def CalcMCCF1(pred=None, truth=None, probCutoff=0.5, contactCutoff=8.0):
if pred is None:
print 'please provide a predicted contact matrix'
exit(-1)
if truth is None:
print 'please provide a true distance matrix'
exit(-1)
assert pred.shape == truth.shape
## in case the matrix is not square, e.g., interfacial contact matrix
seqLen = pred.shape[0]
seqLen2 = pred.shape[1]
pred_binary = (pred > probCutoff)
truth_binary = (0 < truth) & (truth < contactCutoff)
pred_truth = pred_binary * 2 + truth_binary
numPredicted = np.sum(pred_binary)
numTruths = np.sum(truth_binary)
#print "#predicted=", numPredicted, "#natives=", numTruths
mask_LR = np.triu_indices(seqLen, 24, m=seqLen2)
mask_MLR = np.triu_indices(seqLen, 12, m=seqLen2)
mask_SMLR = np.triu_indices(seqLen, 6, m=seqLen2)
metrics = []
for mask in [mask_LR, mask_MLR, mask_SMLR]:
res = pred_truth[mask]
total = res.shape[0]
count = np.bincount(res, minlength=4)
assert (total == np.sum(count))
## pred=0, truth=0
TN = count[0]
## pred=0, truth=1
FN = count[1]
## pred=1, truth=0
FP = count[2]
## pred=1, truth=1
TP = count[3]
#print TP, FP, TN, FN
MCC = Metrics.MCC(TP, FP, TN, FN)
F1, precision, recall = Metrics.F1(TP, FP, TN, FN)
metrics.extend([MCC, TP, FP, TN, FN, F1, precision, recall])
return np.array(metrics)
with open(nativeFile, 'rb') as fh:
nativeInfo = cPickle.load(fh)
truth = nativeInfo['atomDistMatrix']['CbCb']
truths[protein] = truth
for prob in np.arange(5, 60, 1):
#print "prob=", prob
accs = []
for protein in content:
acc = CalcMCCF1(pred=preds[protein],
truth=truths[protein],
probCutoff=prob / 100.)
accs.append(acc)
avgacc = np.average(accs, axis=0)
resultStr = 'per-target avgMCCF1 at cutoff=' + str(
prob) + ': ' + str_display(avgacc)
print resultStr
lrMCC = Metrics.MCC(avgacc[1], avgacc[2], avgacc[3], avgacc[4])
lrF1, lrprecision, lrrecall = Metrics.F1(avgacc[1], avgacc[2],
avgacc[3], avgacc[4])
mrMCC = Metrics.MCC(avgacc[9], avgacc[10], avgacc[11], avgacc[12])
mrF1, mrprecision, mrrecall = Metrics.F1(avgacc[9], avgacc[10],
avgacc[11], avgacc[12])
print 'per-pair avgMCCF1 at cutoff=' + str(prob) + ': ' + str_display([
lrMCC, lrF1, lrprecision, lrrecall, mrMCC, mrF1, mrprecision,
mrrecall
])
