DataPoint

A DataPoint represents an highlighted point on a plotted curve. It is subordered to that curve and strictly bound to its fate. If the curve is deleted, the DataPoint gets deleted also. If some aspect of the curve change, like the x or y dataset or axis, the DataPoint is adjusted accordingly.

Creating a DataPoint

There are two methods of placing a new DataPoint on a curve:

  1. Activate the picker tool and click on a curve. A new DataPoint will be created, associated to the curve you clicked onto, and as near as possible to the coordinates where your click happened.
  2. Select the curve in the Misura™ Navigator, then right click on its node and select the Intercept action. A plugin window will allow to customize the location where the DataPoint will appear and some additional settings.

Positioning

Once created, a DataPoint can be positioned by dragging and dropping it along its curve (it will never jump to another curve).

Its exact positioning, once dropped, can follow different algorithms, which makes it a powerful analytical tools. For example, a DataPoint can search for the nearest maximum, minimum or inflection point in the target curve.

Placement options can be configured before creating a datapoint according to method (2) above (Intercept from Misura™ Navigator) by setting the Place nearest field. Once the DataPoint has been created with either method, placement algorithm can be modified from the Place nearest setting found in the Properties panel.

  1. Nearest (fixed X): the default method will consider the X coordinate of your click, and place the DataPoint the nearest possible to that value, without considering the Y coordinate.
  2. Nearest: as above, but will consider also the Y coordinate. Use this method when there is a non-univocal curve (multiple Y for the same X).
  3. Maximum: search the nearest maximum value
  4. Minimum: as above, looking for the minimum
  5. Inflection: search the nearest point where the second derivative is zero
  6. Stationary: as above, but use the first derivative

Inflection and Stationary methods will need an addtional X dataset in order to calculate the derivatives. The DataPoint is initialized with the same X dataset of the parent curve, but that can be changed in the Critical search X dataset setting.

The surrounding portion of the curve, in which the automatic positioning will occur, is defined by Critical search range option. It is expressed as the number of points around the current position of the DataPoint where to search according to the selected method. This allows a precise local search of the desired morphological feature of the curve.

Labels

DataPoint creates a subordered label listing the Y value, temperature and time of the point. The label can be deleted by setting Show label to False under the Formatting panel of the DataPoint.

The label can be customized in Output label text folling Python replacement rules. Available substitutions are:

  • y: y value (%(y).1f will output 1.2 if y is 1.234)
  • x: x value, as above
  • ylabel: the label of the y axis, use the string formatter: %(ylabel)s
  • xlabel: x axis label, as above
  • t: time value
  • T: temperature value

For example:

Intercept\\%(ylabel)s=%(y).1E\\T=%(T).1f\\t=%(t)i

Will render as:

Intercept
Vol (%)=5.1E
T=840.1
t=2800

Lines

The Formatting panel offers three kinds of subordered lines:

  1. Show tangent line: a line tangent to the curve will be added
  2. Show perpendicular line: a line perpendicular to the curve will be added
  3. Second Data Point: specify a second DataPoint: a line will be drawn which passes through both the current DataPoint and that second DataPoint.

After one of these option is activated, it might be necessary to move the DataPoint on the plot for the related lines to show up. Alternatively, you can click the Update Data Point button a few times.

Remove Gaps

A DataPoint can also be placed on curve defects, like sudden jumps, in order to remove them by clicking on the Remove Gaps button. The curve will be smoothed around the datapoint, removing sudden jumps. You can use the Undo button to revert its operation.

Gaps removal algorithm reads two DataPoint settings which can be properly configured to obtain the desired output:

  1. Remove gaps range: Number of points surrounding the DataPoint that will be scanned for jump removal.
  2. Remove gaps threshold: A limit above which the distance between two points is considered a jump that should be removed.

The threshold is automatically configured according to the range and the selected surrounding, so that any point above the mean scattering should be flattened out.