* (The inverse of this will be a horizontal transformation.)
   */
  public static LinearTransformation vertical(double x) {
    checkArgument(isFinite(x));
    return new VerticalLinearTransformation(x);
  }

  /**
   * Builds an instance representing a horizontal transformation with a constant value of {@code y}.

    double y = 1.2;
    LinearTransformation transformation = LinearTransformation.horizontal(y);
    assertHorizontalLinearTransformation(transformation, y);
  }

  public void testHorizontal_infiniteY() {
    assertThrows(
        IllegalArgumentException.class,
        () -> LinearTransformation.horizontal(Double.POSITIVE_INFINITY));
  }

  public void testHorizontal_nanY() {

    double y = 1.2;
    LinearTransformation transformation = LinearTransformation.horizontal(y);
    assertHorizontalLinearTransformation(transformation, y);
  }

  public void testHorizontal_infiniteY() {
    assertThrows(
        IllegalArgumentException.class,
        () -> LinearTransformation.horizontal(Double.POSITIVE_INFINITY));
  }

  public void testHorizontal_nanY() {

            stats.xStats().populationVariance(),
            stats.populationCovariance());
      }
    }
    assertHorizontalLinearTransformation(
        HORIZONTAL_VALUES_PAIRED_STATS.leastSquaresFit(),
        HORIZONTAL_VALUES_PAIRED_STATS.yStats().mean());
    assertVerticalLinearTransformation(
        VERTICAL_VALUES_PAIRED_STATS.leastSquaresFit(),
        VERTICAL_VALUES_PAIRED_STATS.xStats().mean());

            stats.xStats().populationVariance(),
            stats.populationCovariance());
      }
    }
    assertHorizontalLinearTransformation(
        HORIZONTAL_VALUES_PAIRED_STATS.leastSquaresFit(),
        HORIZONTAL_VALUES_PAIRED_STATS.yStats().mean());
    assertVerticalLinearTransformation(
        VERTICAL_VALUES_PAIRED_STATS.leastSquaresFit(),
        VERTICAL_VALUES_PAIRED_STATS.xStats().mean());

    checkArgument(xDelta != 0.0);
    checkArgument(yDelta != 0.0);
    assertThat(transformation.isHorizontal()).isFalse();
    assertThat(transformation.isVertical()).isFalse();
    assertThat(transformation.inverse().isHorizontal()).isFalse();
    assertThat(transformation.inverse().isVertical()).isFalse();
    assertThat(transformation.transform(x1)).isWithin(ALLOWED_ERROR).of(y1);

    checkArgument(xDelta != 0.0);
    checkArgument(yDelta != 0.0);
    assertThat(transformation.isHorizontal()).isFalse();
    assertThat(transformation.isVertical()).isFalse();
    assertThat(transformation.inverse().isHorizontal()).isFalse();
    assertThat(transformation.inverse().isVertical()).isFalse();
    assertThat(transformation.transform(x1)).isWithin(ALLOWED_ERROR).of(y1);

   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code
   * xStats().populationVariance() > 0.0 || yStats().populationVariance() > 0.0}). The result is
   * guaranteed to be horizontal if there is variance in the {@code x} data but not the {@code y}
   * data, and vertical if there is variance in the {@code y} data but not the {@code x} data.
   *

      },
      "id": 20,
      "links": [],
      "maxDataPoints": 100,
      "options": {
        "colorMode": "none",
        "graphMode": "area",
        "justifyMode": "auto",
        "orientation": "horizontal",
        "reduceOptions": {
          "calcs": [
            "mean"
          ],
          "fields": "",
          "values": false
        },
        "textMode": "auto"
      },

}

// list of horizontal pod autoscaler objects.
message HorizontalPodAutoscalerList {
  // Standard list metadata.
  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.ListMeta metadata = 1;

  // items is the list of horizontal pod autoscaler objects.
  repeated HorizontalPodAutoscaler items = 2;
}

// specification of a horizontal pod autoscaler.
message HorizontalPodAutoscalerSpec {