diff --git a/docs/api/comps.rst b/docs/api/comps.rst
new file mode 100644
index 0000000..18938fe
--- /dev/null
+++ b/docs/api/comps.rst
@@ -0,0 +1,7 @@
+.. _computed-msids:
+
+Computed MSIDs
+==============
+
+.. automodule:: cheta.derived.comps
+    :members:
diff --git a/docs/api/derived.rst b/docs/api/derived.rst
new file mode 100644
index 0000000..7bcd035
--- /dev/null
+++ b/docs/api/derived.rst
@@ -0,0 +1,47 @@
+.. _derived-msids:
+
+Derived MSIDs
+==============
+
+Base classes
+------------
+
+.. automodule:: cheta.derived.base
+    :members:
+    :undoc-members:
+
+ACIS power
+----------
+
+.. automodule:: cheta.derived.acispow
+   :members:
+
+EPS
+---
+
+.. automodule:: cheta.derived.eps
+    :members:
+
+MUPS valve
+----------
+
+.. automodule:: cheta.derived.mups_valve
+    :members:
+
+Orbit
+-----
+
+.. automodule:: cheta.derived.orbit
+    :members:
+
+PCAD
+----
+
+.. automodule:: cheta.derived.pcad
+    :members:
+
+Thermal
+-------
+
+.. automodule:: cheta.derived.thermal
+    :members:
diff --git a/docs/api/index.rst b/docs/api/index.rst
new file mode 100644
index 0000000..368caca
--- /dev/null
+++ b/docs/api/index.rst
@@ -0,0 +1,11 @@
+API docs
+========
+
+.. toctree::
+   :maxdepth: 1
+
+   fetch
+   plot
+   utils
+   comps
+   derived
diff --git a/docs/fetch_tutorial.rst b/docs/fetch_tutorial.rst
index 706b7d8..6825d75 100644
--- a/docs/fetch_tutorial.rst
+++ b/docs/fetch_tutorial.rst
@@ -26,8 +26,8 @@ Fetching and plotting full time-resolution data for a single MSID is then quite
 easy::
 
   tephin = fetch.MSID('tephin', '2009:001', '2009:007') # (MSID, start, stop)
-  clf()
-  plot(tephin.times, tephin.vals)
+  plt.clf()
+  plt.plot(tephin.times, tephin.vals)
 
 .. image:: fetchplots/first.png
 
@@ -128,7 +128,7 @@ converting between formats but for making plots we use the
 function of the ``ska_matplotlib`` module::
 
   from ska_matplotlib import plot_cxctime
-  clf()
+  plt.clf()
   plot_cxctime(tephin.times, tephin.vals)
 
 An even simpler way to make the same plot is with the
@@ -545,11 +545,11 @@ These data are accessed by specifying
   tephin_5min = fetch.MSID('tephin', '2009:001', stat='5min')
   tephin_daily = fetch.MSID('tephin', '2000:001', stat='daily')
   figure(1)
-  clf()
+  plt.clf()
   plot_cxctime(tephin_daily.times, tephin_daily.mins, '-b')
   plot_cxctime(tephin_daily.times, tephin_daily.maxes, '-r')
   figure(2)
-  clf()
+  plt.clf()
   plot_cxctime(tephin_5min.times, tephin_5min.means, '-b')
 
 .. image:: fetchplots/tephin_daily.png
@@ -608,7 +608,7 @@ The returned ``rates`` object is like a python dictionary (hash) object with
 a couple extra methods.  Indexing the object by the MSID name gives the
 usual ``fetch.MSID`` object that we've been using up to this point::
 
-  clf()
+  plt.clf()
   plot_cxctime(rates['aorate1'].times, rates['aorate1'].vals)
 
 You might wonder what's special about an ``MSIDset``, after all the actual code
@@ -681,8 +681,8 @@ new centroid value every 2.05 sec.
   gyr_dct1 = msids['aogyrct1'].vals[1:] - msids['aogyrct1'].vals[:-1]
   gyr_dt = msids['aogyrct1'].times[1:] - msids['aogyrct1'].times[:-1]
   gyr_rate = gyr_dct1 / gyr_dt * 0.02
-  clf()
-  plot(aca_rate, gyr_rate, '.')
+  plt.clf()
+  plt.plot(aca_rate, gyr_rate, '.')
 
 .. image:: fetchplots/aca_gyro_rates.png
 
@@ -1299,7 +1299,7 @@ rates to those derived on the ground using raw gyro data.
 
   # Plot the OBC rates
   figure(1, figsize=(8,6))
-  clf()
+  plt.clf()
   for frame, msid, label in ((1, 'aorate1', 'roll'),
                              (2, 'aorate2', 'pitch'),
                              (3, 'aorate3', 'yaw')):
@@ -1315,7 +1315,7 @@ rates to those derived on the ground using raw gyro data.
 
   # Plot the S/C rates from raw gyro data
   figure(2, figsize=(8,6))
-  clf()
+  plt.clf()
   for axis, label in ((0, 'roll'),
                       (1, 'pitch'),
                       (2, 'yaw')):
diff --git a/docs/pseudo_msids.rst b/docs/pseudo_msids.rst
index b3e8a82..bf94c02 100644
--- a/docs/pseudo_msids.rst
+++ b/docs/pseudo_msids.rst
@@ -654,35 +654,6 @@ sequence with step size ``time_step``.
                    data['1dp28bvo'].vals * data['1dpicbcu'].vals)
           return power
 
-
-ACIS Power
-^^^^^^^^^^^
-.. automodule:: cheta.derived.acispow
-   :members:
-
-EPS
-^^^^^^^^^^^^^^^^^
-.. automodule:: cheta.derived.eps
-   :members:
-   :undoc-members:
-
-Orbital elements
-^^^^^^^^^^^^^^^^^
-.. automodule:: cheta.derived.orbit
-   :members:
-   :undoc-members:
-
-PCAD
-^^^^^
-.. automodule:: cheta.derived.pcad
-   :members:
-
-Thermal
-^^^^^^^^^
-.. automodule:: cheta.derived.thermal
-   :members:
-   :undoc-members:
-
 Computed MSIDs
 --------------
 
@@ -811,9 +782,3 @@ following structure::
 
 The specified units must all be convertable using functions defined in the
 ``converters`` dict in the ``cheta.units`` module.
-
-Built-in computed MSIDs and API
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-  .. automodule:: cheta.derived.comps
-    :members: