The Analysis Menu
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## The Analysis Menu

The commands which are available in this menu are not the same is a table or a plot is selected.

### Commands for the analysis of data in tables

Statistics on Columns

  Creates a new table providing basic statistical information about the selected columns in the active table: average, variance, standard deviation, max value, etc...

  You can select several columns in one table, one line will be created for each column. You can't select columns in different tables to obtain one single table of statistics.

Statistics on Rows

  Creates a new table providing basic statistical information about the selected rows in the active table: average, variance, standard deviation, max value, etc...

  See the Statistics on Columns command command for more details.

Sort Column

  Sort the columns selected. If more than one column is selected, you can sort them:

  - separately: each column will be sorted in ascending or descending order

  - together: the column selected as leading column will be sorted in ascending or descending order, and the others column selected will be sorted in order to keep the rows unchanged.

Sort Table

  This is the same command as Sort Column but it operate on all columns of the active table.

Normalize

  Normalize the columns selected, that is modify the data in order to obtain a range of 0 to 1. All columns selected are normalized separately. This command doesn't create new normalized columns but replace the values of the selected columns.

  Normalize -> Column

    Normalize the selected column.

  Normalize -> Table

    Normalize all the columns of the table, it is not a global normalization of all values of the table: each column is normalized separately.

FFT...

  Compute a direct or inverse Fast Fourier Transform. The parameters used can be set with the FFT dialog. See the fft section of the Analysis chapter for more details.

Correlate

  Do a croos-correlation of the two columns which are selected. See the correlate section of the Analysis chapter for more details.

Convolute

  Do a convolution of the two columns which are selected. The first one being the response and the second the signal. See the convolution section of the Analysis chapter for more details.

Deconvolute

  Do a deconvolution of the two columns which are selected. The first one being the response and the second the signal. See the deconvolution section of the Analysis chapter for more details.

Non Linear Curve Fit... (Ctrl-Y)

  Opens the Non-linear Fit dialog, allowing you to choose the curve to fit, the algorithm and the tolerance, the number of iterations to be performed, and to type the analytical function to use, the names of the fitting parameters and their initial guessed values. See the Non Linear Curve Fit section of the Analysis chapter for more details.

### Commands for the analysis of curves in plots

The following items are enabled only if the active window is a 2D Multilayer Plot Window. If the active plot layer contains more than one curve, and the Data Range Selectors are not enabled, a dialog window will pop-out allowing you to select the curve you want to analyse.

In most of the cases (except for integration), a new red curve is added to the active plot layer and a a new table containing the data used to plot this curve is added to the workspace. Useful information about the operation performed will be showed in the Results Log display.

The commands FFT... and Non Linear Curve Fit... are presented in the Table Analysis Menu.

Analysis -> Differentiate

  Creates a new plot displaying the resulting curve of the numerical differentiation. The computation of the derivative is done by centered finite diferences.

Analysis -> Integrate...

  Opens the Integration dialog, allowing you to choose the curve to integrate and the integration method.

Analysis -> Smooth

  Savitski-Golay

  Moving Window Average...

    This command perform a smoothing of the selected curve with the moving window average method. The formula used to smooth the curve defined by the points yi=f(xi) is:

    The greater is n, the smoother the resulting curve zi=f(xi) is. The dialog allows to specify the curve which will be smoothed, the value of n and the color used to draw the smoothed curved. A new table will be created to store the data points xi, zi.

    Figure 3.1. The Smooth -> Moving Window Average dialog.

  FFT Filter

Analysis -> FFT Filter

  Low Pass...

  High Pass...

  Band Pass...

  Band Block...

Analysis -> Interpolate...

  Performs an interpolation. The curve must have enough data points to compute the interpolated points, if not a warning message will be prompted out.

  The methods available to perform the interpolation are Linear (the curve must contain at least 3 points), Cubic Spline (the curve you analyse must contain at least 4 points, if not a warning message will be prompted out, Non-rounded Akime spline (the curve you analyse must contain at least 5 points).

Analysis -> FFT...

  Performs a forward or inverse FFT transform of the selected curve.

  The inverse FFT transform of a forward transform will result in a data set identical to that used for the forward transform.

Analysis -> Fit Linear

  Performs a linear fit of the selected curve.

Analysis -> Fit Polynomial...

  Opens the Polynomial Fit dialog, allowing you to choose the curve to fit, the order of the polynomial function to use, the number of points of the resulting curve and the abscissae limits for the fit.

Analysis -> Fit Exponential Decay

  First Order...

    Opens the Exponential Fit dialog, allowing you to choose the curve to fit and the initial guesses for the fit parameters.

  Second Order...

    Opens a dialog, allowing you to choose the curve to fit and the initial guesses for the fit parameters.

  Third Order...

    Opens a dialog, allowing you to choose the curve to fit and the initial guesses for the fit parameters.

Analysis -> Fit Exponential Growth...

  Performs an exponential growth fit of the selected curve.

Analysis -> Fit Lorentzian

  Performs a lorentzian fit of the selected curve. It can be used to obtain a correlation equation of a bell shaped data set.

Analysis -> Fit Gaussian

  Performs a gaussian fit of the selected curve.It can be used to obtain a correlation equation of a bell shaped data set.

Analysis -> Fit Bolzmann (sigmoidal)

  Performs a fit to a bolzmann function of the selected curve. It can be used to obtain a correlation equation of a S shaped data set.

Analysis -> Fit Multi-peak -->Gaussian

  Performs a fit to a sum of N gaussian function of the selected curve.

Analysis -> Fit Multi-peak - Lorentzian

  Performs a fit to a sum of N lorentz function of the selected curve.

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