TensorBoard: Don't render smoothed lines towards end

Change: 146182705

2 files changed, 26 insertions, 20 deletions

diff --git a/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.html b/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.html
index 210aab6c69..0d160795e8 100644
--- a/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.html
+++ b/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.html
@@ -148,12 +148,13 @@ such as different X scales (linear and temporal), tooltips and smoothing.
          *
          * The smoothing algorithm is a simple moving average, which, given a
          * point p and a window w, replaces p with a simple average of the
-         * points in the [p - floor(w/2), p + floor(w/2)] range.
-         * If there aren't enough points to cover the entire window to the left
-         * and to the right, the window is reduced to fit exactly the amount of
-         * elements available. This means that the smoothed line will be less
-         * smoothed at both extremities and gradually become more smooth until
-         * the desired window is reached.
+         * points in the [p - floor(w/2), p + floor(w/2)] range.  If there
+         * aren't enough points to cover the entire window to the left, the
+         * window is reduced to fit exactly the amount of elements available.
+         * This means that the smoothed line will be less in and gradually
+         * become more smooth until the desired window is reached. However when
+         * there aren't enough points on the right, the line stops being
+         * rendered at all.
          */
         smoothingEnabled: {
           type: Boolean,
@@ -162,17 +163,17 @@ such as different X scales (linear and temporal), tooltips and smoothing.
 
         /**
          * Weight (between 0.0 and 1.0) of the smoothing. This weight controls
-         * the window size, and a weight of 1.0 means using the entire length of
-         * each dataset as the window, while a weight of 0.0 means using a
-         * window of 0 (and thus replacing each point with themselves).
+         * the window size, and a weight of 1.0 means using 50% of the entire
+         * dataset as the window, while a weight of 0.0 means using a window of
+         * 0 (and thus replacing each point with themselves).
          *
-         * The growth between 0.0 and 1.0 is not linear though. Because changing
-         * the window from 0% to 30% of the dataset smooths the line a lot more
-         * than changing the window from 70% to 100%, an exponential function is
-         * used instead. This function increases the size of the window slowly
-         * at the beginning and gradually speeds up the growth, but 0.0 still
-         * means a window of 0 and 1.0 still means a window of the dataset's
-         * length.
+         * The growth between 0.0 and 1.0 is not linear though. Because
+         * changing the window from 0% to 30% of the dataset smooths the line a
+         * lot more than changing the window from 70% to 100%, an exponential
+         * function is used instead: http://i.imgur.com/bDrhEZU.png. This
+         * function increases the size of the window slowly at the beginning
+         * and gradually speeds up the growth, but 0.0 still means a window of
+         * 0 and 1.0 still means a window of the dataset's length.
          */
         smoothingWeight: {
           type: Number,
diff --git a/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.ts b/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.ts
index 7bd0507cf9..1be2a8f913 100644
--- a/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.ts
+++ b/tensorflow/tensorboard/components/vz_line_chart/vz-line-chart.ts
@@ -442,12 +442,17 @@ module VZ {
       let kernelRadius = Math.floor(data.length * factor / 2);
 
       data.forEach((d, i) => {
-        let actualKernelRadius = Math.min(kernelRadius, i, data.length - i - 1);
+        let actualKernelRadius = Math.min(kernelRadius, i);
         let start = i - actualKernelRadius;
         let end = i + actualKernelRadius + 1;
-
-        // Only smooth finite numbers.
-        if (!_.isFinite(d.scalar)) {
+        if (end >= data.length) {
+          // In the beginning, it's OK for the smoothing window to be small,
+          // but this is not desirable towards the end. Rather than shrinking
+          // the window, or extrapolating data to fill the gap, we're simply
+          // not going to display the smoothed line towards the end.
+          d.smoothed = Infinity;
+        } else if (!_.isFinite(d.scalar)) {
+          // Only smooth finite numbers.
           d.smoothed = d.scalar;
         } else {
           d.smoothed = d3.mean(