Cleanup BibTex tags

docs/source/references.bib

@@ -1,7 +1,7 @@
 %comment{This file was created with betterbib v4.3.8.}
 
 
-@article{chen:2001,
+@article{chen2001,
  author = {Chen, Curtis W. and Zebker, Howard A.},
  title = {Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization},
  journal = {Journal of the Optical Society of America A},
@@ -17,7 +17,7 @@ @article{chen:2001
  source = {Crossref},
 }
 
-@inproceedings{kaiser:1974,
+@inproceedings{kaiser1974,
  author = {Kaiser, James F.},
  title = {Nonrecursive Digital Filter Design Using the I0-Sinh Window Function.},
  booktitle = {Proceedings of the 1974 IEEE International Symposium on Circuits and Systems},
@@ -27,7 +27,7 @@ @inproceedings{kaiser:1974
  month = apr,
 }
 
-@article{lee:1994,
+@article{lee1994,
  author = {Lee, Jong-Sen and Hoppel, K.W. and Mango, S.A. and Miller, A.R.},
  title = {Intensity and phase statistics of multilook polarimetric and interferometric {SAR} imagery},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
@@ -42,7 +42,7 @@ @article{lee:1994
  source = {Crossref},
 }
 
-@article{mcclellan:1973,
+@article{mcclellan1973,
  author = {McClellan, J. and Parks, T.},
  title = {A unified approach to the design of optimum {FIR} linear-phase digital filters},
  journal = {IEEE Transactions on Circuit Theory},
@@ -58,7 +58,7 @@ @article{mcclellan:1973
  source = {Crossref},
 }
 
-@article{miller:1986,
+@article{miller1986,
  author = {Miller, Gavin S P},
  title = {The definition and rendering of terrain maps},
  journal = {ACM SIGGRAPH Computer Graphics},
@@ -75,7 +75,7 @@ @article{miller:1986
  source = {Crossref},
 }
 
-@article{rodriguez:1992,
+@article{rodriguez1992,
  author = {Rodriguez, E. and Martin, J.M.},
  title = {Theory and design of interferometric synthetic aperture radars},
  journal = {IEE Proceedings F Radar and Signal Processing},

src/tophu/filter.py

@@ -13,7 +13,7 @@ def equiripple_filter_order_kaiser(ptol: float, stol: float, width: float) -> in
 
     Predicts the order of a finite impulse response (FIR) digital filter obtained from
     the optimal equiripple approximation method using Kaiser's formula\
-    :footcite:p:`kaiser:1974`.
+    :footcite:p:`kaiser1974`.
 
     Evaluates
 
@@ -66,7 +66,7 @@ def bandpass_equiripple_filter(
 
     Form a linear-phase finite impulse response (FIR) discrete-time digital filter wth
     desired passband, stopband, and attenuation characteristics using the
-    Parks-McClellan algorithm\ :footcite:p:`mcclellan:1973`. The algorithm produces a
+    Parks-McClellan algorithm\ :footcite:p:`mcclellan1973`. The algorithm produces a
     filter that is optimal in the sense that it minimizes the maximum weighted deviation
     from the ideal frequency response in the passband and stopband.
 

src/tophu/multiscale.py

@@ -31,7 +31,7 @@ def lowpass_filter_and_multilook(
     Apply an anti-aliasing pre-filter, then multilook.
 
     The input array is filtered by applying a low-pass filter constructed using the
-    optimal equiripple method\ :footcite:p:`mcclellan:1973` and then multilooked to
+    optimal equiripple method\ :footcite:p:`mcclellan1973` and then multilooked to
     produce the downsampled output. However, if the number of looks along any axis is 1,
     no filtering will be applied along that axis of the array.
 

src/tophu/unwrap.py

@@ -63,7 +63,7 @@ class SnaphuUnwrap(UnwrapCallback):
     r"""
     Callback functor for unwrapping using SNAPHU.
 
-    Performs unwrapping using the SNAPHU algorithm\ :footcite:p:`chen:2001`.
+    Performs unwrapping using the SNAPHU algorithm\ :footcite:p:`chen2001`.
     """
 
     cost: str

test/simulate.py

@@ -22,9 +22,9 @@ def simulate_phase_noise(
 
     The resulting samples are zero-mean Gaussian distributed, with variance equal to the
     Cramer-Rao bound of the Maximum Likelihood Estimator for the interferometric
-    phase\ :footcite:p:`rodriguez:1992`. This simple approximation is most accurate for
+    phase\ :footcite:p:`rodriguez1992`. This simple approximation is most accurate for
     high coherence and large number of looks. The true phase difference distribution is
-    more complicated\ :footcite:p:`lee:1994`.
+    more complicated\ :footcite:p:`lee1994`.
 
     Parameters
     ----------
@@ -65,7 +65,7 @@ def simulate_terrain(
     r"""Simulate topography using the Diamond-Square algorithm.
 
     Generate a 2-D fractal height map using the Diamond-Square algorithm\
-    :footcite:p:`miller:1986`.
+    :footcite:p:`miller1986`.
 
     Parameters
     ----------