac") 773 elif not partable.orientation_parameters and xy_mode in ('qac', 'qabc'): 774 raise ValueError("Unexpected function I%s for unoriented shape"%xy_mode) 775 elif partable.orientation_parameters and xy_mode not in ('qac', 'qabc'): 776 if xy_mode == 'qxy': 777 logger.warn("oriented shapes should define Iqac or Iqabc") 778 else: 779 raise ValueError("Expected function Iqac or Iqabc for oriented shape") 744 780 745 781 # Define the parameter table … … 767 803 if xy_mode == 'qabc': 768 804 pars = ",".join(["_qa", "_qb", "_qc"] + model_refs) 769 call_iqxy = "#define CALL_IQ_ABC(_qa,_qb,_qc,_v) Iq xy(%s)" % pars805 call_iqxy = "#define CALL_IQ_ABC(_qa,_qb,_qc,_v) Iqabc(%s)" % pars 770 806 clear_iqxy = "#undef CALL_IQ_ABC" 771 807 elif xy_mode == 'qac': 772 808 pars = ",".join(["_qa", "_qc"] + model_refs) 773 call_iqxy = "#define CALL_IQ_AC(_qa,_qc,_v) Iq xy(%s)" % pars809 call_iqxy = "#define CALL_IQ_AC(_qa,_qc,_v) Iqac(%s)" % pars 774 810 clear_iqxy = "#undef CALL_IQ_AC" 775 el se: # xy_mode == 'qa'811 elif xy_mode == 'qa': 776 812 pars = ",".join(["_qa"] + model_refs) 777 813 call_iqxy = "#define CALL_IQ_A(_qa,_v) Iq(%s)" % pars 778 814 clear_iqxy = "#undef CALL_IQ_A" 815 elif xy_mode == 'qxy': 816 orientation_refs = _call_pars("_v.", partable.orientation_parameters) 817 pars = ",".join(["_qx", "_qy"] + model_refs + orientation_refs) 818 call_iqxy = "#define CALL_IQ_XY(_qx,_qy,_v) Iqxy(%s)" % pars 819 clear_iqxy = "#undef CALL_IQ_XY" 820 if partable.orientation_parameters: 821 call_iqxy += "\n#define HAVE_THETA" 822 clear_iqxy += "\n#undef HAVE_THETA" 823 if partable.is_asymmetric: 824 call_iqxy += "\n#define HAVE_PSI" 825 clear_iqxy += "\n#undef HAVE_PSI" 826 779 827 780 828 magpars = [k-2 for k, p in enumerate(partable.call_parameters) -
sasmodels/kernel_header.c
r8698a0d r108e70e 150 150 inline double cube(double x) { return x*x*x; } 151 151 inline double sas_sinx_x(double x) { return x==0 ? 1.0 : sin(x)/x; } 152 153 // CRUFT: support old style models with orientation received qx, qy and angles 154 155 // To rotate from the canonical position to theta, phi, psi, first rotate by 156 // psi about the major axis, oriented along z, which is a rotation in the 157 // detector plane xy. Next rotate by theta about the y axis, aligning the major 158 // axis in the xz plane. Finally, rotate by phi in the detector plane xy. 159 // To compute the scattering, undo these rotations in reverse order: 160 // rotate in xy by -phi, rotate in xz by -theta, rotate in xy by -psi 161 // The returned q is the length of the q vector and (xhat, yhat, zhat) is a unit 162 // vector in the q direction. 163 // To change between counterclockwise and clockwise rotation, change the 164 // sign of phi and psi. 165 166 #if 1 167 //think cos(theta) should be sin(theta) in new coords, RKH 11Jan2017 168 #define ORIENT_SYMMETRIC(qx, qy, theta, phi, q, sn, cn) do { \ 169 SINCOS(phi*M_PI_180, sn, cn); \ 170 q = sqrt(qx*qx + qy*qy); \ 171 cn = (q==0. ? 1.0 : (cn*qx + sn*qy)/q * sin(theta*M_PI_180)); \ 172 sn = sqrt(1 - cn*cn); \ 173 } while (0) 174 #else 175 // SasView 3.x definition of orientation 176 #define ORIENT_SYMMETRIC(qx, qy, theta, phi, q, sn, cn) do { \ 177 SINCOS(theta*M_PI_180, sn, cn); \ 178 q = sqrt(qx*qx + qy*qy);\ 179 cn = (q==0. ? 1.0 : (cn*cos(phi*M_PI_180)*qx + sn*qy)/q); \ 180 sn = sqrt(1 - cn*cn); \ 181 } while (0) 182 #endif 183 184 #if 1 185 #define ORIENT_ASYMMETRIC(qx, qy, theta, phi, psi, q, xhat, yhat, zhat) do { \ 186 q = sqrt(qx*qx + qy*qy); \ 187 const double qxhat = qx/q; \ 188 const double qyhat = qy/q; \ 189 double sin_theta, cos_theta; \ 190 double sin_phi, cos_phi; \ 191 double sin_psi, cos_psi; \ 192 SINCOS(theta*M_PI_180, sin_theta, cos_theta); \ 193 SINCOS(phi*M_PI_180, sin_phi, cos_phi); \ 194 SINCOS(psi*M_PI_180, sin_psi, cos_psi); \ 195 xhat = qxhat*(-sin_phi*sin_psi + cos_theta*cos_phi*cos_psi) \ 196 + qyhat*( cos_phi*sin_psi + cos_theta*sin_phi*cos_psi); \ 197 yhat = qxhat*(-sin_phi*cos_psi - cos_theta*cos_phi*sin_psi) \ 198 + qyhat*( cos_phi*cos_psi - cos_theta*sin_phi*sin_psi); \ 199 zhat = qxhat*(-sin_theta*cos_phi) \ 200 + qyhat*(-sin_theta*sin_phi); \ 201 } while (0) 202 #else 203 // SasView 3.x definition of orientation 204 #define ORIENT_ASYMMETRIC(qx, qy, theta, phi, psi, q, cos_alpha, cos_mu, cos_nu) do { \ 205 q = sqrt(qx*qx + qy*qy); \ 206 const double qxhat = qx/q; \ 207 const double qyhat = qy/q; \ 208 double sin_theta, cos_theta; \ 209 double sin_phi, cos_phi; \ 210 double sin_psi, cos_psi; \ 211 SINCOS(theta*M_PI_180, sin_theta, cos_theta); \ 212 SINCOS(phi*M_PI_180, sin_phi, cos_phi); \ 213 SINCOS(psi*M_PI_180, sin_psi, cos_psi); \ 214 cos_alpha = cos_theta*cos_phi*qxhat + sin_theta*qyhat; \ 215 cos_mu = (-sin_theta*cos_psi*cos_phi - sin_psi*sin_phi)*qxhat + cos_theta*cos_psi*qyhat; \ 216 cos_nu = (-cos_phi*sin_psi*sin_theta + sin_phi*cos_psi)*qxhat + sin_psi*cos_theta*qyhat; \ 217 } while (0) 218 #endif -
sasmodels/kernel_iq.c
rec8d4ac rec8d4ac 31 31 // CALL_IQ_AC(qa, qc, table) : call the Iqxy function for symmetric shapes 32 32 // CALL_IQ_ABC(qa, qc, table) : call the Iqxy function for asymmetric shapes 33 // CALL_IQ_XY(qx, qy, table) : call the Iqxy function for arbitrary models 33 34 // INVALID(table) : test if the current point is feesible to calculate. This 34 35 // will be defined in the kernel definition file. … … 469 470 #define APPLY_ROTATION() qabc_apply(&rotation, qx, qy, &qa, &qb, &qc) 470 471 #define CALL_KERNEL() CALL_IQ_ABC(qa, qb, qc, local_values.table) 471 #endif 472 473 // Doing jitter projection code outside the previous if block so that we don't 474 // need to repeat the identical logic in the IQ_AC and IQ_ABC branches. This 475 // will become more important if we implement more projections, or more 476 // complicated projections. 477 #if defined(CALL_IQ) || defined(CALL_IQ_A) 472 #elif defined(CALL_IQ_XY) 473 // direct call to qx,qy calculator 474 double qx, qy; 475 #define FETCH_Q() do { qx = q[2*q_index]; qy = q[2*q_index+1]; } while (0) 476 #define BUILD_ROTATION() do {} while(0) 477 #define APPLY_ROTATION() do {} while(0) 478 #define CALL_KERNEL() CALL_IQ_XY(qx, qy, local_values.table) 479 #endif 480 481 // Define APPLY_PROJECTION depending on model symmetries. We do this outside 482 // the previous if block so that we don't need to repeat the identical 483 // logic in the IQ_AC and IQ_ABC branches. This will become more important 484 // if we implement more projections, or more complicated projections. 485 #if defined(CALL_IQ) || defined(CALL_IQ_A) // no orientation 478 486 #define APPLY_PROJECTION() const double weight=weight0 479 #else // !spherosymmetric projection 487 #elif defined(CALL_IQ_XY) // pass orientation to the model 488 // CRUFT: support oriented model which define Iqxy rather than Iqac or Iqabc 489 // Need to plug the values for the orientation angles back into parameter 490 // table in case they were overridden by the orientation offset. This 491 // means that orientation dispersity will not work for these models, but 492 // it was broken anyway, so no matter. Still want to provide Iqxy in case 493 // the user model wants full control of orientation/magnetism. 494 #if defined(HAVE_PSI) 495 const double theta = values[details->theta_par+2]; 496 const double phi = values[details->theta_par+3]; 497 const double psi = values[details->theta_par+4]; 498 double weight; 499 #define APPLY_PROJECTION() do { \ 500 local_values.table.theta = theta; \ 501 local_values.table.phi = phi; \ 502 local_values.table.psi = psi; \ 503 weight=weight0; \ 504 } while (0) 505 #elif defined(HAVE_THETA) 506 const double theta = values[details->theta_par+2]; 507 const double phi = values[details->theta_par+3]; 508 double weight; 509 #define APPLY_PROJECTION() do { \ 510 local_values.table.theta = theta; \ 511 local_values.table.phi = phi; \ 512 weight=weight0; \ 513 } while (0) 514 #else 515 #define APPLY_PROJECTION() const double weight=weight0 516 #endif 517 #else // apply jitter and view before calling the model 480 518 // Grab the "view" angles (theta, phi, psi) from the initial parameter table. 481 519 const double theta = values[details->theta_par+2]; … … 488 526 // we go through the mesh. 489 527 double dtheta, dphi, weight; 490 #if PROJECTION == 1 528 #if PROJECTION == 1 // equirectangular 491 529 #define APPLY_PROJECTION() do { \ 492 530 dtheta = local_values.table.theta; \ … … 494 532 weight = fabs(cos(dtheta*M_PI_180)) * weight0; \ 495 533 } while (0) 496 #elif PROJECTION == 2 534 #elif PROJECTION == 2 // sinusoidal 497 535 #define APPLY_PROJECTION() do { \ 498 536 dtheta = local_values.table.theta; \ … … 504 542 } while (0) 505 543 #endif 506 #endif // !spherosymmetric projection544 #endif // done defining APPLY_PROJECTION 507 545 508 546 // ** define looping macros ** -
sasmodels/kernelpy.py
r2d81cfe r108e70e 26 26 # pylint: enable=unused-import 27 27 28 logger = logging.getLogger(__name__) 29 28 30 class PyModel(KernelModel): 29 31 """ … … 31 33 """ 32 34 def __init__(self, model_info): 33 # Make sure Iq and Iqxy areavailable and vectorized35 # Make sure Iq is available and vectorized 34 36 _create_default_functions(model_info) 35 37 self.info = model_info 36 38 self.dtype = np.dtype('d') 37 logg ing.info("load python model " + self.info.name)39 logger.info("load python model " + self.info.name) 38 40 39 41 def make_kernel(self, q_vectors): 40 42 q_input = PyInput(q_vectors, dtype=F64) 41 kernel = self.info.Iqxy if q_input.is_2d else self.info.Iq 42 return PyKernel(kernel, self.info, q_input) 43 return PyKernel(self.info, q_input) 43 44 44 45 def release(self): … … 89 90 Callable SAS kernel. 90 91 91 *kernel* is the DllKernel object to call.92 *kernel* is the kernel object to call. 92 93 93 94 *model_info* is the module information … … 104 105 Call :meth:`release` when done with the kernel instance. 105 106 """ 106 def __init__(self, kernel,model_info, q_input):107 def __init__(self, model_info, q_input): 107 108 # type: (callable, ModelInfo, List[np.ndarray]) -> None 108 109 self.dtype = np.dtype('d') … … 110 111 self.q_input = q_input 111 112 self.res = np.empty(q_input.nq, q_input.dtype) 112 self.kernel = kernel113 113 self.dim = '2d' if q_input.is_2d else '1d' 114 114 … … 159 159 # Generate a closure which calls the form_volume if it exists. 160 160 form_volume = model_info.form_volume 161 self._volume = ((lambda: form_volume(*volume_args)) if form_volume 162 else(lambda: 1.0))161 self._volume = ((lambda: form_volume(*volume_args)) if form_volume else 162 (lambda: 1.0)) 163 163 164 164 def __call__(self, call_details, values, cutoff, magnetic): … … 261 261 any functions that are not already marked as vectorized. 262 262 """ 263 # Note: must call create_vector_Iq before create_vector_Iqxy 263 264 _create_vector_Iq(model_info) 264 _create_vector_Iqxy(model_info) # call create_vector_Iq() first265 _create_vector_Iqxy(model_info) 265 266 266 267 … … 280 281 model_info.Iq = vector_Iq 281 282 283 282 284 def _create_vector_Iqxy(model_info): 283 285 """ 284 286 Define Iqxy as a vector function if it exists, or default it from Iq(). 285 287 """ 286 Iq , Iqxy = model_info.Iq, model_info.Iqxy288 Iqxy = getattr(model_info, 'Iqxy', None) 287 289 if callable(Iqxy): 288 290 if not getattr(Iqxy, 'vectorized', False): … … 295 297 vector_Iqxy.vectorized = True 296 298 model_info.Iqxy = vector_Iqxy 297 el if callable(Iq):299 else: 298 300 #print("defaulting Iqxy") 299 301 # Iq is vectorized because create_vector_Iq was already called. 302 Iq = model_info.Iq 300 303 def default_Iqxy(qx, qy, *args): 301 304 """ -
sasmodels/modelinfo.py
r2d81cfe r108e70e 37 37 38 38 # assumptions about common parameters exist throughout the code, such as: 39 # (1) kernel functions Iq, Iqxy, form_volume, ... don't see them39 # (1) kernel functions Iq, Iqxy, Iqac, Iqabc, form_volume, ... don't see them 40 40 # (2) kernel drivers assume scale is par[0] and background is par[1] 41 41 # (3) mixture models drop the background on components and replace the scale … … 256 256 257 257 *type* indicates how the parameter will be used. "volume" parameters 258 will be used in all functions. "orientation" parameters will be used259 in *Iqxy* and *Imagnetic*. "magnetic* parameters will be used in260 *I magnetic* only. If *type* is the empty string, the parameter will258 will be used in all functions. "orientation" parameters are not passed, 259 but will be used to convert from *qx*, *qy* to *qa*, *qb*, *qc* in calls to 260 *Iqxy* and *Imagnetic*. If *type* is the empty string, the parameter will 261 261 be used in all of *Iq*, *Iqxy* and *Imagnetic*. "sld" parameters 262 262 can automatically be promoted to magnetic parameters, each of which … … 386 386 with vector parameter p sent as p[]. 387 387 388 * [removed] *iqxy_parameters* is the list of parameters to the Iqxy(qx, qy, ...)389 function, with vector parameter p sent as p[].390 391 388 * *form_volume_parameters* is the list of parameters to the form_volume(...) 392 389 function, with vector parameter p sent as p[]. … … 443 440 self.iq_parameters = [p for p in self.kernel_parameters 444 441 if p.type not in ('orientation', 'magnetic')] 445 # note: orientation no longer sent to Iqxy, so its the same as 446 #self.iqxy_parameters = [p for p in self.kernel_parameters 447 # if p.type != 'magnetic'] 442 self.orientation_parameters = [p for p in self.kernel_parameters 443 if p.type == 'orientation'] 448 444 self.form_volume_parameters = [p for p in self.kernel_parameters 449 445 if p.type == 'volume'] … … 490 486 if p.type != 'orientation': 491 487 raise TypeError("psi must be an orientation parameter") 488 elif p.type == 'orientation': 489 raise TypeError("only theta, phi and psi can be orientation parameters") 492 490 if theta >= 0 and phi >= 0: 491 last_par = len(self.kernel_parameters) - 1 493 492 if phi != theta+1: 494 493 raise TypeError("phi must follow theta") 495 494 if psi >= 0 and psi != phi+1: 496 495 raise TypeError("psi must follow phi") 496 #if (psi >= 0 and psi != last_par) or (psi < 0 and phi != last_par): 497 # raise TypeError("orientation parameters must appear at the " 498 # "end of the parameter table") 497 499 elif theta >= 0 or phi >= 0 or psi >= 0: 498 500 raise TypeError("oriented shapes must have both theta and phi and maybe psi") … … 715 717 716 718 719 #: Set of variables defined in the model that might contain C code 720 C_SYMBOLS = ['Imagnetic', 'Iq', 'Iqxy', 'Iqac', 'Iqabc', 'form_volume', 'c_code'] 721 717 722 def _find_source_lines(model_info, kernel_module): 718 723 # type: (ModelInfo, ModuleType) -> None … … 720 725 Identify the location of the C source inside the model definition file. 721 726 722 This code runs through the source of the kernel module looking for 723 lines that start with 'Iq', 'Iqxy' or 'form_volume'. Clearly there are 724 all sorts of reasons why this might not work (e.g., code commented out 725 in a triple-quoted line block, code built using string concatenation, 726 or code defined in the branch of an 'if' block), but it should work 727 properly in the 95% case, and getting the incorrect line number will 728 be harmless. 729 """ 730 # Check if we need line numbers at all 731 if callable(model_info.Iq): 732 return None 733 734 if (model_info.Iq is None 735 and model_info.Iqxy is None 736 and model_info.Imagnetic is None 737 and model_info.form_volume is None): 727 This code runs through the source of the kernel module looking for lines 728 that contain C code (because it is a c function definition). Clearly 729 there are all sorts of reasons why this might not work (e.g., code 730 commented out in a triple-quoted line block, code built using string 731 concatenation, code defined in the branch of an 'if' block, code imported 732 from another file), but it should work properly in the 95% case, and for 733 the remainder, getting the incorrect line number will merely be 734 inconvenient. 735 """ 736 # Only need line numbers if we are creating a C module and the C symbols 737 # are defined. 738 if (callable(model_info.Iq) 739 or not any(hasattr(model_info, s) for s in C_SYMBOLS)): 738 740 return 739 741 740 # find the defintion lines for the different code blocks742 # load the module source if we can 741 743 try: 742 744 source = inspect.getsource(kernel_module) 743 745 except IOError: 744 746 return 745 for k, v in enumerate(source.split('\n')): 746 if v.startswith('Imagnetic'): 747 model_info._Imagnetic_line = k+1 748 elif v.startswith('Iqxy'): 749 model_info._Iqxy_line = k+1 750 elif v.startswith('Iq'): 751 model_info._Iq_line = k+1 752 elif v.startswith('form_volume'): 753 model_info._form_volume_line = k+1 754 747 748 # look for symbol at the start of the line 749 for lineno, line in enumerate(source.split('\n')): 750 for name in C_SYMBOLS: 751 if line.startswith(name): 752 # Add 1 since some compilers complain about "#line 0" 753 model_info.lineno[name] = lineno + 1 754 break 755 755 756 756 def make_model_info(kernel_module): … … 761 761 Fill in default values for parts of the module that are not provided. 762 762 763 Note: vectorized Iq and Iq xyfunctions will be created for python763 Note: vectorized Iq and Iqac/Iqabc functions will be created for python 764 764 models when the model is first called, not when the model is loaded. 765 765 """ … … 790 790 info.profile_axes = getattr(kernel_module, 'profile_axes', ['x', 'y']) 791 791 info.source = getattr(kernel_module, 'source', []) 792 info.c_code = getattr(kernel_module, 'c_code', None) 792 793 # TODO: check the structure of the tests 793 794 info.tests = getattr(kernel_module, 'tests', []) … … 797 798 info.Iq = getattr(kernel_module, 'Iq', None) # type: ignore 798 799 info.Iqxy = getattr(kernel_module, 'Iqxy', None) # type: ignore 800 info.Iqac = getattr(kernel_module, 'Iqac', None) # type: ignore 801 info.Iqabc = getattr(kernel_module, 'Iqabc', None) # type: ignore 799 802 info.Imagnetic = getattr(kernel_module, 'Imagnetic', None) # type: ignore 800 803 info.profile = getattr(kernel_module, 'profile', None) # type: ignore … … 811 814 info.hidden = getattr(kernel_module, 'hidden', None) # type: ignore 812 815 816 if callable(info.Iq) and parameters.has_2d: 817 raise ValueError("oriented python models not supported") 818 819 info.lineno = {} 813 820 _find_source_lines(info, kernel_module) 814 821 … … 824 831 825 832 The structure should be mostly static, other than the delayed definition 826 of *Iq* and *Iqxy* if they need to be defined.833 of *Iq*, *Iqac* and *Iqabc* if they need to be defined. 827 834 """ 828 835 #: Full path to the file defining the kernel, if any. … … 906 913 structure_factor = None # type: bool 907 914 #: List of C source files used to define the model. The source files 908 #: should define the *Iq* function, and possibly *Iq xy*, though a default909 #: *Iqxy = Iq(sqrt(qx**2+qy**2)* will be created if no *Iqxy* is provided.910 #: Files containing the most basic functions must appear first in the list,911 #: followed by the files that use those functions. Form factors are912 #: indicated by providing a:attr:`ER` function.915 #: should define the *Iq* function, and possibly *Iqac* or *Iqabc* if the 916 #: model defines orientation parameters. Files containing the most basic 917 #: functions must appear first in the list, followed by the files that 918 #: use those functions. Form factors are indicated by providing 919 #: an :attr:`ER` function. 913 920 source = None # type: List[str] 914 921 #: The set of tests that must pass. The format of the tests is described … … 935 942 #: See :attr:`ER` for details on the parameters. 936 943 VR = None # type: Optional[Callable[[np.ndarray], Tuple[np.ndarray, np.ndarray]]] 944 #: Arbitrary C code containing supporting functions, etc., to be inserted 945 #: after everything in source. This can include Iq and Iqxy functions with 946 #: the full function signature, including all parameters. 947 c_code = None 937 948 #: Returns the form volume for python-based models. Form volume is needed 938 949 #: for volume normalization in the polydispersity integral. If no … … 955 966 #: include the decimal point. See :mod:`generate` for more details. 956 967 Iq = None # type: Union[None, str, Callable[[np.ndarray], np.ndarray]] 957 #: Returns *I(qx, qy, a, b, ...)*. The interface follows :attr:`Iq`. 958 Iqxy = None # type: Union[None, str, Callable[[np.ndarray], np.ndarray]] 968 #: Returns *I(qab, qc, a, b, ...)*. The interface follows :attr:`Iq`. 969 Iqac = None # type: Union[None, str, Callable[[np.ndarray], np.ndarray]] 970 #: Returns *I(qa, qb, qc, a, b, ...)*. The interface follows :attr:`Iq`. 971 Iqabc = None # type: Union[None, str, Callable[[np.ndarray], np.ndarray]] 959 972 #: Returns *I(qx, qy, a, b, ...)*. The interface follows :attr:`Iq`. 960 973 Imagnetic = None # type: Union[None, str, Callable[[np.ndarray], np.ndarray]] … … 972 985 #: Returns a random parameter set for the model 973 986 random = None # type: Optional[Callable[[], Dict[str, float]]] 974 975 # line numbers within the python file for bits of C source, if defined 976 # NB: some compilers fail with a "#line 0" directive, so default to 1. 977 _Imagnetic_line = 1 978 _Iqxy_line = 1 979 _Iq_line = 1 980 _form_volume_line = 1 981 987 #: Line numbers for symbols defining C code 988 lineno = None # type: Dict[str, int] 982 989 983 990 def __init__(self): -
sasmodels/models/_spherepy.py
ref07e95 r108e70e 88 88 Iq.vectorized = True # Iq accepts an array of q values 89 89 90 def Iqxy(qx, qy, sld, sld_solvent, radius):91 return Iq(sqrt(qx ** 2 + qy ** 2), sld, sld_solvent, radius)92 Iqxy.vectorized = True # Iqxy accepts arrays of qx, qy values93 94 90 def sesans(z, sld, sld_solvent, radius): 95 91 """ -
sasmodels/models/barbell.c
r74768cb r108e70e 90 90 91 91 static double 92 Iq xy(double qab, double qc,92 Iqac(double qab, double qc, 93 93 double sld, double solvent_sld, 94 94 double radius_bell, double radius, double length) -
sasmodels/models/bcc_paracrystal.c
r74768cb r108e70e 107 107 108 108 109 static double Iq xy(double qa, double qb, double qc,109 static double Iqabc(double qa, double qb, double qc, 110 110 double dnn, double d_factor, double radius, 111 111 double sld, double solvent_sld) -
sasmodels/models/capped_cylinder.c
r74768cb r108e70e 115 115 116 116 static double 117 Iq xy(double qab, double qc,117 Iqac(double qab, double qc, 118 118 double sld, double solvent_sld, double radius, 119 119 double radius_cap, double length) -
sasmodels/models/core_shell_bicelle.c
r74768cb r108e70e 67 67 68 68 static double 69 Iq xy(double qab, double qc,69 Iqac(double qab, double qc, 70 70 double radius, 71 71 double thick_rim, -
sasmodels/models/core_shell_bicelle_elliptical.c
r74768cb r108e70e 71 71 72 72 static double 73 Iq xy(double qa, double qb, double qc,73 Iqabc(double qa, double qb, double qc, 74 74 double r_minor, 75 75 double x_core, -
sasmodels/models/core_shell_bicelle_elliptical_belt_rough.c
r74768cb r108e70e 79 79 80 80 static double 81 Iq xy(double qa, double qb, double qc,81 Iqabc(double qa, double qb, double qc, 82 82 double r_minor, 83 83 double x_core, … … 114 114 return 1.0e-4 * Aq*exp(-0.5*(square(qa) + square(qb) + square(qc) )*square(sigma)); 115 115 } 116 -
sasmodels/models/core_shell_bicelle_elliptical_belt_rough.py
r110f69c r108e70e 149 149 ["sld_rim", "1e-6/Ang^2", 1, [-inf, inf], "sld", "Cylinder rim scattering length density"], 150 150 ["sld_solvent", "1e-6/Ang^2", 6, [-inf, inf], "sld", "Solvent scattering length density"], 151 ["sigma", "Ang", 0, [0, inf], "", "interfacial roughness"], 151 152 ["theta", "degrees", 90.0, [-360, 360], "orientation", "cylinder axis to beam angle"], 152 153 ["phi", "degrees", 0, [-360, 360], "orientation", "rotation about beam"], 153 154 ["psi", "degrees", 0, [-360, 360], "orientation", "rotation about cylinder axis"], 154 ["sigma", "Ang", 0, [0, inf], "", "interfacial roughness"]155 155 ] 156 156 -
sasmodels/models/core_shell_cylinder.c
r74768cb r108e70e 48 48 49 49 50 double Iq xy(double qab, double qc,50 double Iqac(double qab, double qc, 51 51 double core_sld, 52 52 double shell_sld, -
sasmodels/models/core_shell_ellipsoid.c
r74768cb r108e70e 75 75 76 76 static double 77 Iq xy(double qab, double qc,77 Iqac(double qab, double qc, 78 78 double radius_equat_core, 79 79 double x_core, -
sasmodels/models/core_shell_parallelepiped.c
r4493288 re077231 43 43 // Code converted from functions CSPPKernel and CSParallelepiped in libCylinder.c 44 44 // Did not understand the code completely, it should be rechecked (Miguel Gonzalez) 45 // Code is rewritten, the code is compliant with Diva Singhs thesis now (Dirk Honecker)46 // Code rewritten (PAK)45 // Code is rewritten, the code is compliant with Diva Singh's thesis now (Dirk Honecker) 46 // Code rewritten; cross checked against hollow rectangular prism and realspace (PAK) 47 47 48 48 const double half_q = 0.5*q; … … 102 102 103 103 static double 104 Iq xy(double qa, double qb, double qc,104 Iqabc(double qa, double qb, double qc, 105 105 double core_sld, 106 106 double arim_sld, … … 121 121 const double drC = crim_sld-solvent_sld; 122 122 123 // The definitions of ta, tb, tc are not the same as in the 1D case because there is no124 // the scaling by B.125 123 const double tA = length_a + 2.0*thick_rim_a; 126 124 const double tB = length_b + 2.0*thick_rim_b; -
sasmodels/models/core_shell_parallelepiped.py
r10ee838 r97be877 136 136 * **Author:** NIST IGOR/DANSE **Date:** pre 2010 137 137 * **Converted to sasmodels by:** Miguel Gonzales **Date:** February 26, 2016 138 * **Last Modified by:** Wojciech Potrzebowski **Date:** January 11, 2017 139 * **Currently Under review by:** Paul Butler 138 * **Last Modified by:** Paul Kienzle **Date:** October 17, 2017 139 * Cross-checked against hollow rectangular prism and rectangular prism for 140 equal thickness overlapping sides, and by Monte Carlo sampling of points 141 within the shape for non-uniform, non-overlapping sides. 140 142 """ 141 143 -
sasmodels/models/cylinder.c
r74768cb r108e70e 45 45 46 46 static double 47 Iq xy(double qab, double qc,47 Iqac(double qab, double qc, 48 48 double sld, 49 49 double solvent_sld, -
sasmodels/models/ellipsoid.c
r74768cb r108e70e 39 39 40 40 static double 41 Iq xy(double qab, double qc,41 Iqac(double qab, double qc, 42 42 double sld, 43 43 double sld_solvent, -
sasmodels/models/elliptical_cylinder.c
r74768cb r108e70e 54 54 55 55 static double 56 Iq xy(double qa, double qb, double qc,56 Iqabc(double qa, double qb, double qc, 57 57 double radius_minor, double r_ratio, double length, 58 58 double sld, double solvent_sld) -
sasmodels/models/fcc_paracrystal.c
r74768cb r108e70e 80 80 81 81 82 static double Iq xy(double qa, double qb, double qc,82 static double Iqabc(double qa, double qb, double qc, 83 83 double dnn, double d_factor, double radius, 84 84 double sld, double solvent_sld) -
sasmodels/models/hollow_cylinder.c
r74768cb r108e70e 52 52 53 53 static double 54 Iq xy(double qab, double qc,54 Iqac(double qab, double qc, 55 55 double radius, double thickness, double length, 56 56 double sld, double solvent_sld) -
sasmodels/models/hollow_rectangular_prism.c
r74768cb r108e70e 85 85 } 86 86 87 double Iq xy(double qa, double qb, double qc,87 double Iqabc(double qa, double qb, double qc, 88 88 double sld, 89 89 double solvent_sld, -
sasmodels/models/line.py
r2d81cfe r108e70e 57 57 Iq.vectorized = True # Iq accepts an array of q values 58 58 59 59 60 def Iqxy(qx, qy, *args): 60 61 """ … … 69 70 70 71 Iqxy.vectorized = True # Iqxy accepts an array of qx qy values 72 73 # uncomment the following to test Iqxy in C models 74 #del Iq, Iqxy 75 #c_code = """ 76 #static double Iq(double q, double b, double m) { return m*q+b; } 77 #static double Iqxy(double qx, double qy, double b, double m) 78 #{ return (m*qx+b)*(m*qy+b); } 79 #""" 71 80 72 81 def random(): -
sasmodels/models/parallelepiped.c
r74768cb r108e70e 53 53 54 54 static double 55 Iq xy(double qa, double qb, double qc,55 Iqabc(double qa, double qb, double qc, 56 56 double sld, 57 57 double solvent_sld, -
sasmodels/models/rectangular_prism.c
r74768cb r108e70e 71 71 72 72 73 double Iq xy(double qa, double qb, double qc,73 double Iqabc(double qa, double qb, double qc, 74 74 double sld, 75 75 double solvent_sld, -
sasmodels/models/sc_paracrystal.c
r74768cb r108e70e 82 82 83 83 static double 84 Iq xy(double qa, double qb, double qc,84 Iqabc(double qa, double qb, double qc, 85 85 double dnn, double d_factor, double radius, 86 86 double sld, double solvent_sld) -
sasmodels/models/stacked_disks.c
r74768cb r108e70e 142 142 143 143 static double 144 Iq xy(double qab, double qc,144 Iqac(double qab, double qc, 145 145 double thick_core, 146 146 double thick_layer, -
sasmodels/models/triaxial_ellipsoid.c
r74768cb r108e70e 46 46 47 47 static double 48 Iq xy(double qa, double qb, double qc,48 Iqabc(double qa, double qb, double qc, 49 49 double sld, 50 50 double sld_solvent,
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