def dictOfBigramIcTimes(listOfBigrams,
df,
ict_XY_l=None,
label='call',
ict_label='ict'):
'''searches sequences (listOfBigrams) of type <label> in the dataframe and returns a
dictionary with the ict_label values of the sequences
Parameters
----------
listOfBigrams : list of bigrams
df : pandas data frame
ict_XY_l : dictionary of lists
bigrams as keys and the ict of the bigrams as values
label : type of sequence, or name of the column in df where to look for the sequences
ict_label : str
name of the column
Return
------
ict_XY : dictionary with lists
ICIs by bigram
'''
if ict_XY_l is None: ict_XY_l = defaultdict(list)
for seq in listOfBigrams:
try:
seqdf = daT.returnSequenceDf(df, seq, label='call')
except ValueError: # sequence not found, continue with the next seq
continue
ky = ''.join(seq) # seqdf.head(20)
ict_XY_l[ky].extend(seqdf[ict_label].values)
return ict_XY_l
def pl_ic_bigram_times(
df0,
my_bigrams,
ignoreKeys="default",
label="call",
oFig=None,
violinInner="box",
yrange="default",
ylabel="time (s)",
minNumBigrams=5,
):
"""violin plot of the ict of a my_bigrams
Parameters:
-----------
df0 : pandas dataframe wirth ict column
mu_bigrams : sequence to search for
ignoteKeys : 'default' removes ['_ini', '_end']
label : type of sequence
oFig : output figure
violinInner : viloin lor parameter
yrange : 'default' (0, mu*2)
"""
if ignoreKeys == "default":
ignoreKeys = ["_ini", "_end"]
topBigrams = daT.removeFromList(daT.returnSortingKeys(Counter(my_bigrams)),
ignoreKeys)
bigrTimes = []
bigrNames = []
for seq in topBigrams:
df = daT.returnSequenceDf(df0, seq, label=label)
# print(len(df))
ict = df.ict.values
if len(ict) > minNumBigrams:
# bigrTimes[tuple(seq)] = ict[ ~ np.isnan(ict)]
bigrTimes.append(ict[~np.isnan(ict)])
bigrNames.append(seq)
kys = ["{}{}".format(a, b) for a, b in bigrNames]
# sns.violinplot( bigrTimes, names=kys, inner=violinInner)
sns.boxplot(bigrTimes, names=kys)
if yrange == "default":
meanVls = [np.mean(item) for item in bigrTimes if len(item) > 1]
yrange = (0, np.mean(meanVls))
plt.ylim(yrange)
plt.ylabel(ylabel)
plt.savefig(oFig, bbox_inches="tight")