Actually, avoid dollars in code (entities escaped when writing the HTML).

diff --git a/posts/calibcant.mdwn_itex b/posts/calibcant.mdwn_itex
index aeb4c6c215ca5de580b88a62dabbcd9b383f4f14..05581d6b1261b7959421135d8f4c66ea2f16e7f4 100644 (file)
--- a/posts/calibcant.mdwn_itex
+++ b/posts/calibcant.mdwn_itex
@@ -8,9 +8,10 @@ The `README` is posted on the [PyPI page][pypi], and you might also be
 interested in the [[package dependency graph|calibcant.svg]] generated
 with Yu-Jie Lin's [PDepGraph.py][]:
 
-    $ IGNORED=matplotlib,scipy,numpy,pyyaml,h5py,python,eselect-python
-    $ python PDepGraph.py -o calibcant.dot -D "$IGNORED" calibcant
-    $ dot -T svg -o calibcant.svg calibcant.dot
+    # python PDepGraph.py -o calibcant.dot \
+        -D matplotlib,scipy,numpy,pyyaml,h5py,python,eselect-python \
+        calibcant
+    # dot -T svg -o calibcant.svg calibcant.dot
 
 Thermal calibration requires three separate measurements: photodiode
 sensitivity (via surface bumps), fluid temperature (estimated, or via
@@ -19,14 +20,14 @@ in far from the surface).  The calibcant package takes repeated
 measurements ([[!ltio statistics.png]]) of each of these parameters to
 allow estimation of statistical uncertainty:
 
-    $ calibcant-analyze.py calibcant/examples/calibration.h5
+    # calibcant-analyze.py calibcant/examples/calibration.h5
     ...
     ... variable (units)         : mean +/- std. dev. (relative error)
     ... cantilever k (N/m)       : 0.0629167 +/- 0.00439057 (0.0697838)
     ... photo sensitivity (V/m)  : 2.4535e+07 +/- 616119 (0.0251118)
     ... T (K)                    : 295.15 +/- 0 (0)
     ... vibration variance (V^2) : 3.89882e-05 +/- 1.88897e-06 (0.0484497)
-               ...
+    ...
 
 While this cannot account for systematic errors, calibration numbers
 are fairly meaninless without at least statistical error estimates.
@@ -53,9 +54,9 @@ well as white noise from the measurement equipment.
 
 \[
   \text{PSD}(x, \omega) =
-    \frac{2 k_BT \beta}
+    \frac{2 k_{B} T \beta}
          { \pi m \left[{(\omega_0^2-\omega^2)^2 + \beta^2\omega^2}\right] }
-    + N \;.
+    + W \;.
 \]
 
 where $\beta$ and $\omega_0$ come from the damped-forced harmonic
@@ -65,7 +66,7 @@ oscillator equation of motion
   \ddot{x} + \beta \dot{x} + \omega_0^2 x = \frac{F(t)}{m} \;,
 \]
 
-$m$ is the cantilever's effective mass, and $N$ is an optional
+the cantilever's effective mass is $m$, and $W$ is an optional
 white-noise offset.
 
 Here is an example of a one-second thermal vibration fit with the