In [1]:
from matplotlib.pyplot import imshow
import matplotlib.pyplot as plt
%matplotlib inline
In [2]:
import cPickle as pickle
from sklearn.metrics import precision_recall_curve, roc_curve
In [3]:
with open('/home/d/CREMIBIG/gp_y_test_proba.p', 'rb') as f:
gp_y_test_proba_cremi = pickle.load(f)
with open('/home/d/CREMIBIG/fp_y_test_proba.p', 'rb') as f:
fp_y_test_proba_cremi = pickle.load(f)
with open('/home/d/CREMIBIG/gt_y_test.p', 'rb') as f:
gt_y_test_cremi = pickle.load(f)
In [5]:
len(gt_y_test_cremi)
Out[5]:
In [19]:
gp_fpr_cremi, gp_tpr_cremi, gp_thresholds_cremi = roc_curve(gt_y_test_cremi,
gp_y_test_proba_cremi,
pos_label=1)
fp_fpr_cremi, fp_tpr_cremi, fp_thresholds_cremi = roc_curve(gt_y_test_cremi,
fp_y_test_proba_cremi,
pos_label=1)
gp_fpr_cremiA, gp_tpr_cremiA, gp_thresholds_cremiA = roc_curve(gt_y_test_cremi[0:cremiA_p],
gp_y_test_proba_cremi[0:cremiA_p],
pos_label=1)
fp_fpr_cremiA, fp_tpr_cremiA, fp_thresholds_cremiA = roc_curve(gt_y_test_cremi[0:cremiA_p],
fp_y_test_proba_cremi[0:cremiA_p],
pos_label=1)
gp_fpr_cremiB, gp_tpr_cremiB, gp_thresholds_cremiB = roc_curve(gt_y_test_cremi[cremiA_p:cremiA_p+cremiB_p],
gp_y_test_proba_cremi[cremiA_p:cremiA_p+cremiB_p],
pos_label=1)
fp_fpr_cremiB, fp_tpr_cremiB, fp_thresholds_cremiB = roc_curve(gt_y_test_cremi[cremiA_p:cremiB_p+cremiA_p],
fp_y_test_proba_cremi[cremiA_p:cremiB_p+cremiA_p],
pos_label=1)
gp_fpr_cremiC, gp_tpr_cremiC, gp_thresholds_cremiC = roc_curve(gt_y_test_cremi[-cremiC_p:],
gp_y_test_proba_cremi[-cremiC_p:],
pos_label=1)
fp_fpr_cremiC, fp_tpr_cremiC, fp_thresholds_cremiC = roc_curve(gt_y_test_cremi[-cremiC_p:],
fp_y_test_proba_cremi[-cremiC_p:],
pos_label=1)
fig = plt.figure(figsize=(10,10))
# plt.plot(gp_fpr_cremi, gp_tpr_cremi, color='#0571b0', label='Guided Proofreading: CREMI', linewidth=3)
# plt.plot(gp_fpr_cyl, gp_tpr_cyl, color='#92c5de', label='Guided Proofreading: L.Cylinder', linewidth=3)
# plt.plot(fp_fpr_cremi, fp_tpr_cremi, color='#ca0020', label='Focused Proofreading: CREMI', linewidth=3)
# plt.plot(fp_fpr_cyl, fp_tpr_cyl, color='#f4a582', label='Focused Proofreading: L.Cylinder', linewidth=3)
plt.plot(gp_fpr_cremiA, gp_tpr_cremiA, color='#2166ac', label='Guided Proofreading: CREMI A', linewidth=3)
plt.plot(fp_fpr_cremiA, fp_tpr_cremiA, color='#b2182b', label='Focused Proofreading: CREMI A', linewidth=3)
plt.plot(gp_fpr_cremiB, gp_tpr_cremiB, color='#67a9cf', label='Guided Proofreading: CREMI B', linewidth=3)
plt.plot(fp_fpr_cremiB, fp_tpr_cremiB, color='#ef8a62', label='Focused Proofreading: CREMI B', linewidth=3)
plt.plot(gp_fpr_cremiC, gp_tpr_cremiC, color='#d1e5f0', label='Guided Proofreading: CREMI C', linewidth=3)
plt.plot(fp_fpr_cremiC, fp_tpr_cremiC, color='#fddbc7', label='Focused Proofreading: CREMI C', linewidth=3)
plt.ylim([0.0, 1.05])
plt.xlim([0.0, 1.00])
font = {'family' : 'sans-serif',
'weight' : 'normal',
'size' : 22}
plt.rc('font', **font)
plt.rc('legend',**{'fontsize':18})
plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.legend( loc='lower right')
plt.savefig('/home/d/PAPERGFX/cremi_roc_separate.pdf', bbox_inches='tight')
In [22]:
gp_fpr_cremi, gp_tpr_cremi, gp_thresholds_cremi = roc_curve(gt_y_test_cremi,
gp_y_test_proba_cremi,
pos_label=1)
fp_fpr_cremi, fp_tpr_cremi, fp_thresholds_cremi = roc_curve(gt_y_test_cremi,
fp_y_test_proba_cremi,
pos_label=1)
gp_fpr_cremiA, gp_tpr_cremiA, gp_thresholds_cremiA = roc_curve(gt_y_test_cremi[cremiA_p_s_s:cremiA_p_s_e],
gp_y_test_proba_cremi[cremiA_p_s_s:cremiA_p_s_e],
pos_label=1)
fp_fpr_cremiA, fp_tpr_cremiA, fp_thresholds_cremiA = roc_curve(gt_y_test_cremi[cremiA_p_s_s:cremiA_p_s_e],
fp_y_test_proba_cremi[cremiA_p_s_s:cremiA_p_s_e],
pos_label=1)
gp_fpr_cremiB, gp_tpr_cremiB, gp_thresholds_cremiB = roc_curve(gt_y_test_cremi[cremiB_p_s_s:cremiB_p_s_e],
gp_y_test_proba_cremi[cremiB_p_s_s:cremiB_p_s_e],
pos_label=1)
fp_fpr_cremiB, fp_tpr_cremiB, fp_thresholds_cremiB = roc_curve(gt_y_test_cremi[cremiB_p_s_s:cremiB_p_s_e],
fp_y_test_proba_cremi[cremiB_p_s_s:cremiB_p_s_e],
pos_label=1)
gp_fpr_cremiC, gp_tpr_cremiC, gp_thresholds_cremiC = roc_curve(gt_y_test_cremi[cremiC_p_s_s:cremiC_p_s_e],
gp_y_test_proba_cremi[cremiC_p_s_s:cremiC_p_s_e],
pos_label=1)
fp_fpr_cremiC, fp_tpr_cremiC, fp_thresholds_cremiC = roc_curve(gt_y_test_cremi[cremiC_p_s_s:cremiC_p_s_e],
fp_y_test_proba_cremi[cremiC_p_s_s:cremiC_p_s_e],
pos_label=1)
fig = plt.figure(figsize=(10,10))
# plt.plot(gp_fpr_cremi, gp_tpr_cremi, color='#0571b0', label='Guided Proofreading: CREMI', linewidth=3)
# plt.plot(gp_fpr_cyl, gp_tpr_cyl, color='#92c5de', label='Guided Proofreading: L.Cylinder', linewidth=3)
# plt.plot(fp_fpr_cremi, fp_tpr_cremi, color='#ca0020', label='Focused Proofreading: CREMI', linewidth=3)
# plt.plot(fp_fpr_cyl, fp_tpr_cyl, color='#f4a582', label='Focused Proofreading: L.Cylinder', linewidth=3)
plt.plot(gp_fpr_cremiA, gp_tpr_cremiA, color='#2166ac', label='Guided Proofreading: CREMI A', linewidth=3)
plt.plot(fp_fpr_cremiA, fp_tpr_cremiA, color='#b2182b', label='Focused Proofreading: CREMI A', linewidth=3)
plt.plot(gp_fpr_cremiB, gp_tpr_cremiB, color='#67a9cf', label='Guided Proofreading: CREMI B', linewidth=3)
plt.plot(fp_fpr_cremiB, fp_tpr_cremiB, color='#ef8a62', label='Focused Proofreading: CREMI B', linewidth=3)
plt.plot(gp_fpr_cremiC, gp_tpr_cremiC, color='#d1e5f0', label='Guided Proofreading: CREMI C', linewidth=3)
plt.plot(fp_fpr_cremiC, fp_tpr_cremiC, color='#fddbc7', label='Focused Proofreading: CREMI C', linewidth=3)
plt.ylim([0.0, 1.05])
plt.xlim([0.0, 1.00])
font = {'family' : 'sans-serif',
'weight' : 'normal',
'size' : 22}
plt.rc('font', **font)
plt.rc('legend',**{'fontsize':18})
plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.legend( loc='lower right')
plt.savefig('/home/d/PAPERGFX/cremi_roc_separate_small.pdf', bbox_inches='tight')
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aaa='''
working on slice 0
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Generated 864 split error patches and 864 correct patches in 88.7517929077 seconds.
working on slice 1
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Generated 644 split error patches and 644 correct patches in 77.0009469986 seconds.
working on slice 2
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Generated 412 split error patches and 412 correct patches in 64.2233221531 seconds.
working on slice 3
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Generated 408 split error patches and 408 correct patches in 60.1068799496 seconds.
working on slice 4
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Generated 392 split error patches and 392 correct patches in 61.5711750984 seconds.
working on slice 5
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Generated 456 split error patches and 456 correct patches in 67.9314539433 seconds.
working on slice 6
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Generated 584 split error patches and 584 correct patches in 72.199368 seconds.
working on slice 7
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Generated 516 split error patches and 516 correct patches in 74.4610579014 seconds.
working on slice 8
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Generated 600 split error patches and 600 correct patches in 79.8463599682 seconds.
working on slice 9
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Generated 536 split error patches and 536 correct patches in 73.4399859905 seconds.
working on slice 10
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Generated 660 split error patches and 660 correct patches in 80.8224570751 seconds.
working on slice 11
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Generated 516 split error patches and 516 correct patches in 73.8577289581 seconds.
working on slice 12
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Generated 568 split error patches and 568 correct patches in 72.4297659397 seconds.
working on slice 13
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Generated 748 split error patches and 748 correct patches in 81.5840780735 seconds.
working on slice 14
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Generated 548 split error patches and 548 correct patches in 72.7623548508 seconds.
working on slice 15
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Generated 440 split error patches and 440 correct patches in 65.453111887 seconds.
working on slice 16
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Generated 448 split error patches and 448 correct patches in 67.6617920399 seconds.
working on slice 17
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Generated 676 split error patches and 676 correct patches in 78.8249759674 seconds.
working on slice 18
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Generated 712 split error patches and 712 correct patches in 81.3622560501 seconds.
working on slice 19
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Generated 588 split error patches and 588 correct patches in 76.3714969158 seconds.
working on slice 20
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Generated 640 split error patches and 640 correct patches in 75.4619441032 seconds.
working on slice 21
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Generated 568 split error patches and 568 correct patches in 75.369535923 seconds.
working on slice 22
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Generated 564 split error patches and 564 correct patches in 74.2786240578 seconds.
working on slice 23
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Generated 620 split error patches and 620 correct patches in 76.340389967 seconds.
working on slice 24
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Generated 412 split error patches and 412 correct patches in 64.9502279758 seconds.
working on slice 25
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Generated 560 split error patches and 560 correct patches in 49.6370921135 seconds.
working on slice 26
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Generated 456 split error patches and 456 correct patches in 45.1472828388 seconds.
working on slice 27
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Generated 432 split error patches and 432 correct patches in 45.1168401241 seconds.
working on slice 28
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Generated 444 split error patches and 444 correct patches in 43.5215339661 seconds.
working on slice 29
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Generated 588 split error patches and 588 correct patches in 48.6778891087 seconds.
working on slice 30
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Generated 496 split error patches and 496 correct patches in 49.1675620079 seconds.
working on slice 31
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Generated 520 split error patches and 520 correct patches in 42.579144001 seconds.
working on slice 32
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Generated 452 split error patches and 452 correct patches in 35.224063158 seconds.
working on slice 33
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Generated 372 split error patches and 372 correct patches in 31.4410500526 seconds.
working on slice 34
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Generated 428 split error patches and 428 correct patches in 35.9716060162 seconds.
working on slice 35
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Generated 400 split error patches and 400 correct patches in 37.2554290295 seconds.
working on slice 36
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Generated 372 split error patches and 372 correct patches in 35.0172948837 seconds.
working on slice 37
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Generated 412 split error patches and 412 correct patches in 35.0888030529 seconds.
working on slice 38
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Generated 324 split error patches and 324 correct patches in 32.1475739479 seconds.
working on slice 39
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Generated 292 split error patches and 292 correct patches in 33.4721031189 seconds.
working on slice 40
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Generated 292 split error patches and 292 correct patches in 32.145138979 seconds.
working on slice 41
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Generated 356 split error patches and 356 correct patches in 37.1747980118 seconds.
working on slice 42
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Generated 432 split error patches and 432 correct patches in 39.0164089203 seconds.
working on slice 43
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Generated 408 split error patches and 408 correct patches in 37.8132679462 seconds.
working on slice 44
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Generated 412 split error patches and 412 correct patches in 34.8254818916 seconds.
working on slice 45
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Generated 412 split error patches and 412 correct patches in 36.1974160671 seconds.
working on slice 46
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Generated 396 split error patches and 396 correct patches in 34.8207061291 seconds.
working on slice 47
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Generated 332 split error patches and 332 correct patches in 29.9883439541 seconds.
working on slice 48
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Generated 304 split error patches and 304 correct patches in 27.8007190228 seconds.
working on slice 49
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Generated 260 split error patches and 260 correct patches in 25.1326870918 seconds.
working on slice 50
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Generated 656 split error patches and 656 correct patches in 67.8867759705 seconds.
working on slice 51
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Generated 708 split error patches and 708 correct patches in 64.5013170242 seconds.
working on slice 52
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Generated 520 split error patches and 520 correct patches in 59.3628590107 seconds.
working on slice 53
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Generated 612 split error patches and 612 correct patches in 64.0020170212 seconds.
working on slice 54
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Generated 860 split error patches and 860 correct patches in 69.3872699738 seconds.
working on slice 55
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Generated 892 split error patches and 892 correct patches in 67.2891058922 seconds.
working on slice 56
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Generated 696 split error patches and 696 correct patches in 60.5339829922 seconds.
working on slice 57
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Generated 792 split error patches and 792 correct patches in 64.5792591572 seconds.
working on slice 58
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Generated 844 split error patches and 844 correct patches in 67.5466179848 seconds.
working on slice 59
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Generated 760 split error patches and 760 correct patches in 71.1473760605 seconds.
working on slice 60
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Generated 816 split error patches and 816 correct patches in 72.0629360676 seconds.
working on slice 61
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Generated 680 split error patches and 680 correct patches in 68.313035965 seconds.
working on slice 62
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Generated 672 split error patches and 672 correct patches in 68.6422839165 seconds.
working on slice 63
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Generated 828 split error patches and 828 correct patches in 75.3140921593 seconds.
working on slice 64
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Generated 776 split error patches and 776 correct patches in 66.7116239071 seconds.
working on slice 65
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Generated 644 split error patches and 644 correct patches in 58.7857379913 seconds.
working on slice 66
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Generated 608 split error patches and 608 correct patches in 59.1434319019 seconds.
working on slice 67
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Generated 628 split error patches and 628 correct patches in 59.5656120777 seconds.
working on slice 68
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Generated 492 split error patches and 492 correct patches in 50.8020510674 seconds.
working on slice 69
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Generated 348 split error patches and 348 correct patches in 47.0378401279 seconds.
working on slice 70
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Generated 516 split error patches and 516 correct patches in 55.1166660786 seconds.
working on slice 71
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Generated 352 split error patches and 352 correct patches in 48.1190011501 seconds.
working on slice 72
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Generated 320 split error patches and 320 correct patches in 44.1336331367 seconds.
working on slice 73
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Generated 320 split error patches and 320 correct patches in 41.7422299385 seconds.
working on slice 74
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Generated 284 split error patches and 284 correct patches in 40.7786231041 seconds.
'''
patches_per_slice = []
for a in aaa.split('\n'):
if a.startswith('Generated'):
nom = a.split(' ')[1]
patches_per_slice.append(int(nom))
In [10]:
import numpy as np
In [14]:
cremiA_p = np.sum(patches_per_slice[0:25])
In [15]:
cremiB_p = np.sum(patches_per_slice[25:50])
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cremiC_p = np.sum(patches_per_slice[50:75])
In [21]:
cremiA_p_s_s = np.sum(patches_per_slice[:20])
cremiA_p_s_e = np.sum(patches_per_slice[:25])
cremiB_p_s_s = np.sum(patches_per_slice[:45])
cremiB_p_s_e = np.sum(patches_per_slice[:50])
cremiC_p_s_s = np.sum(patches_per_slice[:70])
cremiC_p_s_e = np.sum(patches_per_slice[:75])
In [23]:
cremiC_p_s_e
Out[23]:
In [24]:
np.sum(patches_per_slice)
Out[24]:
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