Implementation of dominant scale analysis techniques for python.
Loosely based on Matlab tool DSSRT. This module is incomplete and is
still a work in progress! See my publications on this subject for further
details.
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find_ep_ix(eps,
t)
Finds epoch during time t |
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find_regime_transition(criteria_list,
min_t=-inf) |
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transition_psi(epoch,
pt,
atol)
Assume that, generically, there will only be one transition at a
time. |
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transition_tau(epoch,
pt,
atol)
Assume that, generically, there will only be one transition at a
time. |
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define_psi_events(acts_all,
mods_all,
focus_var,
ignore_transitions=None) |
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get_taus(pts,
tau_names)
pts can be a Point or Pointset |
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get_infs(pts,
inf_names)
pts can be a Point or Pointset |
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split_pts(pts,
interval,
reset_t0=None)
Return trajectory made up from pts argument restricted to the given
interval. |
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split(ds_pt,
thresh)
Split this grouping of values into sub-groups according to spectral
gaps at threshold thresh |
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spectral_gaps_relative(as_rel_ratios,
thresh)
List of indices of spectral gaps larger than thresh in size |
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spectral_gaps_absolute(as_abs_ratios,
thresh)
List of indices of spectral gaps larger than thresh in size |
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normalized_psis(epochs,
root,
midpoint_only=True,
small=1e-16)
Returns Pointset of normalized* psis based on contents of 'epochs' argument,
which would be returned from running da.domscales['psi'].calc_epochs()
where da is a domscales assistant class. |
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show_epochs(eps)
Small utility to print more detailed information about epochs |
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plot_psis(da,
cols=None,
do_vars=None,
do_log=True,
use_prefix=True)
da is a dssrt_assistant object. |
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get_symbol_sequence(epoch_list,
get_actives=True,
get_modulatory=False) |
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comp_seqs(seq1,
seq2,
scorer)
Based on code by Gergely Szollosi |
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swdist(str1,
str2,
scorer,
common_divisor=' longest ' ,
min_threshold=None)
Return approximate string comparator measure (between 0.0 and 1.0)
using the Smith-Waterman distance. |
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editdist_edits(str1,
str2)
Return approximate string comparator measure (between 0.0 and 1.0)
using the edit (or Levenshtein) distance as well as a triplet with the
counts of the actual edits (inserts, deletes and substitutions). |
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jaro(str1,
str2,
min_threshold=None)
Return approximate string comparator measure (between 0.0 and 1.0) |
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tabulate_epoch_seqs(epseq1,
epseq2)
Create a text table of epochs |
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indent(rows,
hasHeader=False,
headerChar=' - ' ,
delim=' | ' ,
justify=' left ' ,
separateRows=False,
prefix='
' ,
postfix='
' ,
wrapfunc=<function <lambda> at 0x97359f0>)
Indents a table by column. |
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