decimation option for remaining DFT functions (NanoComp#1720)

* add decimation factor to add_dft_flux

* some fixes

* fixes

* fixes, unit tests, docs

* update markdown pages for user manual

* increase tolerance of failing unit test in test_bend_flux.py

* fix add_dft_near2far function header

doc/docs/Python_User_Interface.md

@@ -534,10 +534,29 @@ def mean_time_spent_on(self, time_sink):
 <div class="method_docstring" markdown="1">
 
 Return the mean time spent by all processes for a type of work `time_sink` which
-can be one of ten integer values `0`-`9`: (`0`) connecting chunks, (`1`) time stepping,
-(`2`) copying boundaries, (`3`) MPI all-to-all communication/synchronization,
-(`4`) MPI one-to-one communication, (`5`) field output, (`6`) Fourier transforming,
-(`7`) MPB mode solver, (`8`) near-to-far field transformation, and (`9`) other.
+can be one of the following integer constants:
+* meep.Stepping ("time stepping")
+* meep.Connecting ("connecting chunks")
+* meep.Boundaries ("copying boundaries")
+* meep.MpiAllTime ("all-all communication")
+* meep.MpiOneTime ("1-1 communication")
+* meep.FieldOutput ("outputting fields")
+* meep.FourierTransforming ("Fourier transforming")
+* meep.MPBTime ("MPB mode solver")
+* meep.GetFarfieldsTime ("far-field transform")
+* meep.FieldUpdateB ("updating B field")
+* meep.FieldUpdateH ("updating H field")
+* meep.FieldUpdateD ("updating D field")
+* meep.FieldUpdateE ("updating E field")
+* meep.BoundarySteppingB ("boundary stepping B")
+* meep.BoundarySteppingWH ("boundary stepping WH")
+* meep.BoundarySteppingPH ("boundary stepping PH")
+* meep.BoundarySteppingH ("boundary stepping H")
+* meep.BoundarySteppingD ("boundary stepping D")
+* meep.BoundarySteppingWE ("boundary stepping WE")
+* meep.BoundarySteppingPE ("boundary stepping PE")
+* meep.BoundarySteppingE ("boundary stepping E")
+* meep.Other ("everything else")
 
 </div>
 
@@ -726,16 +745,16 @@ fields for `nfreq` equally spaced frequencies covering the frequency range
 `fcen-df/2` to `fcen+df/2` or an array/list `freq` for arbitrarily spaced
 frequencies over the `Volume` specified by `where` (default to the entire cell).
 The volume can also be specified via the `center` and `size` arguments. The
-default routine interpolates the Fourier transformed fields at the center of each
-voxel within the specified volume. Alternatively, the exact Fourier transformed
+default routine interpolates the Fourier-transformed fields at the center of each
+voxel within the specified volume. Alternatively, the exact Fourier-transformed
 fields evaluated at each corresponding Yee grid point is available by setting
-`yee_grid` to `True`. To reduce the memory bandwidth burden of
+`yee_grid` to `True`. To reduce the memory-bandwidth burden of
 accumulating DFT fields, an integer `decimation_factor` >= 1 can be
 specified. DFT field values are updated every `decimation_factor`
-timesteps. Use this experimental feature with care, as the decimated
-timeseries may be corruped by aliasing of high frequencies. The choice
-of decimation factor should take the properties of all sources in the
-simulation and the frequency range of the DFT field monitor into account.
+timesteps. Use this feature with care, as the decimated timeseries may be
+corrupted by [aliasing](https://en.wikipedia.org/wiki/Aliasing) of high frequencies.
+The choice of decimation factor should take into account the properties of all sources
+in the simulation as well as the frequency range of the DFT field monitor.
 
 </div>
 
@@ -1009,7 +1028,9 @@ def reset_meep(self):
 <div class="method_docstring" markdown="1">
 
 Reset all of Meep's parameters, deleting the fields, structures, etcetera, from
-memory as if you had not run any computations.
+memory as if you had not run any computations. If the `num_chunks` or `chunk_layout`
+attributes have been modified internally, they are reset to their original
+values passed in at instantiation.
 
 </div>
 
@@ -1094,8 +1115,8 @@ Given a bunch of [`FluxRegion`](#fluxregion) objects, you can tell Meep to accum
 <div class="class_members" markdown="1">
 
 ```python
-def add_flux(self, *args):
-def add_flux(fcen, df, nfreq, freq, FluxRegions...):
+def add_flux(self, *args, **kwargs):
+def add_flux(fcen, df, nfreq, freq, FluxRegions, decimation_factor=1):
 ```
 
 <div class="method_docstring" markdown="1">
@@ -1106,7 +1127,13 @@ they have not yet been initialized), telling Meep to accumulate the appropriate
 field Fourier transforms for `nfreq` equally spaced frequencies covering the
 frequency range `fcen-df/2` to `fcen+df/2` or an array/list `freq` for arbitrarily
 spaced frequencies. Return a *flux object*, which you can pass to the functions
-below to get the flux spectrum, etcetera.
+below to get the flux spectrum, etcetera. To reduce the memory-bandwidth burden of
+accumulating DFT fields, an integer `decimation_factor` >= 1 can be
+specified. DFT field values are updated every `decimation_factor`
+timesteps. Use this feature with care, as the decimated timeseries may be
+corrupted by [aliasing](https://en.wikipedia.org/wiki/Aliasing) of high frequencies.
+The choice of decimation factor should take into account the properties of all sources
+in the simulation as well as the frequency range of the DFT field monitor.
 
 </div>
 
@@ -1482,8 +1509,8 @@ The usage is similar to the flux spectra: you define a set of [`EnergyRegion`](#
 <div class="class_members" markdown="1">
 
 ```python
-def add_energy(self, *args):
-def add_energy(fcen, df, nfreq, freq, EnergyRegions...):
+def add_energy(self, *args, **kwargs):
+def add_energy(fcen, df, nfreq, freq, EnergyRegions, decimation_factor=1):
 ```
 
 <div class="method_docstring" markdown="1">
@@ -1494,7 +1521,13 @@ if they have not yet been initialized), telling Meep to accumulate the appropria
 field Fourier transforms for `nfreq` equally spaced frequencies covering the
 frequency range `fcen-df/2` to `fcen+df/2` or an array/list `freq` for arbitrarily
 spaced frequencies. Return an *energy object*, which you can pass to the functions
-below to get the energy spectrum, etcetera.
+below to get the energy spectrum, etcetera. To reduce the memory-bandwidth burden of
+accumulating DFT fields, an integer `decimation_factor` >= 1 can be
+specified. DFT field values are updated every `decimation_factor`
+timesteps. Use this feature with care, as the decimated timeseries may be
+corrupted by [aliasing](https://en.wikipedia.org/wiki/Aliasing) of high frequencies.
+The choice of decimation factor should take into account the properties of all sources
+in the simulation as well as the frequency range of the DFT field monitor.
 
 </div>
 
@@ -1708,8 +1741,8 @@ The usage is similar to the [flux spectra](Python_Tutorials/Basics.md#transmitta
 <div class="class_members" markdown="1">
 
 ```python
-def add_force(self, *args):
-def add_force(fcen, df, nfreq, freq, ForceRegions...):
+def add_force(self, *args, **kwargs):
+def add_force(fcen, df, nfreq, freq, ForceRegions, decimation_factor=1):
 ```
 
 <div class="method_docstring" markdown="1">
@@ -1720,7 +1753,13 @@ if they have not yet been initialized), telling Meep to accumulate the appropria
 field Fourier transforms for `nfreq` equally spaced frequencies covering the
 frequency range `fcen-df/2` to `fcen+df/2` or an array/list `freq` for arbitrarily
 spaced frequencies. Return a `force`object, which you can pass to the functions
-below to get the force spectrum, etcetera.
+below to get the force spectrum, etcetera. To reduce the memory-bandwidth burden of
+accumulating DFT fields, an integer `decimation_factor` >= 1 can be
+specified. DFT field values are updated every `decimation_factor`
+timesteps. Use this feature with care, as the decimated timeseries may be
+corrupted by [aliasing](https://en.wikipedia.org/wiki/Aliasing) of high frequencies.
+The choice of decimation factor should take into account the properties of all sources
+in the simulation as well as the frequency range of the DFT field monitor.
 
 </div>
 
@@ -1988,7 +2027,7 @@ There are three steps to using the near-to-far-field feature: first, define the
 
 ```python
 def add_near2far(self, *args, **kwargs):
-def add_near2far(fcen, df, nfreq, freq, Near2FarRegions..., nperiods=1):
+def add_near2far(fcen, df, nfreq, freq, Near2FarRegions, nperiods=1, decimation_factor=1):
 ```
 
 <div class="method_docstring" markdown="1">
@@ -1999,7 +2038,13 @@ fields if they have not yet been initialized), telling Meep to accumulate the
 appropriate field Fourier transforms for `nfreq` equally spaced frequencies
 covering the frequency range `fcen-df/2` to `fcen+df/2` or an array/list `freq`
 for arbitrarily spaced frequencies. Return a `near2far` object, which you can pass
-to the functions below to get the far fields.
+to the functions below to get the far fields. To reduce the memory-bandwidth burden of
+accumulating DFT fields, an integer `decimation_factor` >= 1 can be
+specified. DFT field values are updated every `decimation_factor`
+timesteps. Use this feature with care, as the decimated timeseries may be
+corrupted by [aliasing](https://en.wikipedia.org/wiki/Aliasing) of high frequencies.
+The choice of decimation factor should take into account the properties of all sources
+in the simulation as well as the frequency range of the DFT field monitor.
 
 </div>
 
@@ -7366,6 +7411,22 @@ of processes.
 
 </div>
 
+<a id="BinaryPartition.print"></a>
+
+<div class="class_members" markdown="1">
+
+```python
+def print(self):
+```
+
+<div class="method_docstring" markdown="1">
+
+Pretty-prints the tree structure of the BinaryPartition object.
+
+</div>
+
+</div>
+
 Miscellaneous Functions Reference
 ---------------------------------