assert (set(df['tape'].values) == set([113, 114, 115, 111]))
assert (set(tapedf.keys()) == set([113, 114, 115, 111]))
# # Bigrams and randomisations test
#
# Define the **sequences**
# In[4]:
## parameters and settings
Dt = 0.3
Dtint = (float('-inf'), Dt)
## define the sequences
sequencesList0 = aa.dfDict2listOfSeqs(tapedf,
Dt=Dtint,
l='call',
time_param='ici')
## filter out isolated calls (sequences of size one)
sequencesList = [l for l in sequencesList0 if len(l) > 1]
seqO = mysts.sequenceBigrams(sequencesList)
def test_seqO():
assert (len(seqO.seqOfSeqs) == 71)
assert (seqO.callCounts['129'] == 89)
# **Bigrams**, counts and probabilities
# In[5]:
Nsh = 1000
pc = 0.05
## labels for the calls
calls = [1.0, 2.0, 3.0, 4.0]
# if item[1] > minCalls]
sampsLi = calls[:] + ["_end"] # None #[ 'A', 'B', 'C', 'E', '_ini','_end']
condsLi = calls[:] + ["_ini"]
# remove sequences with cs = -1
rmNodes = list(set(df[call_label]) -
set(calls)) + [-1.0] # nodes to remove from network
#
minBigrams = 3
### define sequence object
# sequences
sequencesList0 = aa.dfDict2listOfSeqs(tape_df,
Dt=Dtint,
l=call_label,
time_param=time_param)
# filter out isolated calls (sequences of size one)
sequencesList = [l for l in sequencesList0 if len(l) > 1]
# object
seqO = myst.sequenceBigrams(sequencesList)
# In[52]:
def test_seqO():
assert len(seqO.seqOfSeqs) == 2027
np.testing.assert_array_almost_equal(seqO.callCounts[2.0], 345)
assert set(df["tape"].values) == set([113, 114, 115, 111])
assert set(tapedf.keys()) == set([113, 114, 115, 111])
# # Bigrams and randomisations test
#
# Define the **sequences**
# In[4]:
## parameters and settings
Dt = 0.3
Dtint = (None, Dt)
## define the sequences
sequencesList0 = aa.dfDict2listOfSeqs(tapedf,
Dt=Dtint,
l="call",
time_param="ici")
## filter out isolated calls (sequences of size one)
sequencesList = [l for l in sequencesList0 if len(l) > 1]
seqO = mysts.sequenceBigrams(sequencesList)
def test_seqO():
assert len(seqO.seqOfSeqs) == 71
assert seqO.callCounts["129"] == 89
# **Bigrams**, counts and probabilities
# In[5]: