Index: doc/guide/pd/polydispersity.rst
===================================================================
--- doc/guide/pd/polydispersity.rst	(revision d089a00eb2e0e6bbb032f5e258e960009a322466)
+++ doc/guide/pd/polydispersity.rst	(revision a5cb9bcbc504127c414602837e600378ebda6add)
@@ -11,11 +11,11 @@
 --------------------------------------------
 
-For some models we can calculate the average intensity for a population of 
-particles that possess size and/or orientational (ie, angular) distributions. 
-In SasView we call the former *polydispersity* but use the parameter *PD* to 
-parameterise both. In other words, the meaning of *PD* in a model depends on 
+For some models we can calculate the average intensity for a population of
+particles that possess size and/or orientational (ie, angular) distributions.
+In SasView we call the former *polydispersity* but use the parameter *PD* to
+parameterise both. In other words, the meaning of *PD* in a model depends on
 the actual parameter it is being applied too.
 
-The resultant intensity is then normalized by the average particle volume such 
+The resultant intensity is then normalized by the average particle volume such
 that
 
@@ -24,15 +24,14 @@
   P(q) = \text{scale} \langle F^* F \rangle / V + \text{background}
 
-where $F$ is the scattering amplitude and $\langle\cdot\rangle$ denotes an 
+where $F$ is the scattering amplitude and $\langle\cdot\rangle$ denotes an
 average over the distribution $f(x; \bar x, \sigma)$, giving
 
 .. math::
 
-  P(q) = \frac{\text{scale}}{V} \int_\mathbb{R} 
+  P(q) = \frac{\text{scale}}{V} \int_\mathbb{R}
   f(x; \bar x, \sigma) F^2(q, x)\, dx + \text{background}
 
 Each distribution is characterized by a center value $\bar x$ or
 $x_\text{med}$, a width parameter $\sigma$ (note this is *not necessarily*
-<<<<<<< HEAD
 the standard deviation, so read the description carefully), the number of
 sigmas $N_\sigma$ to include from the tails of the distribution, and the
@@ -47,15 +46,4 @@
 However, the distribution width applied to *orientation* (ie, angle-describing)
 parameters is just $\sigma = \mathrm{PD}$.
-=======
-the standard deviation, so read the description of the distribution carefully), 
-the number of sigmas $N_\sigma$ to include from the tails of the distribution, 
-and the number of points used to compute the average. The center of the 
-distribution is set by the value of the model parameter.
-
-The distribution width applied to *volume* (ie, shape-describing) parameters 
-is relative to the center value such that $\sigma = \mathrm{PD} \cdot \bar x$. 
-However, the distribution width applied to *orientation* parameters is just 
-$\sigma = \mathrm{PD}$.
->>>>>>> master
 
 $N_\sigma$ determines how far into the tails to evaluate the distribution,
@@ -67,7 +55,7 @@
 
 Users should note that the averaging computation is very intensive. Applying
-polydispersion and/or orientational distributions to multiple parameters at 
-the same time, or increasing the number of points in the distribution, will 
-require patience! However, the calculations are generally more robust with 
+polydispersion and/or orientational distributions to multiple parameters at
+the same time, or increasing the number of points in the distribution, will
+require patience! However, the calculations are generally more robust with
 more data points or more angles.
 
@@ -90,10 +78,10 @@
 **This may not be suitable. See Suggested Applications below.**
 
-.. note:: In 2009 IUPAC decided to introduce the new term 'dispersity' to replace 
-           the term 'polydispersity' (see `Pure Appl. Chem., (2009), 81(2), 
-           351-353 <http://media.iupac.org/publications/pac/2009/pdf/8102x0351.pdf>`_ 
-           in order to make the terminology describing distributions of chemical 
-           properties unambiguous. However, these terms are unrelated to the 
-           proportional size distributions and orientational distributions used in 
+.. note:: In 2009 IUPAC decided to introduce the new term 'dispersity' to replace
+           the term 'polydispersity' (see `Pure Appl. Chem., (2009), 81(2),
+           351-353 <http://media.iupac.org/publications/pac/2009/pdf/8102x0351.pdf>`_
+           in order to make the terminology describing distributions of chemical
+           properties unambiguous. However, these terms are unrelated to the
+           proportional size distributions and orientational distributions used in
            SasView models.
 
@@ -113,5 +101,5 @@
 The array distribution provides a very simple means of implementing a user-
 defined distribution, but without any fittable parameters. Greater flexibility
-is conferred by the user-defined distribution. 
+is conferred by the user-defined distribution.
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
@@ -442,11 +430,11 @@
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Several measures of polydispersity abound in Dynamic Light Scattering (DLS) and 
-it should not be assumed that any of the following can be simply equated with 
+Several measures of polydispersity abound in Dynamic Light Scattering (DLS) and
+it should not be assumed that any of the following can be simply equated with
 the polydispersity *PD* parameter used in SasView.
 
-The dimensionless **Polydispersity Index (PI)** is a measure of the width of the 
-distribution of autocorrelation function decay rates (*not* the distribution of 
-particle sizes itself, though the two are inversely related) and is defined by 
+The dimensionless **Polydispersity Index (PI)** is a measure of the width of the
+distribution of autocorrelation function decay rates (*not* the distribution of
+particle sizes itself, though the two are inversely related) and is defined by
 ISO 22412:2017 as
 
@@ -455,5 +443,5 @@
     PI = \mu_{2} / \bar \Gamma^2
 
-where $\mu_\text{2}$ is the second cumulant, and $\bar \Gamma^2$ is the 
+where $\mu_\text{2}$ is the second cumulant, and $\bar \Gamma^2$ is the
 intensity-weighted average value, of the distribution of decay rates.
 
@@ -464,5 +452,5 @@
     PI = \sigma^2 / 2\bar \Gamma^2
 
-where $\sigma$ is the standard deviation, allowing a **Relative Polydispersity (RP)** 
+where $\sigma$ is the standard deviation, allowing a **Relative Polydispersity (RP)**
 to be defined as
 
@@ -471,9 +459,9 @@
     RP = \sigma / \bar \Gamma = \sqrt{2 \cdot PI}
 
-PI values smaller than 0.05 indicate a highly monodisperse system. Values 
+PI values smaller than 0.05 indicate a highly monodisperse system. Values
 greater than 0.7 indicate significant polydispersity.
 
-The **size polydispersity P-parameter** is defined as the relative standard 
-deviation coefficient of variation  
+The **size polydispersity P-parameter** is defined as the relative standard
+deviation coefficient of variation
 
 .. math::
@@ -482,5 +470,5 @@
 
 where $\nu$ is the variance of the distribution and $\bar R$ is the mean
-value of $R$. Here, the product $P \bar R$ is *equal* to the standard 
+value of $R$. Here, the product $P \bar R$ is *equal* to the standard
 deviation of the Lognormal distribution.
 
