# Changeset 6d6832e in sasview

Ignore:
Timestamp:
Apr 7, 2017 5:16:20 AM (3 years ago)
Branches:
master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, magnetic_scatt, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload
Children:
62af61fd, d1bee3f
Parents:
9d06728 (diff), 5ed76f8 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.
Message:

Merge branch 'ticket-510' of https://github.com/SasView/sasview into ticket-510

Files:
5 deleted
14 edited

Unmodified
Removed
• ## src/sas/sascalc/calculator/sas_gen.py

 r9a5097c def set_sldms(self, sld_mx, sld_my, sld_mz): r""" Sets (\|m\|, m_theta, m_phi) """ Sets mx, my, mz and abs(m). """ # Note: escaping if sld_mx.__class__.__name__ == 'float': self.sld_mx = np.ones(len(self.pos_x)) * sld_mx
• ## src/sas/sasgui/guiframe/media/graph_help.rst

 rf9b0c81 SasView generates three different types of graph window: one that displays *1D data* (ie, I(Q) vs Q), one that displays *1D residuals* (ie, the difference between the experimental data and the theory at the same Q values), and *2D color maps*. (i.e., $I(Q)$ vs $Q$), one that displays *1D residuals* (ie, the difference between the experimental data and the theory at the same $Q$ values), and *2D color maps*. Graph window options plot window. .. note:: .. note:: *If a residuals graph (when fitting data) is hidden, it will not show up after computation.* style and size. *Remove Text* will remove the last annotation added. To change the legend. *Window Title* allows a custom title to be entered instead of Graph x. x. Changing scales ^^^^^^^^^^^^^^^^^^^ Linear fit performs a simple ( y(x)=ax+b ) linear fit within the plot window. Linear fit performs a simple $y(x)=ax+b$ linear fit within the plot window. In the *Dataset Menu* (see Invoking_the_dataset_menu_), select *Linear Fit*. A This option is most useful for performing simple Guinier, XS Guinier, and Porod type analyses, for example, to estimate Rg, a rod diameter, or incoherent Porod type analyses, for example, to estimate $R_g$, a rod diameter, or incoherent background level, respectively. ^^^^^^^^^^^^^^^^^^^^^^^^^ This operation will perform an average in constant Q-rings around the (x,y) This operation will perform an average in constant $Q$ rings around the (x,y) pixel location of the beam center. ^^^^^^^^^^^^^^^^^^^^^^^ This operation averages in constant Q-arcs. The width of the sector is specified in degrees (+/- |delta|\|phi|\) each side of the central angle (|phi|\). Annular average [|phi| View] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ This operation performs an average between two Q-values centered on (0,0), This operation averages in constant $Q$ arcs. The width of the sector is specified in degrees ($\pm\delta|\phi|$) each side of the central angle $\phi$. Annular average [:math:\phi] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ This operation performs an average between two $Q$ values centered on (0,0), and averaged over a specified number of pixels. The data is returned as a function of angle (|phi|\) in degrees with zero The data is returned as a function of angle $\phi$ in degrees with zero degrees at the 3 O'clock position. ^^^^^^^^^^^^^^^^^^^ This operation computes an average I(Qx) for the region of interest. This operation computes an average $I(Q_x)$ for the region of interest. When editing the slicer parameters, the user can control the length and the width the rectangular slicer. The averaged output is calculated from constant bins with rectangular shape. The resultant Q values are nominal values, that bins with rectangular shape. The resultant $Q$ values are nominal values, that is, the central value of each bin on the x-axis. ^^^^^^^^^^^^^^^^^^^ This operation computes an average I(Qy) for the region of interest. This operation computes an average $I(Q_y)$ for the region of interest. When editing the slicer parameters, the user can control the length and the width the rectangular slicer. The averaged output is calculated from constant bins with rectangular shape. The resultant Q values are nominal values, that bins with rectangular shape. The resultant $Q$ values are nominal values, that is, the central value of each bin on the x-axis.
• ## src/sas/sasgui/perspectives/calculator/media/kiessig_calculator_help.rst

 r7805458 ----------- This tool is approximately estimates the thickness of a layer or the diameter of particles from the position of the Kiessig fringe/Bragg peak in NR/SAS data using the relation This tool estimates real space dimensions from the position or spacing of features in recipricol space.  In particular a particle of size $d$ will give rise to Bragg peaks with spacing $\Delta q$ according to the relation (thickness *or* size) = 2 * |pi| / (fringe_width *or* peak position) .. math:: d = 2\pi / \Delta q Similarly, the spacing between the peaks in Kiessig fringes in reflectometry data arise from layers of thickness $d$. .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ -------------- To get a rough thickness or particle size, simply type the fringe or peak To get a rough thickness or particle size, simply type the fringe or peak position (in units of 1/|Ang|\) and click on the *Compute* button. .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ .. note::  This help document was last changed by Steve King, 01May2015 .. note::  This help document was last changed by Paul Kienzle, 05Apr2017
• ## src/sas/sasgui/perspectives/calculator/media/resolution_calculator_help.rst

 r6aad2e8 ----------- This tool is approximately estimates the resolution of Q from SAS instrumental parameter values assuming that the detector is flat and normal to the This tool is approximately estimates the resolution of $Q$ from SAS instrumental parameter values assuming that the detector is flat and normal to the incident beam. 2) Select the source (Neutron or Photon) and source type (Monochromatic or TOF). *NOTE! The computational difference between the sources is only the *NOTE! The computational difference between the sources is only the gravitational contribution due to the mass of the particles.* 3) Change the default values of the instrumental parameters as required. Be 3) Change the default values of the instrumental parameters as required. Be careful to note that distances are specified in cm! 4) Enter values for the source wavelength(s), |lambda|\ , and its spread (= FWHM/|lambda|\ ). For monochromatic sources, the inputs are just one value. For TOF sources, the minimum and maximum values should be separated by a '-' to specify a 4) Enter values for the source wavelength(s), $\lambda$, and its spread (= $\text{FWHM}/\lambda$). For monochromatic sources, the inputs are just one value. For TOF sources, the minimum and maximum values should be separated by a '-' to specify a range. Optionally, the wavelength (BUT NOT of the wavelength spread) can be extended by adding '; nn' where the 'nn' specifies the number of the bins for the numerical integration. The default value is nn = 10. The same number of bins Optionally, the wavelength (BUT NOT of the wavelength spread) can be extended by adding '; nn' where the 'nn' specifies the number of the bins for the numerical integration. The default value is nn = 10. The same number of bins will be used for the corresponding wavelength spread. 5) For TOF, the default wavelength spectrum is flat. A custom spectral distribution file (2-column text: wavelength (|Ang|\) vs Intensity) can also 5) For TOF, the default wavelength spectrum is flat. A custom spectral distribution file (2-column text: wavelength (|Ang|\) vs Intensity) can also be loaded by selecting *Add new* in the combo box. 6) When ready, click the *Compute* button. Depending on the computation the 6) When ready, click the *Compute* button. Depending on the computation the calculation time will vary. 7) 1D and 2D dQ values will be displayed at the bottom of the panel, and a 2D resolution weight distribution (a 2D elliptical Gaussian function) will also be displayed in the plot panel even if the Q inputs are outside of the 7) 1D and 2D $dQ$ values will be displayed at the bottom of the panel, and a 2D resolution weight distribution (a 2D elliptical Gaussian function) will also be displayed in the plot panel even if the $Q$ inputs are outside of the detector limit (the red lines indicate the limits of the detector). TOF only: green lines indicate the limits of the maximum Q range accessible TOF only: green lines indicate the limits of the maximum $Q$ range accessible for the longest wavelength due to the size of the detector. Note that the effect from the beam block/stop is ignored, so in the small Q region near the beam block/stop [ie., Q < 2. |pi|\ .(beam block diameter) / (sample-to-detector distance) / |lambda|\_min] Note that the effect from the beam block/stop is ignored, so in the small $Q$ region near the beam block/stop [i.e., $Q < (2 \pi \cdot \text{beam block diameter}) / (\text{sample-to-detector distance} \cdot \lambda_\text{min})$] the variance is slightly under estimated. 8) A summary of the calculation is written to the SasView *Console* at the 8) A summary of the calculation is written to the SasView *Console* at the bottom of the main SasView window. .. image:: q.png In the small-angle limit, the variance of Q is to a first-order In the small-angle limit, the variance of $Q$ is to a first-order approximation .. image:: sigma_table.png Finally, a Gaussian function is used to describe the 2D weighting distribution of the uncertainty in Q. Finally, a Gaussian function is used to describe the 2D weighting distribution of the uncertainty in $Q$. .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ ---------- D.F.R. Mildner and J.M. Carpenter D.F.R. Mildner and J.M. Carpenter *J. Appl. Cryst.* 17 (1984) 249-256 D.F.R. Mildner, J.M. Carpenter and D.L. Worcester D.F.R. Mildner, J.M. Carpenter and D.L. Worcester *J. Appl. Cryst.* 19 (1986) 311-319
• ## src/sas/sasgui/perspectives/calculator/media/sas_calculator_help.rst

 r6aad2e8 ------ In general, a particle with a volume *V* can be described by an ensemble containing *N* 3-dimensional rectangular pixels where each pixel is much smaller than *V*. In general, a particle with a volume $V$ can be described by an ensemble containing $N$ 3-dimensional rectangular pixels where each pixel is much smaller than $V$. Assuming that all the pixel sizes are the same, the elastic scattering Assuming that all the pixel sizes are the same, the elastic scattering intensity from the particle is Equation 1. where |beta|\ :sub:j and *r*\ :sub:j are the scattering length density and the position of the j'th pixel respectively. where $\beta_j$ and $r_j$ are the scattering length density and the position of the $j^\text{th}$ pixel respectively. The total volume *V* The total volume $V$ .. image:: v_j.png .. math:: for |beta|\ :sub:j |noteql|\0 where *v*\ :sub:j is the volume of the j'th pixel (or the j'th natural atomic volume (= atomic mass / (natural molar V = \sum_j^N v_j for $\beta_j \ne 0$ where $v_j$ is the volume of the $j^\text{th}$ pixel (or the $j^\text{th}$ natural atomic volume (= atomic mass / (natural molar density * Avogadro number) for the atomic structures). *V* can be corrected by users. This correction is useful especially for an atomic structure (such as taken from a PDB file) to get the right normalization. $V$ can be corrected by users. This correction is useful especially for an atomic structure (such as taken from a PDB file) to get the right normalization. *NOTE!* |beta|\ :sub:j *displayed in the GUI may be incorrect but this will not *NOTE! $\beta_j$ displayed in the GUI may be incorrect but this will not affect the scattering computation if the correction of the total volume V is made.* The scattering length density (SLD) of each pixel, where the SLD is uniform, is a combination of the nuclear and magnetic SLDs and depends on the spin states The scattering length density (SLD) of each pixel, where the SLD is uniform, is a combination of the nuclear and magnetic SLDs and depends on the spin states of the neutrons as follows. ^^^^^^^^^^^^^^^^^^^ For magnetic scattering, only the magnetization component, *M*\ :sub:perp\ , perpendicular to the scattering vector *Q* contributes to the magnetic For magnetic scattering, only the magnetization component, $M_\perp$, perpendicular to the scattering vector $Q$ contributes to the magnetic scattering length. .. image:: dm_eq.png where the gyromagnetic ratio |gamma| = -1.913, |mu|\ :sub:B is the Bohr magneton, *r*\ :sub:0 is the classical radius of electron, and |sigma| is the where the gyromagnetic ratio is $\gamma = -1.913$, $\mu_B$ is the Bohr magneton, $r_0$ is the classical radius of electron, and $\sigma$ is the Pauli spin. For a polarized neutron, the magnetic scattering is depending on the spin states. Let us consider that the incident neutrons are polarised both parallel (+) and anti-parallel (-) to the x' axis (see below). The possible states after scattering from the sample are then Let us consider that the incident neutrons are polarised both parallel (+) and anti-parallel (-) to the x' axis (see below). The possible states after scattering from the sample are then *  Non-spin flips: (+ +) and (- -) .. image:: gen_mag_pic.png Now let us assume that the angles of the *Q* vector and the spin-axis (x') to the x-axis are |phi| and |theta|\ :sub:up respectively (see above). Then, depending upon the polarization (spin) state of neutrons, the scattering length densities, including the nuclear scattering length density (|beta|\ :sub:N\ ) Now let us assume that the angles of the *Q* vector and the spin-axis (x') to the x-axis are $\phi$ and $\theta_\text{up}$ respectively (see above). Then, depending upon the polarization (spin) state of neutrons, the scattering length densities, including the nuclear scattering length density ($\beta_N$) are given as .. image:: mqy.png Here the *M0*\ :sub:x\ , *M0*\ :sub:y and *M0*\ :sub:z are the x, y and z components of the magnetisation vector in the laboratory xyz frame. Here the $M0_x$, $M0_y$ and $M0_z$ are the $x$, $y$ and $z$ components of the magnetisation vector in the laboratory $xyz$ frame. .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ .. image:: gen_gui_help.png After computation the result will appear in the *Theory* box in the SasView After computation the result will appear in the *Theory* box in the SasView *Data Explorer* panel. *Up_frac_in* and *Up_frac_out* are the ratio *Up_frac_in* and *Up_frac_out* are the ratio (spin up) / (spin up + spin down) of neutrons before the sample and at the analyzer, respectively. *NOTE 1. The values of* Up_frac_in *and* Up_frac_out *must be in the range *NOTE 1. The values of* Up_frac_in *and* Up_frac_out *must be in the range 0.0 to 1.0. Both values are 0.5 for unpolarized neutrons.* *NOTE 2. This computation is totally based on the pixel (or atomic) data fixed *NOTE 2. This computation is totally based on the pixel (or atomic) data fixed in xyz coordinates. No angular orientational averaging is considered.* *NOTE 3. For the nuclear scattering length density, only the real component *NOTE 3. For the nuclear scattering length density, only the real component is taken account.* The SANS Calculator tool can read some PDB, OMF or SLD files but ignores polarized/magnetic scattering when doing so, thus related parameters such as polarized/magnetic scattering when doing so, thus related parameters such as *Up_frac_in*, etc, will be ignored. The calculation for fixed orientation uses Equation 1 above resulting in a 2D output, whereas the scattering calculation averaged over all the orientations The calculation for fixed orientation uses Equation 1 above resulting in a 2D output, whereas the scattering calculation averaged over all the orientations uses the Debye equation below providing a 1D output .. image:: gen_debye_eq.png where *v*\ :sub:j |beta|\ :sub:j |equiv| *b*\ :sub:j is the scattering length of the j'th atom. The calculation output is passed to the *Data Explorer* where $v_j \beta_j \equiv b_j$ is the scattering length of the $j^\text{th}$ atom. The calculation output is passed to the *Data Explorer* for further use.
• ## src/sas/sasgui/perspectives/calculator/media/sld_calculator_help.rst

 rf93b473f ----------- The neutron scattering length density (SLD) is defined as The neutron scattering length density (SLD, $\beta_N$) is defined as SLD = (b_c1 + b_c2 + ... + b_cn) / Vm .. math:: where b_ci is the bound coherent scattering length of ith of n atoms in a molecule with the molecular volume Vm \beta_N = (b_{c1} + b_{c2} + ... + b_{cn}) / V_m where $b_{ci}$ is the bound coherent scattering length of ith of n atoms in a molecule with the molecular volume $V_m$. .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ ---------------------------- To calculate scattering length densities enter the empirical formula of a To calculate scattering length densities enter the empirical formula of a compound and its mass density and click "Calculate". Entering a wavelength value is optional (a default value of 6.0 |Ang| will Entering a wavelength value is optional (a default value of 6.0 |Ang| will be used). *  Parentheses can be nested, such as "(CaCO3(H2O)6)1". *  Isotopes are represented by their atomic number in *square brackets*, such *  Isotopes are represented by their atomic number in *square brackets*, such as "CaCO[18]3+6H2O", H[1], or H[2]. *  Numbers of atoms can be integer or decimal, such as "CaCO3+(3HO0.5)2". *  The SLD of mixtures can be calculated as well. For example, for a 70-30 *  The SLD of mixtures can be calculated as well. For example, for a 70-30 mixture of H2O/D2O write "H14O7+D6O3" or more simply "H7D3O5" (i.e. this says 7 hydrogens, 3 deuteriums, and 5 oxygens) and enter a mass density calculated on the percentages of H2O and D2O. *  Type "C[13]6 H[2]12 O[18]6" for C(13)6H(2)12O(18)6 (6 Carbon-13 atoms, 12 *  Type "C[13]6 H[2]12 O[18]6" for C(13)6H(2)12O(18)6 (6 Carbon-13 atoms, 12 deuterium atoms, and 6 Oxygen-18 atoms). .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ .. note::  This help document was last changed by Steve King, 01May2015 .. note::  This help document was last changed by Paul Kienzle, 05Apr2017
• ## src/sas/sasgui/perspectives/calculator/media/slit_calculator_help.rst

 rf93b473f ----------- This tool enables X-ray users to calculate the slit size (FWHM/2) for smearing This tool enables X-ray users to calculate the slit size (FWHM/2) for smearing based on their half beam profile data. *NOTE! Whilst it may have some more generic applicability, the calculator has only been tested with beam profile data from Anton-Paar SAXSess*\ |TM|\ *software.* only been tested with beam profile data from Anton-Paar SAXSess:sup:TM software.* .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ 2) Load a beam profile file in the *Data* field using the *Browse* button. *NOTE! To see an example of the beam profile file format, visit the file *NOTE! To see an example of the beam profile file format, visit the file beam profile.DAT in your {installation_directory}/SasView/test folder.* 3) Once a data is loaded, the slit size is automatically computed and displayed 3) Once a data is loaded, the slit size is automatically computed and displayed in the tool window. *NOTE! The beam profile file does not carry any information about the units of *NOTE! The beam profile file does not carry any information about the units of the Q data. This calculator assumes the data has units of 1/\ |Ang|\ . If the data is not in these units it must be manually converted beforehand.*
• ## src/sas/sasgui/perspectives/fitting/media/fitting_help.rst

 r6aad2e8 In the bottom left corner of the *Fit Page* is a box displaying the normalised value of the statistical |chi|\  :sup:2 parameter returned by the optimiser. of the statistical $\chi^2$ parameter returned by the optimiser. Now check the box for another model parameter and click *Fit* again. Repeat this fit of the theory to the experimental data improves the value of 'chi2/Npts' will decrease. A good model fit should easily produce values of 'chi2/Npts' that are close to zero, and certainly <100. See :ref:Assessing_Fit_Quality. close to one, and certainly <100. See :ref:Assessing_Fit_Quality. SasView has a number of different optimisers (see the section :ref:Fitting_Options).
• ## src/sas/sasgui/perspectives/fitting/media/mag_help.rst

 r6aad2e8 -------------------------------- Magnetic scattering is implemented in five (2D) models Magnetic scattering is implemented in five (2D) models *  *sphere* *  *parallelepiped* In general, the scattering length density (SLD, = |beta|) in each region where the In general, the scattering length density (SLD, = $\beta$) in each region where the SLD is uniform, is a combination of the nuclear and magnetic SLDs and, for polarised neutrons, also depends on the spin states of the neutrons. For magnetic scattering, only the magnetization component, *M*\ :sub:perp, perpendicular to the scattering vector *Q* contributes to the the magnetic For magnetic scattering, only the magnetization component, $M_\perp$, perpendicular to the scattering vector $Q$ contributes to the the magnetic scattering length. .. image:: dm_eq.png where |gamma| = -1.913 is the gyromagnetic ratio, |mu|\ :sub:B is the Bohr magneton, *r*\ :sub:0 is the classical radius of electron, and |sigma| where $\gamma = -1.913$ is the gyromagnetic ratio, $\mu_B$ is the Bohr magneton, $r_0$ is the classical radius of electron, and $\sigma$ is the Pauli spin. .. image:: M_angles_pic.png If the angles of the *Q* vector and the spin-axis (*x'*) to the *x*-axis are |phi| and |theta|\ :sub:up, respectively, then, depending on the spin state of the If the angles of the $Q$ vector and the spin-axis (*x'*) to the *x*-axis are $\phi$ and $\theta_\text{up}$, respectively, then, depending on the spin state of the neutrons, the scattering length densities, including the nuclear scattering length density (|beta|\ :sub:N) are length density ($\beta_N$) are .. image:: sld1.png .. image:: mqy.png Here, *M*\ :sub:0x, *M*\ :sub:0y and *M*\ :sub:0z are the x, y and z components of the magnetization vector given in the laboratory xyz frame given by Here, $M_{0x}$, $M_{0y}$ and $M_{0z}$ are the $x$, $y$ and $z$ components of the magnetization vector given in the laboratory $xyz$ frame given by .. image:: m0x_eq.png .. image:: m0z_eq.png and the magnetization angles |theta|\ :sub:M and |phi|\ :sub:M are defined in and the magnetization angles $\theta_M$ and $\phi_M$ are defined in the figure above. ===========   ================================================================ M0_sld        = *D*\ :sub:M *M*\ :sub:0 Up_theta      = |theta|\ :sub:up M_theta       = |theta|\ :sub:M M_phi         = |phi|\ :sub:M M0_sld        = $D_M M_0$ Up_theta      = $\theta_\text{up}$ M_theta       = $\theta_M$ M_phi         = $\phi_M$ Up_frac_i     = (spin up)/(spin up + spin down) neutrons *before* the sample Up_frac_f     = (spin up)/(spin up + spin down) neutrons *after* the sample
• ## src/sas/sasgui/perspectives/fitting/media/pd_help.rst

 r6aad2e8 form factor is normalized by the average particle volume such that *P(q) = scale* * \ / *V + bkg* .. math:: where F is the scattering amplitude and the \<\> denote an average over the size distribution. P(q) = \text{scale} \langle F^*F rangle V + \text{background} where $F$ is the scattering amplitude and $\langle\cdot\rangle$ denotes an average over the size distribution. Users should note that this computation is very intensive. Applying polydispersion .. image:: pd_image001.png where *xmean* is the mean of the distribution, *w* is the half-width, and *Norm* is a normalization factor which is determined during the numerical calculation. where $x_{mean}$ is the mean of the distribution, $w$ is the half-width, and $Norm$ is a normalization factor which is determined during the numerical calculation. Note that the standard deviation and the half width *w* are different! Note that the standard deviation and the half width $w$ are different! The standard deviation is .. image:: pd_image005.png where *xmean* is the mean of the distribution and *Norm* is a normalization factor where $x_{mean}$ is the mean of the distribution and $Norm$ is a normalization factor which is determined during the numerical calculation. .. image:: pd_image007.png where |mu|\ =ln(*xmed*), *xmed* is the median value of the distribution, and *Norm* is a normalization factor which will be determined during the numerical where $\mu=\ln(x_{med})$, $x_{med}$ is the median value of the distribution, and $Norm$ is a normalization factor which will be determined during the numerical calculation. size parameter in the *FitPage*, for example, radius = 60. The polydispersity is given by |sigma| The polydispersity is given by $\sigma$ .. image:: pd_image008.png .. image:: pd_image009.png The mean value is given by *xmean*\ =exp(|mu|\ +p\ :sup:2\ /2). The peak value is given by *xpeak*\ =exp(|mu|-p\ :sup:2\ ). The mean value is given by $x_{mean} =\exp(\mu + p^2 /2)$. The peak value is given by $x_{peak} =\exp(\mu-p^2)$. .. image:: pd_image010.jpg This distribution function spreads more, and the peak shifts to the left, as *p* This distribution function spreads more, and the peak shifts to the left, as $p$ increases, requiring higher values of Nsigmas and Npts. .. image:: pd_image011.png where *xmean* is the mean of the distribution and *Norm* is a normalization factor which is determined during the numerical calculation, and *z* is a measure of the where $x_{mean}$ is the mean of the distribution and $Norm$ is a normalization factor which is determined during the numerical calculation, and $z$ is a measure of the width of the distribution such that z = (1-p\ :sup:2\ ) / p\ :sup:2 .. math:: z = (1-p^2 ) / p^2 The polydispersity is This user-definable distribution should be given as as a simple ASCII text file where the array is defined by two columns of numbers: *x* and *f(x)*. The *f(x)* where the array is defined by two columns of numbers: $x$ and $f(x)$. The $f(x)$ will be normalized by SasView during the computation. SasView only uses these array values during the computation, therefore any mean value of the parameter represented by *x* present in the *FitPage* value of the parameter represented by $x$ present in the *FitPage* will be ignored. Many commercial Dynamic Light Scattering (DLS) instruments produce a size polydispersity parameter, sometimes even given the symbol *p*! This parameter is polydispersity parameter, sometimes even given the symbol $p$! This parameter is defined as the relative standard deviation coefficient of variation of the size distribution and is NOT the same as the polydispersity parameters in the Lognormal

• ## docs/sphinx-docs/build_sphinx.py

 r6aad2e8 copy_tree(html, SASVIEW_DOCS) print "=== Build Latex Docs from Rest Files ===" subprocess.call(["sphinx-build", #We are building latex doc on linux only if "linux" in platform: print "=== Build Latex Docs from Rest Files ===" subprocess.call(["sphinx-build", "-b", "latex", # Builder name. TODO: accept as arg to setup.py. "-d", os.path.join(SPHINX_BUILD, "doctrees"), os.path.join(SPHINX_BUILD, "latex")]) print "=== Copy Latex Docs to Build Directory ===" latex = os.path.join(SPHINX_BUILD, "latex") copy_tree(latex, SASVIEW_DOCS) print "=== Copy Latex Docs to Build Directory ===" latex = os.path.join(SPHINX_BUILD, "latex") copy_tree(latex, SASVIEW_DOCS) def rebuild():
Note: See TracChangeset for help on using the changeset viewer.