!58 support resampling buckets

Merge pull request !58 from wenkai/wk0422

mindinsight/datavisual/data_transform/histogram_container.py

@@ -16,6 +16,8 @@
 import math
 
 from mindinsight.datavisual.proto_files.mindinsight_summary_pb2 import Summary
+from mindinsight.utils.exceptions import ParamValueError
+from mindinsight.datavisual.utils.utils import calc_histogram_bins
 
 
 def _mask_invalid_number(num):
@@ -26,6 +28,49 @@ def _mask_invalid_number(num):
     return num
 
 
+class Bucket:
+    """
+    Bucket data class.
+
+    Args:
+        left (double): Left edge of the histogram bucket.
+        width (double): Width of the histogram bucket.
+        count (int): Count of numbers fallen in the histogram bucket.
+    """
+    def __init__(self, left, width, count):
+        self._left = left
+        self._width = width
+        self._count = count
+
+    @property
+    def left(self):
+        """Gets left edge of the histogram bucket."""
+        return self._left
+
+    @property
+    def count(self):
+        """Gets count of numbers fallen in the histogram bucket."""
+        return self._count
+
+    @property
+    def width(self):
+        """Gets width of the histogram bucket."""
+        return self._width
+
+    @property
+    def right(self):
+        """Gets right edge of the histogram bucket."""
+        return self._left + self._width
+
+    def as_tuple(self):
+        """Gets the bucket as tuple."""
+        return self._left, self._width, self._count
+
+    def __repr__(self):
+        """Returns repr(self)."""
+        return "Bucket(left={}, width={}, count={})".format(self._left, self._width, self._count)
+
+
 class HistogramContainer:
     """
     Histogram data container.
@@ -35,16 +80,19 @@ class HistogramContainer:
     """
     def __init__(self, histogram_message: Summary.Histogram):
         self._msg = histogram_message
-        self._original_buckets = tuple((bucket.left, bucket.width, bucket.count) for bucket in self._msg.buckets)
+        original_buckets = [Bucket(bucket.left, bucket.width, bucket.count) for bucket in self._msg.buckets]
+        # Ensure buckets are sorted from min to max.
+        original_buckets.sort(key=lambda bucket: bucket.left)
+        self._original_buckets = tuple(original_buckets)
+        self._count = sum(bucket.count for bucket in self._original_buckets)
         self._max = _mask_invalid_number(histogram_message.max)
         self._min = _mask_invalid_number(histogram_message.min)
         self._visual_max = self._max
         self._visual_min = self._min
         # default bin number
-        self._visual_bins = 10
-        self._count = sum(bucket[2] for bucket in self._original_buckets)
+        self._visual_bins = calc_histogram_bins(self._count)
         # Note that tuple is immutable, so sharing tuple is often safe.
-        self._re_sampled_buckets = self._original_buckets
+        self._re_sampled_buckets = ()
 
     @property
     def max(self):
@@ -63,7 +111,7 @@ class HistogramContainer:
 
     @property
     def original_msg(self):
-        """Get original proto message"""
+        """Gets original proto message."""
         return self._msg
 
     def set_visual_range(self, max_val: float, min_val: float, bins: int) -> None:
@@ -77,6 +125,13 @@ class HistogramContainer:
             min_val (float): Min value for visual histogram.
             bins (int): Bins number for visual histogram.
         """
+        if max_val < min_val:
+            raise ParamValueError(
+                "Invalid input. max_val({}) is less or equal than min_val({}).".format(max_val, min_val))
+
+        if bins < 1:
+            raise ParamValueError("Invalid input bins({}). Must be greater than 0.".format(bins))
+
         self._visual_max = max_val
         self._visual_min = min_val
         self._visual_bins = bins
@@ -84,15 +139,104 @@ class HistogramContainer:
         # mark _re_sampled_buckets to empty
         self._re_sampled_buckets = ()
 
-    def _re_sample_buckets(self):
-        # Will call re-sample logic in later PR.
-        self._re_sampled_buckets = self._original_buckets
+    def _calc_intersection_len(self, max1, min1, max2, min2):
+        """Calculates intersection length of [min1, max1] and [min2, max2]."""
+        if max1 < min1:
+            raise ParamValueError(
+                "Invalid input. max1({}) is less than min1({}).".format(max1, min1))
+
+        if max2 < min2:
+            raise ParamValueError(
+                "Invalid input. max2({}) is less than min2({}).".format(max2, min2))
+
+        if min1 <= min2:
+            if max1 <= min2:
+                # return value must be calculated by max1.__sub__
+                return max1 - max1
+            if max1 <= max2:
+                return max1 - min2
+            # max1 > max2
+            return max2 - min2
+
+        # min1 > min2
+        if max2 <= min1:
+            return max2 - max2
+        if max2 <= max1:
+            return max2 - min1
+        return max1 - min1
 
-    def buckets(self):
+    def _re_sample_buckets(self):
+        """Re-samples buckets according to visual_max, visual_min and visual_bins."""
+        if self._visual_max == self._visual_min:
+            # Adjust visual range if max equals min.
+            self._visual_max += 0.5
+            self._visual_min -= 0.5
+
+        width = (self._visual_max - self._visual_min) / self._visual_bins
+
+        if not self.count:
+            self._re_sampled_buckets = tuple(
+                Bucket(self._visual_min + width * i, width, 0)
+                for i in range(self._visual_bins))
+            return
+
+        re_sampled = []
+        original_pos = 0
+        original_bucket = self._original_buckets[original_pos]
+        for i in range(self._visual_bins):
+            cur_left = self._visual_min + width * i
+            cur_right = cur_left + width
+            cur_estimated_count = 0.0
+
+            # Skip no bucket range.
+            if cur_right <= original_bucket.left:
+                re_sampled.append(Bucket(cur_left, width, math.ceil(cur_estimated_count)))
+                continue
+
+            # Skip no intersect range.
+            while cur_left >= original_bucket.right:
+                original_pos += 1
+                if original_pos >= len(self._original_buckets):
+                    break
+                original_bucket = self._original_buckets[original_pos]
+
+            # entering with this condition: cur_right > original_bucket.left and cur_left < original_bucket.right
+            while True:
+                if original_pos >= len(self._original_buckets):
+                    break
+                original_bucket = self._original_buckets[original_pos]
+
+                intersection = self._calc_intersection_len(
+                    min1=cur_left, max1=cur_right,
+                    min2=original_bucket.left, max2=original_bucket.right)
+                estimated_count = (intersection / original_bucket.width) * original_bucket.count
+
+                cur_estimated_count += estimated_count
+                if cur_right > original_bucket.right:
+                    # Need to sample next original bucket to this visual bucket.
+                    original_pos += 1
+                else:
+                    # Current visual bucket has taken all intersect buckets into account.
+                    break
+
+            re_sampled.append(Bucket(cur_left, width, math.ceil(cur_estimated_count)))
+
+        self._re_sampled_buckets = tuple(re_sampled)
+
+    def buckets(self, convert_to_tuple=True):
         """
         Get visual buckets instead of original buckets.
+
+        Args:
+            convert_to_tuple (bool): Whether convert bucket object to tuple.
+
+        Returns:
+            tuple, contains buckets.
         """
         if not self._re_sampled_buckets:
             self._re_sample_buckets()
 
+        if not convert_to_tuple:
             return self._re_sampled_buckets
+
+        return tuple(bucket.as_tuple() for bucket in self._re_sampled_buckets)

mindinsight/datavisual/data_transform/reservoir.py

@@ -16,10 +16,11 @@
 
 import random
 import threading
-import math
 
+from mindinsight.datavisual.common.log import logger
 from mindinsight.datavisual.common.enums import PluginNameEnum
 from mindinsight.utils.exceptions import ParamValueError
+from mindinsight.datavisual.utils.utils import calc_histogram_bins
 
 
 class Reservoir:
@@ -173,39 +174,20 @@ class HistogramReservoir(Reservoir):
                 max_count = max(histogram.count, max_count)
                 visual_range.update(histogram.max, histogram.min)
 
-            bins = self._calc_bins(max_count)
+            bins = calc_histogram_bins(max_count)
 
             # update visual range
+            logger.info("Visual histogram: min %s, max %s, bins %s, max_count %s.",
+                        visual_range.min,
+                        visual_range.max,
+                        bins,
+                        max_count)
             for sample in self._samples:
                 histogram = sample.value
                 histogram.set_visual_range(visual_range.max, visual_range.min, bins)
 
             return list(self._samples)
 
-    def _calc_bins(self, count):
-        """
-        Calculates experience-based optimal bins number.
-
-        To suppress re-sample bias, there should be enough number in each bin. So we calc bin numbers according to
-        count. For very small count(1 - 10), we assign carefully chosen number. For large count, we tried to make
-        sure there are 9-10 numbers in each bucket on average. Too many bins will also distract users, so we set max
-        number of bins to 30.
-        """
-        number_per_bucket = 10
-        max_bins = 30
-
-        if not count:
-            return 1
-        if count <= 5:
-            return 2
-        if count <= 10:
-            return 3
-        if count <= 280:
-            # note that math.ceil(281/10) + 1 = 30
-            return math.ceil(count / number_per_bucket) + 1
-
-        return max_bins
-
 
 class ReservoirFactory:
     """Factory class to get reservoir instances."""

mindinsight/datavisual/utils/utils.py

+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+"""Utils."""
+import math
+
+
+def calc_histogram_bins(count):
+    """
+    Calculates experience-based optimal bins number for histogram.
+
+    To suppress re-sample bias, there should be enough number in each bin. So we calc bin numbers according to
+    count. For very small count(1 - 10), we assign carefully chosen number. For large count, we tried to make
+    sure there are 9-10 numbers in each bucket on average. Too many bins will also distract users, so we set max
+    number of bins to 30.
+
+    Args:
+        count (int): Valid number count for the tensor.
+
+    Returns:
+        int, number of histogram bins.
+    """
+    number_per_bucket = 10
+    max_bins = 30
+
+    if not count:
+        return 1
+    if count <= 5:
+        return 2
+    if count <= 10:
+        return 3
+    if count <= 280:
+        # note that math.ceil(281/10) + 1 equals 30
+        return math.ceil(count / number_per_bucket) + 1
+
+    return max_bins

tests/ut/datavisual/data_transform/test_histogram_container.py

@@ -20,8 +20,9 @@ from mindinsight.datavisual.data_transform import histogram_container as hist
 
 class TestHistogram:
     """Test histogram."""
+
     def test_get_buckets(self):
-        """Test get buckets."""
+        """Tests get buckets."""
         mocked_input = mock.MagicMock()
         mocked_bucket = mock.MagicMock()
         mocked_bucket.left = 0
@@ -31,4 +32,54 @@ class TestHistogram:
         histogram = hist.HistogramContainer(mocked_input)
         histogram.set_visual_range(max_val=1, min_val=0, bins=1)
         buckets = histogram.buckets()
-        assert len(buckets) == 1
\ No newline at end of file
+        assert buckets == ((0.0, 1.0, 1),)
+
+    def test_re_sample_buckets_split_original(self):
+        """Tests splitting original buckets when re-sampling."""
+        mocked_input = mock.MagicMock()
+        mocked_bucket = mock.MagicMock()
+        mocked_bucket.left = 0
+        mocked_bucket.width = 1
+        mocked_bucket.count = 1
+        mocked_input.buckets = [mocked_bucket]
+        histogram = hist.HistogramContainer(mocked_input)
+        histogram.set_visual_range(max_val=1, min_val=0, bins=3)
+        buckets = histogram.buckets()
+        assert buckets == ((0.0, 0.3333333333333333, 1), (0.3333333333333333, 0.3333333333333333, 1),
+                           (0.6666666666666666, 0.3333333333333333, 1))
+
+    def test_re_sample_buckets_zero_bucket(self):
+        """Tests zero bucket when re-sampling."""
+        mocked_input = mock.MagicMock()
+        mocked_bucket = mock.MagicMock()
+        mocked_bucket.left = 0
+        mocked_bucket.width = 1
+        mocked_bucket.count = 1
+        mocked_bucket2 = mock.MagicMock()
+        mocked_bucket2.left = 1
+        mocked_bucket2.width = 1
+        mocked_bucket2.count = 2
+        mocked_input.buckets = [mocked_bucket, mocked_bucket2]
+        histogram = hist.HistogramContainer(mocked_input)
+        histogram.set_visual_range(max_val=3, min_val=-1, bins=4)
+        buckets = histogram.buckets()
+        assert buckets == ((-1.0, 1.0, 0), (0.0, 1.0, 1), (1.0, 1.0, 2), (2.0, 1.0, 0))
+
+    def test_re_sample_buckets_merge_bucket(self):
+        """Tests merging counts from two buckets when re-sampling."""
+        mocked_input = mock.MagicMock()
+        mocked_bucket = mock.MagicMock()
+        mocked_bucket.left = 0
+        mocked_bucket.width = 1
+        mocked_bucket.count = 1
+        mocked_bucket2 = mock.MagicMock()
+        mocked_bucket2.left = 1
+        mocked_bucket2.width = 1
+        mocked_bucket2.count = 10
+        mocked_input.buckets = [mocked_bucket, mocked_bucket2]
+        histogram = hist.HistogramContainer(mocked_input)
+        histogram.set_visual_range(max_val=3, min_val=-1, bins=5)
+        buckets = histogram.buckets()
+        assert buckets == (
+            (-1.0, 0.8, 0), (-0.19999999999999996, 0.8, 1), (0.6000000000000001, 0.8, 5), (1.4000000000000004, 0.8, 6),
+            (2.2, 0.8, 0))