Small fixes, guide additions, tweaks

doc/Guide.md

@@ -82,6 +82,9 @@ The authors of this program feel that Whole is the best style for most users, bu
   
 ## Features
 
+### Gain Switch
+The acceleration curve styles below (see "Acceleration Styles") each describe a certain shape mathematically. The gain switch determines whether that shape is applied in the sensitivity graph or the gain graph. For styles Linear, Classic, and Power, this setting does not change the possible shapes of the velocity curve - that is, for any particular settings with the gain switch set to Sensitivity, there is a different set of settings that will replicate the exact same velocity curve (output for a given hand motion) with the switch set to Gain. For styles Natural, Jump, and Motivity, this is not true, and the gain switch allows new velocity curves for each style. 
+
 ### Offsets
 An offset, sometimes called a threshold, is a speed in counts before acceleration "kicks in". The legacy way of applying an offset is having a multiplier of 1 below and at the offset, and applying the sensitivity of (speed-offset) above. This legacy "sensitivity offset" is still available but causes a large discontuinity in gain at the point of offset, leading to non-smooth feeling at offset cross. The new default "gain offset" does a little extra math to simply shift the gain graph by the offset amount without any discontinuity. This feels smoother and has almost no effect on sensitivity. The theory behind "gain offsets" is developed in [this document](https://docs.google.com/document/d/1P6LygpeEazyHfjVmaEygCsyBjwwW2A-eMBl81ZfxXZk).
 
@@ -118,16 +121,20 @@ This is the style found in CS:GO and Source Engine games (m_customaccel 3). The
 ![PowerExample](images/power_example.png)
 
 ### Natural & NaturalGain
-Natural is a style found in the game Diabotical. It features a concave curve which starts at 1 and approaches some maximum sensitivity. This style is unique and useful but causes an ugly dip in the gain graph. For this reason we have created the NaturalGain style, which recreates the Natural style shape in the gain graph without any dips. We recommend users use the NaturalGain style instead of the Natural style; on switch some small tweaks may be needed since for any particular settings the NaturalGain is slightly slower to ramp up than the Natural style. NaturalGain is another excellent choice for new users.
+Natural features a concave curve which starts at 1 and approaches some maximum sensitivity. The sensitivity version of this curve can be found in the game Diabotical. This style is unique and useful but causes an ugly dip in the gain graph. The gain version of this curve recreates the Natural style shape in the gain graph without any dips and therefore we recommend this version. Natural is an excellent choice for new users due to only needing a two intuitive parameters which achieve what many users are looking for.
 ![NaturalExample](images/natural_example.png)
 ![NaturalGainExample](images/natural_gain_example.png)
 
+### Jump
+ This style applies one sensitivity below a certain threshold, and another above it. It can be useful for those who want one constant sensitivity and gain for slow hand motions and a different constant sensitivity or gain for fast hand motions. Users can set a "smooth" parameter which dictates whether the jump happens instaneously (at smooth 0) or with a slight tailing in and out (smooth 1) leading to a small sigmoid shape (s-shape). (Note that this "smooth" parameter has nothing to do with averaging over mouse counts like in sensor smoothing on mice or mouse smoothing in games.)
+
 ### Motivity
-This curve looks like an "S" with the top half bigger than the bottom. Mathematically it's a "Sigmoid function on a log-log plot". A user can set the "midpoint" of the S, the "acceleration" (i.e. slantedness) of the S, and the "motivity". "Motivity" sets min and max sensitivity, where the maximum is just "motivity", and the minimum is "1/motivity." (Gain is 1 at the midpoint.) This curve is calculated and stored in a lookup table before applying acceleration, which makes the gain graph look a little funny.  This is one author's favorite curve, and an excellent choice for power users and new users who don't mind playing with the settings a little.
+This curve looks like an "S" with the top half bigger than the bottom. Mathematically it's a "Sigmoid function on a log-log plot". A user can set the "midpoint" of the S, the "acceleration" (i.e. slantedness) of the S, and the "motivity". "Motivity" sets min and max sensitivity, where the maximum is just "motivity", and the minimum is "1/motivity." (Sensitivity or gain is 1 at the midpoint.) The gain version of this curve is calculated and stored in a lookup table before applying acceleration, which makes the gain graph look a little funny.  This is an excellent choice for power users and new users who don't mind playing with the settings a little.
 ![MotivityExample](images/motivity_example.png)
 
 ### Look Up Table
-This curve style is a blank canvas on which to create a curve. It allows the user to define the points which will make up the curve. For this reason, this mode is only for experts who know exactly what they want. Points can be supplied in the GUI according to format x1,y1;x2,y2;...xn.yn or in the settings.json in json format.
+This curve style is a blank canvas on which to create a curve. It allows the user to define the points which will make up the curve. For this reason, this mode is only for experts who know exactly what they want. Points can be supplied in the GUI according to format x1,y1;x2,y2;...xn.yn or in the settings.json in json format. The default Windows mouse acceleration settings (Enhanced Pointer Precision) can be very closely emulated with this style, using points: "".
+![LUTExample](images/lut_example.png)
 
 ## Further Help
 Further help and frequently asked questions can be found in the [FAQ](https://github.com/a1xd/rawaccel/blob/master/doc/FAQ.md).