From 5328cd5f209d74b45c069a2564d6a5a89b39005a Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 14:14:01 +0430 Subject: [PATCH 01/11] feat : Braun-Blanquet-similarity added #349 --- pycm/pycm_class_func.py | 19 +++++++++++++++++++ pycm/pycm_handler.py | 2 +- pycm/pycm_param.py | 9 ++++++--- 3 files changed, 26 insertions(+), 4 deletions(-) diff --git a/pycm/pycm_class_func.py b/pycm/pycm_class_func.py index 37c4a495..0099c2ad 100644 --- a/pycm/pycm_class_func.py +++ b/pycm/pycm_class_func.py @@ -104,6 +104,24 @@ def OC_calc(TP, TOP, P): except (ZeroDivisionError, TypeError): return "None" +def BB_calc(TP, TOP, P): + """ + Calculate Braun-Blanquet similarity (BB). + + :param TP: true positive + :type TP: int + :param TOP: number of positives in predict vector + :type TOP: int + :param P: number of actual positives + :type P: int + :return: BB as float + """ + try: + BB = TP / max(TOP, P) + return BB + except (ZeroDivisionError, TypeError): + return "None" + def AGF_calc(TP, FP, FN, TN): """ @@ -790,6 +808,7 @@ def class_statistics(TP, TN, FP, FN, classes, table): result["MCCI"][i] = MCC_analysis(result["MCC"][i]) result["AGF"][i] = AGF_calc(TP[i], FP[i], FN[i], TN[i]) result["OC"][i] = OC_calc(TP[i], result["TOP"][i], result["P"][i]) + result["BB"][i] = BB_calc(TP[i], result["TOP"][i], result["P"][i]) result["OOC"][i] = OOC_calc(TP[i], result["TOP"][i], result["P"][i]) result["AUPR"][i] = AUC_calc(result["PPV"][i], result["TPR"][i]) result["ICSI"][i] = MK_BM_calc(result["PPV"][i], result["TPR"][i]) diff --git a/pycm/pycm_handler.py b/pycm/pycm_handler.py index de126862..6986fd2b 100644 --- a/pycm/pycm_handler.py +++ b/pycm/pycm_handler.py @@ -77,7 +77,7 @@ def __class_stat_init__(cm): cm.AUPR = cm.class_stat["AUPR"] cm.ICSI = cm.class_stat["ICSI"] cm.HD = cm.class_stat["HD"] - + cm.BB = cm.class_stat["BB"] def __overall_stat_init__(cm): """ diff --git a/pycm/pycm_param.py b/pycm/pycm_param.py index 84b04dc1..832ef885 100644 --- a/pycm/pycm_param.py +++ b/pycm/pycm_param.py @@ -171,7 +171,8 @@ "AUPR", "ICSI", "QI", - "HD"] + "HD", + "BB"] SUMMARY_OVERALL = [ "ACC Macro", @@ -455,7 +456,8 @@ "OOC": "Otsuka-Ochiai coefficient", "AUPR": "Area under the PR curve", "ICSI": "Individual classification success index", - "HD": "Hamming distance"} + "HD": "Hamming distance", + "BB": "Braun-Blanquet similarity"} PARAMS_LINK = { "TPR": "TPR-(True-positive-rate)", @@ -582,7 +584,8 @@ "ARI": "ARI-(Adjusted-Rand-index)", "Bangdiwala B": "Bangdiwala's-B", "Krippendorff Alpha": "Krippendorff's-alpha", - "HD": "HD-(Hamming-distance)"} + "HD": "HD-(Hamming-distance)", + "BB": "BB-(Braun-Blanquet-similarity)"} CAPITALIZE_FILTER = ["BCD", "AUCI", "Q", "AGF", "OOC", "AUPR", "AUC", "QI"] From 2bd805e1719f8f67fbeddf7d5bf43db9dc43df6f Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 14:21:29 +0430 Subject: [PATCH 02/11] fix : BB verified test added #349 --- Test/verified_test.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/Test/verified_test.py b/Test/verified_test.py index 99a93fe1..932e5a3f 100644 --- a/Test/verified_test.py +++ b/Test/verified_test.py @@ -392,4 +392,9 @@ 5 >>> cm2.HD[0] 5 +>>> cm1 = ConfusionMatrix(matrix = {1:{1:2,0:2},0:{0:778,1:2}}) # Verified Case -- (https://bit.ly/3BVdNBp) +>>> cm1.BB +0.5 +>>> cm2 = ConfusionMatrix(matrix = {1:{1:2,0:3},0:{0:775,1:4}}) # Verified Case -- (https://bit.ly/3BVdNBp) +0.3333333333333333 """ From bb5a1b010758fc0f4341fdf6cd34c5871a998be4 Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 14:38:08 +0430 Subject: [PATCH 03/11] fix : tests updated #349 --- Test/function_test.py | 229 +++++++++++++++++++++--------------------- Test/output_test.py | 2 + Test/overall_test.py | 7 ++ Test/verified_test.py | 3 +- Test/warning_test.py | 3 + pycm/pycm_param.py | 2 +- 6 files changed, 131 insertions(+), 115 deletions(-) diff --git a/Test/function_test.py b/Test/function_test.py index 718ac588..116e9d4f 100644 --- a/Test/function_test.py +++ b/Test/function_test.py @@ -56,119 +56,120 @@ 10-AUNP 11-AUNU 12-AUPR -13-BCD -14-BM -15-Bangdiwala B -16-Bennett S -17-CBA -18-CEN -19-CSI -20-Chi-Squared -21-Chi-Squared DF -22-Conditional Entropy -23-Cramer V -24-Cross Entropy -25-DOR -26-DP -27-DPI -28-ERR -29-F0.5 -30-F1 -31-F1 Macro -32-F1 Micro -33-F2 -34-FDR -35-FN -36-FNR -37-FNR Macro -38-FNR Micro -39-FOR -40-FP -41-FPR -42-FPR Macro -43-FPR Micro -44-G -45-GI -46-GM -47-Gwet AC1 -48-HD -49-Hamming Loss -50-IBA -51-ICSI -52-IS -53-J -54-Joint Entropy -55-KL Divergence -56-Kappa -57-Kappa 95% CI -58-Kappa No Prevalence -59-Kappa Standard Error -60-Kappa Unbiased -61-Krippendorff Alpha -62-LS -63-Lambda A -64-Lambda B -65-MCC -66-MCCI -67-MCEN -68-MK -69-Mutual Information -70-N -71-NIR -72-NLR -73-NLRI -74-NPV -75-OC -76-OOC -77-OP -78-Overall ACC -79-Overall CEN -80-Overall J -81-Overall MCC -82-Overall MCEN -83-Overall RACC -84-Overall RACCU -85-P -86-P-Value -87-PLR -88-PLRI -89-POP -90-PPV -91-PPV Macro -92-PPV Micro -93-PRE -94-Pearson C -95-Phi-Squared -96-Q -97-QI -98-RACC -99-RACCU -100-RCI -101-RR -102-Reference Entropy -103-Response Entropy -104-SOA1(Landis & Koch) -105-SOA2(Fleiss) -106-SOA3(Altman) -107-SOA4(Cicchetti) -108-SOA5(Cramer) -109-SOA6(Matthews) -110-Scott PI -111-Standard Error -112-TN -113-TNR -114-TNR Macro -115-TNR Micro -116-TON -117-TOP -118-TP -119-TPR -120-TPR Macro -121-TPR Micro -122-Y -123-Zero-one Loss -124-dInd -125-sInd +13-BB +14-BCD +15-BM +16-Bangdiwala B +17-Bennett S +18-CBA +19-CEN +20-CSI +21-Chi-Squared +22-Chi-Squared DF +23-Conditional Entropy +24-Cramer V +25-Cross Entropy +26-DOR +27-DP +28-DPI +29-ERR +30-F0.5 +31-F1 +32-F1 Macro +33-F1 Micro +34-F2 +35-FDR +36-FN +37-FNR +38-FNR Macro +39-FNR Micro +40-FOR +41-FP +42-FPR +43-FPR Macro +44-FPR Micro +45-G +46-GI +47-GM +48-Gwet AC1 +49-HD +50-Hamming Loss +51-IBA +52-ICSI +53-IS +54-J +55-Joint Entropy +56-KL Divergence +57-Kappa +58-Kappa 95% CI +59-Kappa No Prevalence +60-Kappa Standard Error +61-Kappa Unbiased +62-Krippendorff Alpha +63-LS +64-Lambda A +65-Lambda B +66-MCC +67-MCCI +68-MCEN +69-MK +70-Mutual Information +71-N +72-NIR +73-NLR +74-NLRI +75-NPV +76-OC +77-OOC +78-OP +79-Overall ACC +80-Overall CEN +81-Overall J +82-Overall MCC +83-Overall MCEN +84-Overall RACC +85-Overall RACCU +86-P +87-P-Value +88-PLR +89-PLRI +90-POP +91-PPV +92-PPV Macro +93-PPV Micro +94-PRE +95-Pearson C +96-Phi-Squared +97-Q +98-QI +99-RACC +100-RACCU +101-RCI +102-RR +103-Reference Entropy +104-Response Entropy +105-SOA1(Landis & Koch) +106-SOA2(Fleiss) +107-SOA3(Altman) +108-SOA4(Cicchetti) +109-SOA5(Cramer) +110-SOA6(Matthews) +111-Scott PI +112-Standard Error +113-TN +114-TNR +115-TNR Macro +116-TNR Micro +117-TON +118-TOP +119-TP +120-TPR +121-TPR Macro +122-TPR Micro +123-Y +124-Zero-one Loss +125-dInd +126-sInd >>> online_help("J") ... >>> online_help("J",alt_link=True) @@ -220,6 +221,8 @@ 'None' >>> RCI_calc(24,0) 'None' +>>> BB_calc(0,0,0) +'None' >>> CEN_calc([1,2,3], {1:{1:0,2:0},2:{1:0,2:0}}, {1:2,2:3}, {1:2,2:3}, 2, modified=False) 'None' >>> convex_combination([1,2,3], {1:{1:0,2:0},2:{1:0,2:0}}, {1:2,2:3}, {1:2,2:3}, 2, modified=False) diff --git a/Test/output_test.py b/Test/output_test.py index 9b14a040..510c5a5e 100644 --- a/Test/output_test.py +++ b/Test/output_test.py @@ -197,6 +197,7 @@ AUC(Area under the ROC curve) None 0.5625 0.63725 0.5 AUCI(AUC value interpretation) None Poor Fair Poor AUPR(Area under the PR curve) None 0.61607 0.41667 None +BB(Braun-Blanquet similarity) 0.0 0.375 0.33333 0.0 BCD(Bray-Curtis dissimilarity) 0.275 0.225 0.025 0.025 BM(Informedness or bookmaker informedness) None 0.125 0.27451 0.0 CEN(Confusion entropy) 0.33496 0.35708 0.53895 0.0 @@ -418,6 +419,7 @@ AUC(Area under the ROC curve) 0.86667 0.61111 0.63889 AUCI(AUC value interpretation) Very Good Fair Fair AUPR(Area under the PR curve) 0.8 0.33333 0.625 +BB(Braun-Blanquet similarity) 0.6 0.33333 0.5 BCD(Bray-Curtis dissimilarity) 0.09524 0.0 0.09524 BM(Informedness or bookmaker informedness) 0.73333 0.22222 0.27778 CEN(Confusion entropy) 0.25 0.52832 0.56439 diff --git a/Test/overall_test.py b/Test/overall_test.py index 800ea44d..a50c4fd9 100644 --- a/Test/overall_test.py +++ b/Test/overall_test.py @@ -102,6 +102,7 @@ AUC(Area under the ROC curve) 0.88889 0.61111 0.58333 AUCI(AUC value interpretation) Very Good Fair Poor AUPR(Area under the PR curve) 0.8 0.41667 0.55 +BB(Braun-Blanquet similarity) 0.6 0.33333 0.5 BCD(Bray-Curtis dissimilarity) 0.08333 0.04167 0.04167 BM(Informedness or bookmaker informedness) 0.77778 0.22222 0.16667 CEN(Confusion entropy) 0.25 0.49658 0.60442 @@ -254,6 +255,7 @@ AUC(Area under the ROC curve) 0.88889 0.61111 0.58333 AUCI(AUC value interpretation) Very Good Fair Poor AUPR(Area under the PR curve) 0.8 0.41667 0.55 +BB(Braun-Blanquet similarity) 0.6 0.33333 0.5 BCD(Bray-Curtis dissimilarity) 0.08333 0.04167 0.04167 BM(Informedness or bookmaker informedness) 0.77778 0.22222 0.16667 CEN(Confusion entropy) 0.25 0.49658 0.60442 @@ -421,6 +423,7 @@ AUC(Area under the ROC curve) None 0.5625 0.63725 0.5 AUCI(AUC value interpretation) None Poor Fair Poor AUPR(Area under the PR curve) None 0.61607 0.41667 None +BB(Braun-Blanquet similarity) 0.0 0.375 0.33333 0.0 BCD(Bray-Curtis dissimilarity) 0.275 0.225 0.025 0.025 BM(Informedness or bookmaker informedness) None 0.125 0.27451 0.0 CEN(Confusion entropy) 0.33496 0.35708 0.53895 0.0 @@ -554,6 +557,7 @@ AUC(Area under the ROC curve) None 0.5625 0.63725 0.5 AUCI(AUC value interpretation) None Poor Fair Poor AUPR(Area under the PR curve) None 0.61607 0.41667 None +BB(Braun-Blanquet similarity) 0.0 0.375 0.33333 0.0 BCD(Bray-Curtis dissimilarity) 0.275 0.225 0.025 0.025 BM(Informedness or bookmaker informedness) None 0.125 0.27451 0.0 CEN(Confusion entropy) 0.33496 0.35708 0.53895 0.0 @@ -845,6 +849,7 @@ AUC(Area under the ROC curve) 0.74167 0.66667 0.80952 AUCI(AUC value interpretation) Good Fair Very Good AUPR(Area under the PR curve) 0.72115 0.55556 0.73333 +BB(Braun-Blanquet similarity) 0.69231 0.55556 0.66667 BCD(Bray-Curtis dissimilarity) 0.01852 0.0 0.01852 BM(Informedness or bookmaker informedness) 0.48333 0.33333 0.61905 CEN(Confusion entropy) 0.45994 0.66249 0.47174 @@ -995,6 +1000,7 @@ AUC(Area under the ROC curve) 0.74167 0.66667 0.80952 AUCI(AUC value interpretation) Good Fair Very Good AUPR(Area under the PR curve) 0.72115 0.55556 0.73333 +BB(Braun-Blanquet similarity) 0.69231 0.55556 0.66667 BCD(Bray-Curtis dissimilarity) 0.01852 0.0 0.01852 BM(Informedness or bookmaker informedness) 0.48333 0.33333 0.61905 CEN(Confusion entropy) 0.45994 0.66249 0.47174 @@ -1147,6 +1153,7 @@ AUC(Area under the ROC curve) 0.86667 0.61111 0.63889 AUCI(AUC value interpretation) Very Good Fair Fair AUPR(Area under the PR curve) 0.8 0.33333 0.625 +BB(Braun-Blanquet similarity) 0.6 0.33333 0.5 BCD(Bray-Curtis dissimilarity) 0.09524 0.0 0.09524 BM(Informedness or bookmaker informedness) 0.73333 0.22222 0.27778 CEN(Confusion entropy) 0.25 0.52832 0.56439 diff --git a/Test/verified_test.py b/Test/verified_test.py index 932e5a3f..5b0fd991 100644 --- a/Test/verified_test.py +++ b/Test/verified_test.py @@ -393,8 +393,9 @@ >>> cm2.HD[0] 5 >>> cm1 = ConfusionMatrix(matrix = {1:{1:2,0:2},0:{0:778,1:2}}) # Verified Case -- (https://bit.ly/3BVdNBp) ->>> cm1.BB +>>> cm1.BB[1] 0.5 >>> cm2 = ConfusionMatrix(matrix = {1:{1:2,0:3},0:{0:775,1:4}}) # Verified Case -- (https://bit.ly/3BVdNBp) +>>> cm1.BB[1] 0.3333333333333333 """ diff --git a/Test/warning_test.py b/Test/warning_test.py index 8a6c826a..04f54865 100644 --- a/Test/warning_test.py +++ b/Test/warning_test.py @@ -129,6 +129,7 @@ AUC(Area under the ROC curve) 1.0 0.95833 0.70455 0.75 1.0 0.75 1.0 0.95833 1.0 1.0 AUCI(AUC value interpretation) Excellent Excellent Good Good Excellent Good Excellent Excellent Excellent Excellent AUPR(Area under the PR curve) 1.0 0.75 0.5 0.75 1.0 0.75 1.0 0.75 1.0 1.0 +BB(Braun-Blanquet similarity) 1.0 0.5 0.5 0.5 1.0 0.5 1.0 0.5 1.0 1.0 BCD(Bray-Curtis dissimilarity) 0.0 0.03846 0.0 0.03846 0.0 0.03846 0.0 0.03846 0.0 0.0 BM(Informedness or bookmaker informedness) 1.0 0.91667 0.40909 0.5 1.0 0.5 1.0 0.91667 1.0 1.0 CEN(Confusion entropy) 0 0.1267 0.23981 0.1267 0 0.1267 0 0.1267 0 0 @@ -289,6 +290,7 @@ AUC(Area under the ROC curve) 1.0 0.95833 0.70455 0.75 1.0 0.75 1.0 0.95833 1.0 1.0 AUCI(AUC value interpretation) Excellent Excellent Good Good Excellent Good Excellent Excellent Excellent Excellent AUPR(Area under the PR curve) 1.0 0.75 0.5 0.75 1.0 0.75 1.0 0.75 1.0 1.0 +BB(Braun-Blanquet similarity) 1.0 0.5 0.5 0.5 1.0 0.5 1.0 0.5 1.0 1.0 BCD(Bray-Curtis dissimilarity) 0.0 0.03846 0.0 0.03846 0.0 0.03846 0.0 0.03846 0.0 0.0 BM(Informedness or bookmaker informedness) 1.0 0.91667 0.40909 0.5 1.0 0.5 1.0 0.91667 1.0 1.0 CEN(Confusion entropy) 0 0.1267 0.23981 0.1267 0 0.1267 0 0.1267 0 0 @@ -469,6 +471,7 @@ AUC(Area under the ROC curve) 0.66667 0.80952 0.74167 None AUCI(AUC value interpretation) Fair Very Good Good None AUPR(Area under the PR curve) 0.55556 0.73333 0.72115 None +BB(Braun-Blanquet similarity) 0.55556 0.66667 0.69231 None BCD(Bray-Curtis dissimilarity) 0.0 0.01852 0.01852 0.0 BM(Informedness or bookmaker informedness) 0.33333 0.61905 0.48333 None CEN(Confusion entropy) 0.51257 0.36499 0.35586 None diff --git a/pycm/pycm_param.py b/pycm/pycm_param.py index 832ef885..dc9b2374 100644 --- a/pycm/pycm_param.py +++ b/pycm/pycm_param.py @@ -587,7 +587,7 @@ "HD": "HD-(Hamming-distance)", "BB": "BB-(Braun-Blanquet-similarity)"} -CAPITALIZE_FILTER = ["BCD", "AUCI", "Q", "AGF", "OOC", "AUPR", "AUC", "QI"] +CAPITALIZE_FILTER = ["BCD", "AUCI", "Q", "AGF", "OOC", "AUPR", "AUC", "QI", "BB"] BENCHMARK_COLOR = { "PLRI": { From 52e8f29a342d4c73372ce07f8db2f7a0122170f4 Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 14:44:21 +0430 Subject: [PATCH 04/11] fix : minor bug in BB verified tests fixed --- Test/verified_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Test/verified_test.py b/Test/verified_test.py index 5b0fd991..e4b7a5b5 100644 --- a/Test/verified_test.py +++ b/Test/verified_test.py @@ -396,6 +396,6 @@ >>> cm1.BB[1] 0.5 >>> cm2 = ConfusionMatrix(matrix = {1:{1:2,0:3},0:{0:775,1:4}}) # Verified Case -- (https://bit.ly/3BVdNBp) ->>> cm1.BB[1] +>>> cm2.BB[1] 0.3333333333333333 """ From 2137b445b375e2573e1be6db14462308f8c7529e Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 15:05:30 +0430 Subject: [PATCH 05/11] doc : Document updated #349 --- Document/Document.ipynb | 44 ++++++++++++++++++++++++++++++++++++++++- 1 file changed, 43 insertions(+), 1 deletion(-) diff --git a/Document/Document.ipynb b/Document/Document.ipynb index 2809e203..52f82012 100644 --- a/Document/Document.ipynb +++ b/Document/Document.ipynb @@ -125,6 +125,7 @@ "
  • Adjusted G-Mean
    • \n", "
  • Adjusted F-Score
    • \n", "
  • Overlap Coefficient
    • \n", + "
  • Braun-Blanquet Coefficient
    • \n", "
  • Otsuka Ochiai Coefficient
    • \n", "
  • Tversky Index
    • \n", "
  • Area Under The PR Curve
    • \n", @@ -6152,6 +6153,45 @@ "" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### BB (Braun-Blanquet coefficient)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The Braun-Blanquet coefficient is a similarity measure that is mostly used in botany. It is defined as the size of the intersection divided by the larger of the size of the two sets [[82]](#ref82)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$BB=\\frac{TP}{max(TOP,P)}=min(PPV,TPR)$$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cm.BB" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
      \n", + "
    • Notice : new in version 3.6
      • \n", + "
    " + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -14029,7 +14069,9 @@ "\n", "
    80- R. W. Hamming, \"Error detecting and error correcting codes,\" The Bell system technical journal, vol. 29, no. 2, pp. 147-160, 1950.
    \n", "\n", - "
    81- S. S. Choi, S. H. Cha, and C. C. Tappert, \"A survey of binary similarity and distance measures,\" Journal of systemics, cybernetics and informatics, vol. 8, no. 1, pp. 43-48, 2010.
    \n" + "
    81- S. S. Choi, S. H. Cha, and C. C. Tappert, \"A survey of binary similarity and distance measures,\" Journal of systemics, cybernetics and informatics, vol. 8, no. 1, pp. 43-48, 2010.
    \n", + "\n", + "
    82- Josias Braun-Blanquet. Plant Sociology: The Study of Plant Communities. McGraw-Hill Book Company, New York, 1932.
    \n" ] } ], From fb389660da3e786d790a4709e1f66dff02f21811 Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 15:16:40 +0430 Subject: [PATCH 06/11] doc : minor edit in Document #349 --- Document/Document.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/Document/Document.ipynb b/Document/Document.ipynb index 52f82012..d84d1b77 100644 --- a/Document/Document.ipynb +++ b/Document/Document.ipynb @@ -125,7 +125,7 @@ "
  • Adjusted G-Mean
    • \n", "
  • Adjusted F-Score
    • \n", "
  • Overlap Coefficient
    • \n", - "
  • Braun-Blanquet Coefficient
    • \n", + "
  • Braun-Blanquet Similarity
    • \n", "
  • Otsuka Ochiai Coefficient
    • \n", "
  • Tversky Index
    • \n", "
  • Area Under The PR Curve
    • \n", @@ -6157,7 +6157,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### BB (Braun-Blanquet coefficient)" + "### BB (Braun-Blanquet similarity)" ] }, { From f568f28c335fde9c96125cb76bfb0a873f41f6bb Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 15:17:17 +0430 Subject: [PATCH 07/11] fix : autopep8 --- pycm/pycm_class_func.py | 1 + pycm/pycm_handler.py | 1 + pycm/pycm_param.py | 11 ++++++++++- 3 files changed, 12 insertions(+), 1 deletion(-) diff --git a/pycm/pycm_class_func.py b/pycm/pycm_class_func.py index 0099c2ad..a1f59e8d 100644 --- a/pycm/pycm_class_func.py +++ b/pycm/pycm_class_func.py @@ -104,6 +104,7 @@ def OC_calc(TP, TOP, P): except (ZeroDivisionError, TypeError): return "None" + def BB_calc(TP, TOP, P): """ Calculate Braun-Blanquet similarity (BB). diff --git a/pycm/pycm_handler.py b/pycm/pycm_handler.py index 6986fd2b..7736731f 100644 --- a/pycm/pycm_handler.py +++ b/pycm/pycm_handler.py @@ -79,6 +79,7 @@ def __class_stat_init__(cm): cm.HD = cm.class_stat["HD"] cm.BB = cm.class_stat["BB"] + def __overall_stat_init__(cm): """ Init individual overall stats. diff --git a/pycm/pycm_param.py b/pycm/pycm_param.py index dc9b2374..b781f80a 100644 --- a/pycm/pycm_param.py +++ b/pycm/pycm_param.py @@ -587,7 +587,16 @@ "HD": "HD-(Hamming-distance)", "BB": "BB-(Braun-Blanquet-similarity)"} -CAPITALIZE_FILTER = ["BCD", "AUCI", "Q", "AGF", "OOC", "AUPR", "AUC", "QI", "BB"] +CAPITALIZE_FILTER = [ + "BCD", + "AUCI", + "Q", + "AGF", + "OOC", + "AUPR", + "AUC", + "QI", + "BB"] BENCHMARK_COLOR = { "PLRI": { From b28451d4fdb27974e96baae4c91da260f895bbce Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 15:18:00 +0430 Subject: [PATCH 08/11] doc : CHANGELOG updated --- CHANGELOG.md | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index acc27df2..92f2ff98 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0. ## [Unreleased] ### Added - Hamming distance +- Braun-Blanquet similarity ### Changed - `classes` parameter added to `matrix_params_from_table` function - Matrices with `numpy.integer` elements are now accepted From 8169ff303578c7b935a8d39bbebdbab2782e4199 Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 15:23:52 +0430 Subject: [PATCH 09/11] doc : new reference added --- Document/Document.ipynb | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/Document/Document.ipynb b/Document/Document.ipynb index d84d1b77..8f60bde2 100644 --- a/Document/Document.ipynb +++ b/Document/Document.ipynb @@ -6164,7 +6164,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The Braun-Blanquet coefficient is a similarity measure that is mostly used in botany. It is defined as the size of the intersection divided by the larger of the size of the two sets [[82]](#ref82)." + "The Braun-Blanquet coefficient is a similarity measure that is mostly used in botany. It is defined as the size of the intersection divided by the larger of the size of the two sets [[82]](#ref82) [[83]](#ref83)." ] }, { @@ -14071,7 +14071,9 @@ "\n", "
    81- S. S. Choi, S. H. Cha, and C. C. Tappert, \"A survey of binary similarity and distance measures,\" Journal of systemics, cybernetics and informatics, vol. 8, no. 1, pp. 43-48, 2010.
    \n", "\n", - "
    82- Josias Braun-Blanquet. Plant Sociology: The Study of Plant Communities. McGraw-Hill Book Company, New York, 1932.
    \n" + "
    82- Josias Braun-Blanquet. Plant Sociology: The Study of Plant Communities. McGraw-Hill Book Company, New York, 1932.
    \n", + "\n", + "
    83- Little, Christopher C. (2020). Abydos NLP/IR library for Python (v0.4.1). Zenodo. https://doi.org/10.5281/zenodo.3603514
    \n" ] } ], From 36a4460ffe65c81f05637251802c3e0cae2cdb73 Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 17:21:59 +0430 Subject: [PATCH 10/11] doc : references format updated --- Document/Document.ipynb | 4 ++-- README.md | 4 ++++ 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/Document/Document.ipynb b/Document/Document.ipynb index 8f60bde2..f95ff7a8 100644 --- a/Document/Document.ipynb +++ b/Document/Document.ipynb @@ -14071,9 +14071,9 @@ "\n", "
    81- S. S. Choi, S. H. Cha, and C. C. Tappert, \"A survey of binary similarity and distance measures,\" Journal of systemics, cybernetics and informatics, vol. 8, no. 1, pp. 43-48, 2010.
    \n", "\n", - "
    82- Josias Braun-Blanquet. Plant Sociology: The Study of Plant Communities. McGraw-Hill Book Company, New York, 1932.
    \n", + "
    82- J. Braun-Blanquet, \"Plant sociology. The study of plant communities,\" Plant sociology. The study of plant communities. First ed., 1932.
    \n", "\n", - "
    83- Little, Christopher C. (2020). Abydos NLP/IR library for Python (v0.4.1). Zenodo. https://doi.org/10.5281/zenodo.3603514
    \n" + "
    83- C. C. Little, \"Abydos Documentation,\" 2018.
    \n" ] } ], diff --git a/README.md b/README.md index b85ba3a9..6b9338ec 100644 --- a/README.md +++ b/README.md @@ -932,6 +932,10 @@ PyCM can be used online in interactive Jupyter Notebooks via the Binder or Colab
    81- S. S. Choi, S. H. Cha, and C. C. Tappert, "A survey of binary similarity and distance measures," Journal of systemics, cybernetics and informatics, vol. 8, no. 1, pp. 43-48, 2010.
    +
    82- J. Braun-Blanquet, "Plant sociology. The study of plant communities," Plant sociology. The study of plant communities. First ed., 1932.
    + +
    83- C. C. Little, "Abydos Documentation," 2018.
    + ## Cite From 26298b84b0ad735bf33a37b5b7cc01bd61ca4709 Mon Sep 17 00:00:00 2001 From: sepandhaghighi Date: Wed, 10 Aug 2022 17:46:04 +0430 Subject: [PATCH 11/11] doc : minor edit in BB reference #444 --- Document/Document.ipynb | 2 +- README.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/Document/Document.ipynb b/Document/Document.ipynb index f95ff7a8..3d546f90 100644 --- a/Document/Document.ipynb +++ b/Document/Document.ipynb @@ -14073,7 +14073,7 @@ "\n", "
    82- J. Braun-Blanquet, \"Plant sociology. The study of plant communities,\" Plant sociology. The study of plant communities. First ed., 1932.
    \n", "\n", - "
    83- C. C. Little, \"Abydos Documentation,\" 2018.
    \n" + "
    83- C. C. Little, \"Abydos Documentation,\" 2020.
    \n" ] } ], diff --git a/README.md b/README.md index 6b9338ec..fb2a364e 100644 --- a/README.md +++ b/README.md @@ -934,7 +934,7 @@ PyCM can be used online in interactive Jupyter Notebooks via the Binder or Colab
    82- J. Braun-Blanquet, "Plant sociology. The study of plant communities," Plant sociology. The study of plant communities. First ed., 1932.
    -
    83- C. C. Little, "Abydos Documentation," 2018.
    +
    83- C. C. Little, "Abydos Documentation," 2020.
    ## Cite