 gmisclib.HList: This reads HTK feature vectors via the HList program.
 gmisclib.HTK_HMM_io: This reads in HMM files produced by HTK.
 gmisclib.HTK_MLF_io: This reads MLF (Master Label Files) for/from the HTK speech
recognition toolkit.
 gmisclib.MFCCFile
 gmisclib.MLF_file
 gmisclib.Num: This is a compatibility module, allowing python to work with either
scipy, Numeric, or numarray.
 gmisclib.Numeric_gpk
 gmisclib.accent_spec: This module provides a way of safely specifing accent positions in
running text.
 gmisclib.array_window: Defines array_window class.
 gmisclib.avio: Module to parse and create lines in "a=v;" format.
 gmisclib.bark_scale
 gmisclib.beamsearch
 gmisclib.blue_data_attributes: This chooses samples such that the specified attributes are broadly
distributed.
 gmisclib.blue_data_selector: This takes anticorrelated samples from a sequence of data.
 gmisclib.cache
 gmisclib.chunkio: These are I/O routines to allow you to write stuff like arrays and
dictionaries (and arrays of dictionaries) to a humanreadable file.
 gmisclib.convex_hull2d: convexhull.py
 gmisclib.dict_vector: Vectors of numbers, but indexed as a dictionary.
 gmisclib.dictops: Operations on dictionaries.
 gmisclib.die
 gmisclib.die2
 gmisclib.do_exec: Execute a *nix command and capture the output.
 gmisclib.ds9_region
 gmisclib.dtw4
 gmisclib.dyn_prog: Viterbi search
 gmisclib.edit_distance: Levenshtein (edit) distance between two strings of symbols.
 gmisclib.entropy
 gmisclib.erb_scale: ERB Perceptual frequency scale.
 gmisclib.evolution
 gmisclib.fake_file: A class that implements a simple file in memory.
 gmisclib.fiat_merge
 gmisclib.fiatio: Fiatio reads and writes an extension of the FIAT file format
originally defined by David Wittman (UC Davis).
 gmisclib.find_home: This lets you find files with just a path name relative to where
the program's executable code script sits.
 gmisclib.find_ngram: This module lets you search through label files to find particular
ngrams.
 gmisclib.findleak
 gmisclib.ftest
 gmisclib.fuzzygraph
 gmisclib.g2_select
 gmisclib.g_closure: This module defines closures.
 gmisclib.g_datetime
 gmisclib.g_ds9: Handles interactions with ds9 (http://heawww.harvard.edu/RD/ds9/).
 gmisclib.g_encode: This module allows strings to be encoded into a reduced subset.
 gmisclib.g_entropy: This returns the entropy of a probability distribution that
produced a given sample.
 gmisclib.g_exec: Run a Linux command and capture the result.
 gmisclib.g_implements: This module tells you if an object's signature matches a class.
 gmisclib.g_keyed_accum
 gmisclib.g_lin_fit: Generic linear best fits.
 gmisclib.g_localfit: Fit a linear transform to a bunch of tt input/output vectors.
 gmisclib.g_pipe: A multithreaded version of os.popen2().
 gmisclib.g_pipe_old: A multithreaded version of os.popen2().
 gmisclib.g_place_label
 gmisclib.g_pylab: This class works in concert with bin/pylab_server.py to allow you
to display simple pylab/matplotlib graphics on another machine.
 gmisclib.g_selector
 gmisclib.g_ucode: Functions to make unicode handling easier for Python 2.X.
 gmisclib.gpk_getopt
 gmisclib.gpk_hdr
 gmisclib.gpk_lapack
 gmisclib.gpk_lsq
 gmisclib.gpk_rlsq
 gmisclib.gpk_writer
 gmisclib.gpkmisc
 gmisclib.hilbert_xform
 gmisclib.kl_dist: Suppose there is a random variable with true distribution p.
 gmisclib.load_mod: This module has functions that help you dynamically import modules.
 gmisclib.lreg_fill
 gmisclib.makemake: This module is designed to build makefiles.
 gmisclib.matrix_arrange: Take a covariancelike matrix, and reorder it to be close to a
diagonal matrix.
 gmisclib.matrix_arrange_entropy: This rotates a matrix by multiplying with a unitary matrix so that
the resulting elements are either nearly zero or relatively large.
 gmisclib.matrix_rearrange_labels: This module helps you plot confusion matrices or similar images
where the axis labels do not have a natural order.
 gmisclib.mcmc: Bootstrap MarkovChain MonteCarlo algorithm.
 gmisclib.mcmcS2: MarkovChain MonteCarlo algorithms.
 gmisclib.mcmc_big: An extension of mcmc that includes new stepping algorithms.
 gmisclib.mcmc_cooperate
 gmisclib.mcmc_helper: This is a helper module to make use of mcmc.py and mcmc_big.py.
 gmisclib.mcmc_idxr
 gmisclib.mcmc_indexclass: This module provides several classes to manage the parameters of an
algorithm, particularly so that you can run the mcmc.py optimizer
on it.
 gmisclib.mcmc_logger
 gmisclib.mcmc_logtools
 gmisclib.mcmc_m4p: This is a helper module to make use of mcmc.py and mcmc_big.py.
 gmisclib.mcmc_mpi: This is a helper module to make use of mcmc.py and mcmc_big.py.
 gmisclib.mcmc_newlogger
 gmisclib.mcmc_pypar: This is a helper module to make use of mcmc.py and mcmc_big.py.
 gmisclib.mcmc_restart
 gmisclib.mcmc_socket: This is a helper module to make use of mcmc.py and mcmc_big.py.
 gmisclib.multivariance_classes: Support module for multivariance.py
 gmisclib.multivariance_mm: This a helper module for multivariance.py
 gmisclib.multivariance_q: This a helper module for multivariance.py
 gmisclib.multivariate_normal
 gmisclib.named_block_file: Read and write files in the form [label] text text text [label2]
text text ...
 gmisclib.nbest: Beam search through a graph.
 gmisclib.nice_hash
 gmisclib.nicknames
 gmisclib.nmf: V=WH, where W and H are nonnegative.
 gmisclib.opt: This module is a LevenbergMarquardt optimizer with stemsize
control for numeric differentiation.
 gmisclib.ortho_poly
 gmisclib.parse_tree_number
 gmisclib.permute: Find different permutations of an array.
 gmisclib.pylab_oneaxis: You can control the axis tick and grid properties
 gmisclib.pylab_starplot: This makes a little 'star' of error bars, using pylab/matplotlib.
 gmisclib.read_dicom
 gmisclib.robust_multivariate: Does a robust estimate of covariance.
 gmisclib.root: Solve a 1dimensional equation to find the roots.
 gmisclib.rubber_array: This acts like a dictionary, but indexed by integers and stored
rather more efficiently, at least in terms of memory.
 gmisclib.s_lin_fit: Fit a plane to some data.
 gmisclib.sbd_array
 gmisclib.segmentfile: This parses a '.in' file from xwaves.
 gmisclib.sharp_energy
 gmisclib.solve_sum_abs: Solves various equations involving minimizing the sum of absolute
values of things.
 gmisclib.spread_jobs: A module that starts a bunch of subprocesses and distributes work
amongst them, then collects the results.
 gmisclib.sqlbase: This is a module for using a SQLlite database as a collection of
python objects.
 gmisclib.stats: Some of these functions, specifically f_value(), fprob(), betai(),
and betacf(), are taken from stats.py "A collection of basic
statistical functions for python." by Gary Strangman.
 gmisclib.system_load
 gmisclib.threaded_io: This is designed to let you do asynchronous I/O conveniently.
 gmisclib.tsops: Do mathematical operations on time series, where the two operands
don't necessarily have the same sampling times.
 gmisclib.wavesurfer_lab: When used as a script, this reads label files produced by
wavesurfer and prints the result.
 gmisclib.wavio: When run as a script: python ~/lib/wavio.py [g gain]
wavinwavout infile outfile Reads or writes .wav files from any
format supported by gpkimgclass.py .
 gmisclib.weighted_percentile: This computes order statistics on data with weights.
 gmisclib.xmlmisc: This contains helper functions and classes for processing XML,
based on the ElementTree module.
 gmisclib.xwaves_errs: Errors for reading label (typically speech transcription) files.
 gmisclib.xwaves_lab: Reads label files produced by ESPS xwaves.
 gmisclib.xwaves_mark: Read in .in files produced by ESPS xmark.
