Merge branch 'master' of github.com:fastnlp/fastNLP

fastNLP/core/metrics.py

@@ -313,6 +313,7 @@ class ConfusionMatrixMetric(MetricBase):
                  pred=None,
                  target=None,
                  seq_len=None,
+                 show_result=None,
                  print_ratio=False
                 ):
         r"""
@@ -326,6 +327,7 @@ class ConfusionMatrixMetric(MetricBase):
         super().__init__()
         self._init_param_map(pred=pred, target=target, seq_len=seq_len)
         self.confusion_matrix = ConfusionMatrix(
+            show_result=show_result,
             vocab=vocab,
             print_ratio=print_ratio,
         )

fastNLP/core/utils.py

@@ -36,8 +36,9 @@ _CheckRes = namedtuple('_CheckRes', ['missing', 'unused', 'duplicated', 'require
 
 class ConfusionMatrix:
     r"""a dict can provide Confusion Matrix"""
-    def __init__(self, vocab=None, print_ratio=False):
+    def __init__(self, show_result=None,vocab=None, print_ratio=False):
         r"""
+        :param show_result: list type, 数据类型需要和target保持一致
         :param vocab: 需要有to_word方法，建议直接使用Fastnlp.core.Vocabulary。
         :param print_ratio: 限制print的输出，False只输出数量Confusion Matrix, True还会输出百分比Confusion Matrix, 分别为行/列
         """
@@ -48,6 +49,7 @@ class ConfusionMatrix:
         self.confusiondict = {}  # key: pred index, value:target word ocunt
         self.predcount = {}  # key:pred index, value:count
         self.targetcount = {}  # key:target index, value:count
+        self.show_result = show_result
         self.vocab = vocab
         self.print_ratio = print_ratio
 
@@ -153,16 +155,16 @@ class ConfusionMatrix:
                 set(self.targetcount.keys()).union(set(
                     self.predcount.keys()))))
         lenth = len(totallabel)
-        # namedict key :idx value:word/idx
+        # namedict key :label idx value: str label name/label idx
         namedict = dict([
             (k, str(k if self.vocab == None else self.vocab.to_word(k)))
             for k in totallabel
         ])
-        for label, idx in zip(totallabel, range(lenth)):
+        for label, lineidx in zip(totallabel, range(lenth)):
             idx2row[
-                label] = idx  # 建立一个临时字典，key:vocab的index, value: 行列index  1,3,5...->0,1,2,...
+                label] = lineidx  # 建立一个临时字典，key:vocab的index, value: 行列index  1,3,5...->0,1,2,...
             row2idx[
-                idx] = label  # 建立一个临时字典，value:vocab的index, key: 行列index  0,1,2...->1,3,5,...
+                lineidx] = label  # 建立一个临时字典，key: 行列index  0,1,2...->1,3,5,...,value:vocab的index,
         # 这里打印东西
         out = str()
         output = []
@@ -183,6 +185,7 @@ class ConfusionMatrix:
                 for idx in range(len(col_lenths))
             ]
             output.append(l)
+
         tail = ["all"] + [[str(n) + "%", str(n)][flag == "result"]
                           for n in data[-1]]
         col_lenths = [
@@ -190,6 +193,18 @@ class ConfusionMatrix:
             for idx in range(len(col_lenths))
         ]
         output.append(tail)
+
+        if self.show_result:
+            missing_item=[]
+            missing_item = [i for i in self.show_result if i not in idx2row]
+            self.show_result = [i for i in self.show_result if i in idx2row]
+            if missing_item:
+                print(f"Noticing label(s) which is/are not in target list appeared, final output string will not contain{str(missing_item)}")
+            if self.show_result:
+                show_col = [0] + [i + 1 for i in [idx2row[i] for i in self.show_result]]
+                show_row = [0]+[i+2 for i in [idx2row[i] for i in self.show_result]]
+                output = [[row[col] for col in show_col] for row in [output[row] for row in show_row]]
+                output.insert(1,["pred"])
         for line in output:
             for colidx in range(len(line)):
                 out += "%*s" % (col_lenths[colidx], line[colidx]) + "\t"
@@ -217,6 +232,7 @@ class ConfusionMatrix:
         return out
 
 
+
 class Option(dict):
     r"""a dict can treat keys as attributes"""