Manual

User Manual:

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Veusz Documentation
Release 3.0

Jeremy Sanders

Jun 09, 2018

CONTENTS

1

2

3

4

Introduction
1.1 Veusz . . . . . . . . . . . . . . . . . . . .
1.2 Installation . . . . . . . . . . . . . . . . .
1.3 Getting started . . . . . . . . . . . . . . .
1.4 Terminology . . . . . . . . . . . . . . . .
1.4.1
Widget . . . . . . . . . . . . . .
1.4.2
Settings: properties and formatting
1.4.3
Datasets . . . . . . . . . . . . . .
1.4.4
Text . . . . . . . . . . . . . . . .
1.4.5
Measurements . . . . . . . . . . .
1.4.6
Color theme . . . . . . . . . . . .
1.4.7
Axis numeric scales . . . . . . . .
1.4.8
Three dimensional (3D) plots . . .
1.5 The main window . . . . . . . . . . . . .
1.6 My first plot . . . . . . . . . . . . . . . .

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3
3
3
3
3
3
6
7
7
8
8
8
9
10
11

Reading data
2.1 Standard text import . . . . . . .
2.1.1
Data types in text import
2.1.2
Descriptors . . . . . . .
2.1.3
Descriptor examples . .
2.2 CSV files . . . . . . . . . . . . .
2.3 HDF5 files . . . . . . . . . . . .
2.3.1
Error bars . . . . . . . .
2.3.2
Slices . . . . . . . . . .
2.3.3
2D data ranges . . . . .
2.3.4
Dates . . . . . . . . . .
2.4 2D text or CSV format . . . . . .
2.5 FITS files . . . . . . . . . . . . .
2.6 Reading other data formats . . . .

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13
13
14
14
15
15
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16
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17
17
18

Manipulating datasets
3.1 Using dataset plugins . . . . . . . . . . .
3.2 Using expressions to create new datasets
3.3 Linking datasets to expressions . . . . .
3.4 Splitting data . . . . . . . . . . . . . . .
3.5 Defining new constants or functions . . .
3.6 Dataset plugins . . . . . . . . . . . . . .

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21
21
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22
22
22
23

Capturing data

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25

i

5

ii

Veusz command line and embedding interface (API)
5.1 Introduction . . . . . . . . . . . . . . . . . . .
5.2 Commands and API . . . . . . . . . . . . . . .
5.2.1
Action . . . . . . . . . . . . . . . . . .
5.2.2
Add . . . . . . . . . . . . . . . . . . .
5.2.3
AddCustom . . . . . . . . . . . . . . .
5.2.4
AddImportPath . . . . . . . . . . . . .
5.2.5
CloneWidget . . . . . . . . . . . . . .
5.2.6
Close . . . . . . . . . . . . . . . . . .
5.2.7
CreateHistogram . . . . . . . . . . . .
5.2.8
DatasetPlugin . . . . . . . . . . . . . .
5.2.9
EnableToolbar . . . . . . . . . . . . . .
5.2.10 Export . . . . . . . . . . . . . . . . . .
5.2.11 FilterDatasets . . . . . . . . . . . . . .
5.2.12 ForceUpdate . . . . . . . . . . . . . .
5.2.13 Get . . . . . . . . . . . . . . . . . . .
5.2.14 GetChildren . . . . . . . . . . . . . . .
5.2.15 GetClick . . . . . . . . . . . . . . . . .
5.2.16 GetColormap . . . . . . . . . . . . . .
5.2.17 GetData . . . . . . . . . . . . . . . . .
5.2.18 GetDataType . . . . . . . . . . . . . .
5.2.19 GetDatasets . . . . . . . . . . . . . . .
5.2.20 GPL . . . . . . . . . . . . . . . . . . .
5.2.21 ImportFile . . . . . . . . . . . . . . . .
5.2.22 ImportFile2D . . . . . . . . . . . . . .
5.2.23 ImportFileCSV . . . . . . . . . . . . .
5.2.24 ImportFileFITS . . . . . . . . . . . . .
5.2.25 ImportFileHDF5 . . . . . . . . . . . .
5.2.26 ImportFileND . . . . . . . . . . . . . .
5.2.27 ImportFilePlugin . . . . . . . . . . . .
5.2.28 ImportFITSFile . . . . . . . . . . . . .
5.2.29 ImportString . . . . . . . . . . . . . .
5.2.30 ImportString2D . . . . . . . . . . . . .
5.2.31 ImportStringND . . . . . . . . . . . . .
5.2.32 IsClosed . . . . . . . . . . . . . . . . .
5.2.33 List . . . . . . . . . . . . . . . . . . .
5.2.34 Load . . . . . . . . . . . . . . . . . . .
5.2.35 MoveToPage . . . . . . . . . . . . . .
5.2.36 ReloadData . . . . . . . . . . . . . . .
5.2.37 Rename . . . . . . . . . . . . . . . . .
5.2.38 Remove . . . . . . . . . . . . . . . . .
5.2.39 ResizeWindow . . . . . . . . . . . . .
5.2.40 Save . . . . . . . . . . . . . . . . . . .
5.2.41 Set . . . . . . . . . . . . . . . . . . . .
5.2.42 SetAntiAliasing . . . . . . . . . . . . .
5.2.43 SetData . . . . . . . . . . . . . . . . .
5.2.44 SetDataExpression . . . . . . . . . . .
5.2.45 SetDataND . . . . . . . . . . . . . . .
5.2.46 SetDataRange . . . . . . . . . . . . . .
5.2.47 SetData2D . . . . . . . . . . . . . . . .
5.2.48 SetData2DExpression . . . . . . . . . .
5.2.49 SetData2DExpressionXYZ . . . . . . .
5.2.50 SetData2DXYFunc . . . . . . . . . . .
5.2.51 SetDataDateTime . . . . . . . . . . . .

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5.3
5.4

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5.2.52 SetDataText . . . . . . . . .
5.2.53 SetToReference . . . . . . .
5.2.54 SetUpdateInterval . . . . . .
5.2.55 SetVerbose . . . . . . . . .
5.2.56 StartSecondView . . . . . .
5.2.57 TagDatasets . . . . . . . . .
5.2.58 To . . . . . . . . . . . . . .
5.2.59 Quit . . . . . . . . . . . . .
5.2.60 WaitForClose . . . . . . . .
5.2.61 Zoom . . . . . . . . . . . .
Security . . . . . . . . . . . . . . . .
Using Veusz from other programs . .
5.4.1
Non-Qt Python programs . .
5.4.2
Older path-based interface .
5.4.3
New-style object interface .
5.4.4
Translating old to new style .

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iii

iv

Veusz Documentation, Release 3.0

Jeremy Sanders
Copyright 2018
This document is licensed under the GNU General Public License, version 2 or greater. Please see the file COPYING
for details, or see http://www.gnu.org/licenses/gpl-2.0.html.
This is the documentation for Veusz. Veusz is a multiplatform scientific plotting package with a graphical user interface.
Contents:

CONTENTS

1

Veusz Documentation, Release 3.0

2

CONTENTS

CHAPTER

ONE

INTRODUCTION

1.1 Veusz
Veusz is a 2D and 3D scientific plotting package. It is designed to be easy to use, easily extensible, but powerful. The
program features a graphical user interface (GUI), which works under Unix/Linux, Windows or Mac OS. It can also
be easily scripted (the saved file formats are similar to Python scripts) or used as module inside Python. Veusz reads
data from a number of different types of data file, it can be manually entered, or constructed from other datasets.
In Veusz the document is built in an object-oriented fashion, where a document is built up by a number of widgets in
a hierarchy. For example, multiple function or xy widgets can be placed inside a graph widget, and many graphs can
be placed in a grid widget. The program also supports a variety of 3D plots, including 3D point and surface plots. The
program produces vector rather than rastered 3D output.
Veusz can be extended by the user easily by adding plugins. Support for different data file types can be added with
import plugins. Dataset plugins automate the manipulation of datasets. Tools plugins automate the manipulation of
the document.

1.2 Installation
Please go to the website of Veusz to learn more about the program. Links to binaries, distribution packages and the
source package can be found in downloads. For source installation, please see the package INSTALL.

1.3 Getting started
Veusz includes a built-in tutorial which starts the first time the program is run. You can rerun it later from the Help
menu. It also includes many examples, to show how certain kinds of plots are produced. For more help and link to a
video tutorial, see help.

1.4 Terminology
Here we define some terminology for future use.

1.4.1 Widget
A document and its graphs are built up from widgets. These widgets can often by placed within each other, depending
on the type of the widget. A widget has children (those widgets placed within it) and its parent. The widgets have

3

Veusz Documentation, Release 3.0

a number of different settings which modify their behaviour. These settings are divided into properties, which affect
what is plotted and how it is plotted. These would include the dataset being plotted or whether an axis is logarithmic.
There are also formatting settings, including the font to be used and the line thickness. In addition they have actions,
which perform some sort of activity on the widget or its children, like “fit” for a fit widget.
As an aside, using the scripting interface, widgets are specified with a “path”, like a file in Unix or Windows. These
can be relative to the current widget (do not start with a slash), or absolute (start with a slash). Examples of paths
include, /page1/graph1/x, x and ..
The widget types include
1. document - representing a complete document. A document can contain pages. In addition it contains a setting
giving the page size for the document.
2. page - representing a page in a document. One or more graphs can be placed on a page, or a grid.
3. graph - defining an actual graph. A graph can be placed on a page or within a grid. Contained within the
graph are its axes and plotters. A graph can be given a background fill and a border if required. It also has a
margin, which specifies how far away from the edge of its parent widget to plot the body of the graph. A graph
can contain several axes, at any position on the plot. In addition a graph can use axes defined in parent widgets,
shared with other graphs. More than one graph can be placed within in a page. The margins can be adjusted so
that they lie within or besides each other.
4. grid - containing one or more graphs. A grid plots graphs in a gridlike fashion. You can specify the number
of rows and columns, and the plots are automatically replotted in the chosen arrangement. A grid can contain
graphs or axes. If an axis is placed in a grid, it can be shared by the graphs in the grid.
5. axis - giving the scale for plotting data. An axis translates the coordinates of the data to the screen. An axis
can be linear or logarithmic, it can have fixed endpoints, or can automatically get them from the plotted data.
It also has settings for the axis labels and lines, tick labels, and major and minor tick marks. An axis may be
“horizontal” or “vertical” and can appear anywhere on its parent graph or grid. If an axis appears within a grid,
then it can be shared by all the graphs which are contained within the grid. The axis-broken widget is an
axis sub-type. It is an axis type where there are jumps in the scale of the axis. The axis-function widget
allows the user to create an axis where the values are scaled by a monotonic function, allowing non-linear and
non-logarithmic axis scales. The widget can also be linked to a different axis via the function.
6. plotters - types of widgets which plot data or add other things on a graph. There is no actual plotter widget
which can be added, but several types of plotters listed below. Plotters typically take an axis as a setting, which
is the axis used to plot the data on the graph (default x and y).
(a) function - a plotter which plots a function on the graph. Functions can be functions of x or y (parametric
functions are not done yet!), and are defined in Python expression syntax, which is very close to most other
languages. For example 3*x**2 + 2*x - 4. A number of functions are available (e.g. sin, cos, tan, exp,
log...). Technically, Veusz imports the numpy package when evaluating, so numpy functions are available.
As well as the function setting, also settable is the line type to plot the function, and the number of steps
to evaluate the function when plotting. Filling is supported above/below/left/right of the function.
(b) xy - a plotter which plots scatter, line, or stepped plots. This versatile plotter takes an x and y dataset, and
plots (optional) points, in a chosen marker and colour, connecting them with (optional) lines, and plotting
(optional) error bars. An xy plotter can also plot a stepped line, allowing histograms to be plotted (note
that it doesn’t yet do the binning of the data). The settings for the xy widget are the various attributes for
the points, line and error bars, the datasets to plot, and the axes to plot on. The xy plotter can plot a label
next to each dataset, which is either the same for each point or taken from a text dataset. If you wish to
leave gaps in a plot, the input value nan can be specified in the numeric dataset.
(c) fit - fit a function to data. This plotter is a like the function plotter, but allows fitting of the function to
data. This is achieved by clicking on a “fit” button, or using the “fit” action of the widget. The fitter takes
a function to fit containing the unknowns, e.g. a*x**2 + b*x + c, and initial values for the variables (here
a, b and c). It then fits the data (note that at the moment, the fit plotter fits all the data, not just the data

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Veusz Documentation, Release 3.0

that can be seen on the graph) by minimising the chi-squared. In order to fit properly, the y data (or x, if
fitting as a function of x) must have a properly defined, preferably symmetric error. If there is none, Veusz
assumes the same fractional error everywhere, or symmetrises asymmetric errors. Note that more work
is required in this widget, as if a parameter is not well defined by the data, the matrix inversion in the fit
will fail. In addition Veusz does not supply estimates for the errors or the final chi-squared in a machine
readable way. If the fitting parameters vary significantly from 1, then it is worth “normalizing” them by
adding in a factor in the fit equation to bring them to of the order of 1.
(d) bar - a bar chart which plots sets of data as horizontal or vertical bars. Multiple datasets are supported. In
“grouped” mode the bars are placed side-by-side for each dataset. In “stacked” mode the bars are placed
on top of each other (in the appropriate direction according to the sign of the dataset). Bars are placed on
coordinates given, or in integer values from 1 upward if none are given. Error bars are plotted for each of
the datasets. Different fill styles can be given for each dataset given. A separate key value can be given for
each dataset.
(e) key - a box which describes the data plotted. If a key is added to a plot, the key looks for “key” settings of
the other data plotted within a graph. If there any it builds up a box containing the symbol and line for the
plotter, and the text in the “key” setting of the widget. This allows a key to be very easily added to a plot.
The key may be placed in any of the corners of the plot, in the centre, or manually placed. Depending on
the ordering of the widgets, the key will be placed behind or on top of the widget. The key can be filled
and surrounded by a box, or not filled or surrounded.
(f) label - a text label places on a graph. The alignment can be adjusted and the font changed. The position
of the label can be specified in fractional terms of the current graph, or using axis coordinates.
(g) rect, ellipse - these draw a rectangle or ellipse, respectively, of size and rotation given. These
widgets can be placed directly on the page or on a graph. The centre can be given in axis coordinates or
fractional coordinates.
(h) imagefile - draw an external graphs file on the graph or page, with size and rotation given. The centre
can be given in axis coordinates or fractional coordinates.
(i) line - draw a line with optional arrowheads on the graph or page. One end can be given in axis coordinates or fractional coordinates.
(j) contour - plot contours of a 2D dataset on the graph. Contours are automatically calculated between
the minimum and maximum values of the graph or chosen manually. The line style of the contours can
be chosen individually and the region between contours can be filled with shading or color. 2D datasets
currently consist of a regular grid of values between minimum and maximum positions in x and y. They
can be constructed from three 1D datasets of x, y and z if they form a regular x, y grid.
(k) image - plot a 2D dataset as a colored image. Different color schemes can be chosen. The scaling between
the values and the image can be specified as linear, logarithmic, square-root or square.
(l) polygon - plot x and y points from datasets as a polygon. The polygon can be placed directly on the
page or within a graph. Coordinates are either plotted using the axis or as fractions of the width and height
of the containing widget.
(m) boxplot - plot distribution of points in a dataset.
(n) polar - plot polar data or functions. This is a non-orthogonal plot and is placed directly on the page
rather than in a graph.
(o) ternary - plot data of three variables which add up to 100 per cent.This is a non-orthogonal plot and is
placed directly on the page rather than in a graph.
7. 3D widgets - 3D graphs can be created by adding a 3D scene widget (scene3d) to a blank page, or by creating
a new 3D document. The 3D scene has settings which control the angle the rotation angle of the plot, the
position and color of lighting and the rendering method.
To build up a 3D plot the following widgets can be placed inside it:

1.4. Terminology

5

Veusz Documentation, Release 3.0

(a) graph3d - this is an analogous widget to the 2D graph widget, plotting a 3D plot with cartesian axes.
It contains three or more axis3d widgets, and plotting widgets. The graph contains settings for the graph
size (the default is 1 in each direction) and the 3D position of the graph in the same units. Multiple graph
widgets can be added to a scene, though the position and sizes may need to be adjusted.
(b) axis3d - normally a 3D graph has three axes (X, Y and Z), but more axes can be added to plot multiple
things on a single axis direction. This works in a similar way to the 2D axis widget. The widget has
options for the axis label, tick labels, tick marks and grid lines (which appear on the outside of the 3D
cube). An axis can be swiched between linear and logorithmic mode. Scalings can be applied to the data
values plotted in that dimension or to the axis labels.
(c) point3d - for plotting points, and optionally connecting lines, in 3D. This, and the other plotting widgets
are placed in a graph3d widget. The user provides three 1D datasets for the x, y and z values. The markers
can be scaled in size by another optional dataset. The markers can also be colored according to another
optional dataset, according to a color map, minimum and maximum. Error bars can be provided for each
of the x, y and z datasets. The connecting line can also be colored if a color dataset is provided and a
colormap chosen.
(d) function3d - for plotting either a functional line in 3D space or a functional surface. The type of plot is
given by the mode parameter. In the case of the line, the x,y,z coordinates can be specified as a function of
t, where t goes from 0 to 1, or by giving functions for two of the coordinates as a function of the other. For
a surface, the value for x, y or z is given as a function of the other two. In addition, a function returning
0 to 1 can be provided for the color, which specifies the color map value for the surface at each position
or the line color. For a 2D surface, the grid lines or surface fill can be hidden or shown. There are also
settings giving the number of function evaluations to compute in each direction for a surface, or in one
direction for a line.
(e) surface3d - for plotting a two dimensional surface from data values. The user should provide a 2D
dataset for the height of a surface. The x, y or z axis for the height and other directions can be chosen. A
second 2D dataset can be provided for the color of the surface at each point. Note that the coordinate of
the 2D dataset lies at the center of each 2D grid point. The height of the grid at the edge is calculated by
linear interpolation. Normally the grid is surrounded by four lines and the surface by two triangles. If a
high resolution option is enabled, the each grid point is surrounded by eight lines and the surface drawn
by eight triangles.
(f) volume3d - for plotting 3D volumes. In this widget, for a volume described by A×B×C values, then the
user should provide four datasets, each containing up to A×B×C values (there can be holes in the representation). Three of the datasets give coordinates of the centers of the 3D cells and the fourth the color of
the cell. An example set of datasets would be X=(0,0,0,0,1,1,1,1), Y=(0,0,1,1,0,0,1,1), Z=(0,1,0,1,0,1,0,1),
color=(0.1,0.2,0.3,0.4,0.3,0.2,0.1,0). Additionally, the user can provide a transparency dataset, which can
be useful for showing or hiding parts of the 3D space.

1.4.2 Settings: properties and formatting
The various settings of the widgets come in a number of types, including integers (e.g. 10), floats (e.g. 3.14), dataset
names (mydata), expressions (x+y), text (hi there!), distances (see above), options (horizontal or vertical for axes).
Veusz performs type checks on these parameters. If they are in the wrong format the control to edit the setting will
turn red. In the command line, a TypeError exception is thrown.
In the GUI, the current page is replotted if a setting is changed when enter is pressed or the user moves to another
setting.
The settings are split up into formatting settings, controlling the appearance of the plot, or properties, controlling what
is plotted and how it is plotted.
Default settings, including the default font and line style, and the default settings for any graph widget, can be modified
in the “Default styles” dialog box under the “Edit” menu. Default settings are set on a per-document basis, but can be
6

Chapter 1. Introduction

Veusz Documentation, Release 3.0

saved into a separate file and loaded. A default default settings file can be given to use for new documents (set in the
preferences dialog).

1.4.3 Datasets
Data are imported into Veusz as a dataset. A dataset is imported from a file, entered manually, set via the command
line, or linked to other datasets via an expression or dataset plugin. Each dataset has a unique name in the document.
They can be seen in the dataset browser panel, or in the Data, Edit dialog box. To choose the data to be plotted, the
user usually selects the dataset in the appropriate setting of a widget.
Veusz supports one-dimensional (1D) datasets, which are a list of values with optional error bars. Error bars can either
be symmetric or asymmetric. Veusz also supports two-dimensional (2D) data. A 2D dataset is a grid of values, with
either a fixed spacing in coordinates, or with arbitrary pixel sizes. An n-dimensional (nD) dataset is an arbitrary matrix
of values. These cannot be plotted directly, but subsets can be plotted using python slice syntax to convert to 1D or 2D
datasets.
In addition to simple numeric datasets, Veusz also supports date-time datasets. For details see the sections on reading
data. Also supported are text datasets, which are lists of text strings.
Datasets can either be plain lists of values which are stored within the document, or they can be linked to a file, so that
the values update if the file is reloaded, or they can be linked to other datasets via expressions or dataset plugins.

1.4.4 Text
Veusz understands a limited set of LaTeX-like formatting for text. There are some differences (for example, 10^23
puts the 2 and 3 into superscript), but it is fairly similar. You should also leave out the dollar signs. Veusz supports
superscripts (^), subscripts (_), brackets for grouping attributes are { and }.
Supported LaTeX symbols include: \AA, \Alpha, \Beta, \Chi, \Delta, \Epsilon, \Eta, \Gamma, \Iota, \Kappa, \Lambda,
\Mu, \Nu, \Omega, \Omicron, \Phi, \Pi, \Psi, \Rho, \Sigma, \Tau, \Theta, \Upsilon, \Xi, \Zeta, \alpha, \approx, \ast,
\asymp, \beta, \bowtie, \bullet, \cap, \chi, \circ, \cup, \dagger, \dashv, \ddagger, \deg, \delta, \diamond, \divide, \doteq,
\downarrow, \epsilon, \equiv, \eta, \gamma, \ge, \gg, \hat, \in, \infty, \int, \iota, \kappa, \lambda, \le, \leftarrow, \lhd, \ll,
\models, \mp, \mu, \neq, \ni, \nu, \odot, \omega, \omicron, \ominus, \oplus, \oslash, \otimes, \parallel, \perp, \phi, \pi,
\pm, \prec, \preceq, \propto, \psi, \rhd, \rho, \rightarrow, \sigma, \sim, \simeq, \sqrt, \sqsubset, \sqsubseteq, \sqsupset,
\sqsupseteq, \star, \stigma, \subset, \subseteq, \succ, \succeq, \supset, \supseteq, \tau, \theta, \times, \umid, \unlhd,
\unrhd, \uparrow, \uplus, \upsilon, \vdash, \vee, \wedge, \xi, \zeta. Please request additional characters if they are
required (and exist in the unicode character set). Special symbols can be included directly from a character map.
Other LaTeX commands are supported. \\ breaks a line. This can be used for simple tables. For example {a\\b} {c\\d}
shows a c over b d. The command \frac{a}{b} shows a vertical fraction a/b.
Also supported are commands to change font. The command \font{name}{text} changes the font text is written in to
name. This may be useful if a symbol is missing from the current font, e.g. \font{symbol}{g} should produce a gamma.
You can increase, decrease, or set the size of the font with \size{+2}{text}, \size{-2}{text}, or \size{20}{text}. Numbers
are in points.
Various font attributes can be changed: for example, \italic{some italic text} (or use \textit or \emph), \bold{some bold
text} (or use \textbf ) and \underline{some underlined text}.
Example text could include Area / \pi (10^{-23} cm^{-2}), or \pi\bold{g}.
Veusz plots these symbols with Qt’s unicode support. You can also include special characters directly, by copying and
pasting from a character map application. If your current font does not contain these symbols then you may get a box
character.
Veusz also supports the evaluation of a Python expression when text is written to the page. Python code is written
inside the brackets %{{ }}%. Note that the Python evaluation happens before the LaTeX expansion is done. The

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return value of the expression is converted to text using the Python str() function. For example, the expression
%{{2+2}}% would write 4. Custom functions and constants are supported when evaluation, in addition to the usual
numpy functions. In addition, Veusz defines the following useful functions and values.
1. ENVIRON is the os.environ dict of environment variables. %{{ENVIRON['USER']}}% would show the
current user in unix.
2. DATE([fmt]) returns the current date, by default in ISO format. fmt is an optional format specifier using
datetime.date.strftime format specifiers.
3. TIME([fmt]) returns the current date/time, by default in ISO format. fmt is an optional format specifier using
datetime.datetime.strftime format specifiers.
4. DATA(name[, part]) returns the Veusz dataset with given name. For numeric datasets this is a numpy
array. For numeric datasets with errors, part specifies the dataset part to return, i.e. ‘data’, ‘serr’, ‘perr’, ‘nerr’.
For example, the mean value of a dataset could be shown using %{{mean(DATA('x'))}}%.
5. FILENAME() - returns the current document filename. This can include the directory/folder of the file. Note
that the filename is escaped with ESCAPE() so that LaTeX symbols are not expanded when shown.
6. BASENAME() - returns the current document filename, removing the directory or folder name Note that the
filename is escaped with ESCAPE() so that LaTeX symbols are not expanded when shown.
7. ESCAPE(x) - escapes any LaTeX symbols in x so that they are not interpreted as LaTeX.
8. SETTING(path) - return the value of the Veusz setting given by the full path, e.g. %{{SETTING('/
page1/width')}}%.
9. LANG(mapping) - mapping is a dictionary which maps language names to strings. This returns the string
corresponding to the current language. The keys come from the locale names which are the two-letter language
codes (e.g. en or fr), or the full code (e.g. en_GB or de_AT). The default key is used if the language code is not
found. An example is %{{ LANG({'de':'Druck','default':'Pressure'}) }}%.

1.4.5 Measurements
Distances, widths and lengths in Veusz can be specified in a number of different ways. These include absolute distances
specified in physical units, e.g. 1cm, 0.05m, 10mm, 5in and 10pt, and relative units, which are relative to the largest
dimension of the page, including 5%, 1/20, 0.05.

1.4.6 Color theme
From version 1.26, widgets are colored automatically using the color theme. This theme is specified in the main
document widget settings. Widgets are given the colors in order given the order in a graph widget. The default theme
can be specified in the preferences dialog box.
To override a theme, the user can manually specify the individual colors in the custom definitions dialog box. Color
theme1 is used as the first theme color, then theme2, etc.

1.4.7 Axis numeric scales
The way in which numbers are formatted in axis scales is chosen automatically. For standard numerical axes, values
are shown with the %Vg formatting (see below). For date axes, an appropriate date formatting is used so that the
interval shown is correct. A format can be given for an axis in the axis number formatting panel can be given to
explicitly choose a format. Some examples are given in the drop down axis menu. Hold the mouse over the example
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C-style number formatting is used with a few Veusz specific extensions. Text can be mixed with format specifiers,
which start with a % sign. Examples of C-style formatting include: %.2f (decimal number with two decimal places,
e.g. 2.01), %.3e (scientific formatting with three decimal places, e.g. 2.123e-02), %g (general formatting, switching
between %f and %e as appropriate). See http://opengroup.org/onlinepubs/007908799/xsh/fprintf.html for details.
Veusz extensions include %Ve, which is like %e except it displays scientific notation as written, e.g. 1.2x10^23, rather
than 1.2e+23. %Vg switches between standard numbers and Veusz scientific notation for large and small numbers.
%VE using engineering SI suffixes to represent large or small numbers (e.g. 1000 is 1k).
Veusz allows dates and times to be formatted using %VDX where X is one of the formatting characters for strftime
(see http://opengroup.org/onlinepubs/007908799/xsh/strftime.html for details). These include a for an abbreviated
weekday name, A for full weekday name, b for abbreviated month name, B for full month name, c date and time
representation, d day of month 01..31, H hour as 00..23, I hour as 01..12, j as day of year 001..366, m as month 01..12,
M minute as 00..59, p AM/PM, S second 00..61, U week number of year 00..53 (Sunday as first day of week), w
weekday as decimal number 0..6, W week number of year (Monday as first day of week), x date representation, X
time representation, y year without century 00..99 and Y year. %VDVS is a special Veusz addon format which shows
seconds and fractions of seconds (e.g. 12.2).

1.4.8 Three dimensional (3D) plots
When drawing in three dimensions, Veusz builds up a 3D “scene” for the graph from the various plotting widgets,
made up of triangles, line segments, points and text. Veusz does not use a standard (e.g. OpenGL) drawing method,
but renders the scene itself. The advantage of this is that it can produce vector rather than bitmap or raster output.
OpenGL, for example, is based around bitmaps.
Veusz applies lighting to the scene. The lighting depends on enabled light sources, which are set in the scene3d widget.
Light sources have a color, intensity and position. Note that only the angle of the light to a surface affects its lighting,
not its distance. The position of the light is relative to the viewer (camera), not the graph. Positive light coordinates are
towards the graph (z), upwards (y) and rightwards (x). Normally each solid surface has an intrinsic color, which can
be seen without any lighting. If a light source is enabled, the color of the light is added to the surface color, depending
on the reflectivity of the surface. Each surface also has a transparency setting.
By default, Veusz uses a naive Painter’s Algorithm to draw the scene. It draws from the back of scene to the front. The
main problem with this algorithm is that shapes and lines overlapping in depth can be confused as the depth of each
object is calculated at only one point. In addition objects may intersect, which is not properly treated. In the scene3d
object, the user can switch to a different rendering mode called BSP. In this accurate BSP mode, the objects are split so
that they never overlap from any viewing angle. The disadvantage of this mode is that it is slow, uses a lot of memory
and produces large output files. We plan in future to add another mode which handles overlaps better and does not
unnecessarily split objects.
The plot is affected by the viewing angle, which is specified in the scene3d widget settings. The rotation is given be
three rotations around lines in X, Y and Z directions (note that these are not the same directions as the X, Y and Z
axes!). The X axis runs horizontally on the screen, the Y axis runs vertically, and the Z axis runs along the line of
sight.
There is also a distance setting, which moves graphs closer to or away from the viewer. At larger distances the effect
of perspective reduces, meaning that parts of the plot closer to the viewer are not larger than if they were at the farthest
side. At large distances, a plot tends towards being isometric. At small distances, shapes are more distorted (note by
default the size of the graph is 1 in these distance units). It is currently possible to place graphs inside the camera
leading to strange output.
By default, Veusz enlarges the 3D rendered scene to fill the bounds of the 3D scene widget, so distance has no effect
on the size of the plot. This scaling can be switched off by modifying the Size setting from “Auto” to a fixed number.
A fixed size is useful if the user wants a graph to be the same size for any rotation. With this setting the size of the plot
is affected by their distance.

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By default, a 3D graph has dimensions of 1 along the X, Y and Z axes. The size can be adjusted using the size settings
in the graph3d widget. Care should be taken that the graph size does not lead to points being at negative viewing
distances. The default position of the plot is at the origin 0,0,0. If the user wants to plot multiple graph3d widgets, the
positions should be adjusted to prevent overlap.
Normally in Veusz, sizes of objects (e.g. plot markers) are given in physical units. This makes less sense for a 3D plot
as sizes can depend on distance. In a 3D graph sizes of plotting markers and line widths are given in 1/1000 of the
graph bounding box maximum dimension.

1.5 The main window
You should see the main window when you run Veusz (you can just type the veusz command in Unix).

The Veusz window is split into several sections. At the top is the menu bar and tool bar. These work in the usual way
to other applications. Sometimes options are disabled (greyed out) if they do not make sense to be used. If you hold
your mouse over a button for a few seconds, you will usually get an explanation for what it does called a “tool tip”.
Below the main toolbar is a second toolbar for constructing the graph by adding widgets (on the left), and some editing
buttons. The add widget buttons add the request widget to the currently selected widget in the selection window. The
widgets are arranged in a tree-like structure.
Below these toolbars and to the right is the plot window. This is where the current page of the current document is
shown. You can adjust the size of the plot on the screen (the zoom factor) using the “View” menu or the zoom tool bar
button (the magnifying glass). Initially you will not see a plot in the plot window, but you will see the Veusz logo. At
the moment you cannot do much else with the window. In the future you will be able to click on items in the plot to
modify them.
To the left of the plot window is the selection window, and the properties and formatting windows. The properties
window lets you edit various aspects of the selected widget (such as the minimum and maximum values on an axis).
Changing these values should update the plot. The formatting lets you modify the appearance of the selected widget.
There are a series of tabs for choosing what aspect to modify.
The various windows can be “dragged” from the main window to “float” by themselves on the screen.
To the bottom of the window is the console. This window is not shown by default, but can be enabled in the View menu.
The console is a Veusz and Python command line console. To read about the commands available see Commands.
As this is a Python console, you can enter mathematical expressions (e.g. 1+2.0*cos(pi/4)) here and they will be
evaluated when you press Enter. The usual special functions and the operators are supported. You can also assign
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results to variables (e.g. a=1+2) for use later. The console also supports command history like many Unix shells.
Press the up and down cursor keys to browse through the history. Command line completion is not available yet!
There also exists a dataset browsing window, by default to the right of the screen. This window allows you to view
the datasets currently loaded, their dimensions and type. Hovering a mouse over the size of the dataset will give you a
preview of the data.

1.6 My first plot
After opening Veusz, on the left of the main window, you will see a Document, containing a Page, which contains
a Graph with its axes. The Graph is selected in the selection window. The toolbar above adds a new widget to the
selected widget. If a widget cannot be added to a selected widget it is disabled. On opening a new document Veusz
automatically adds a new Page and Graph (with axes) to the document.
You will see something like this:

Select the x axis which has been added to the document (click on x in the selection window). In the properties window
you will see a variety of different properties you can modify. For instance you can enter a label for the axis by writing
Area (cm^{2}) in the box next to label and pressing enter. Veusz supports text in LaTeX-like form (without the dollar
signs). Other important parameters is the log switch which switches between linear and logarithmic axes, and min and
max which allow the user to specify the minimum and maximum values on the axes.
The formatting dialog lets you edit various aspects of the graph appearance. For instance the “Line” tab allows you to
edit the line of the axis. Click on “Line”, then you can then modify its colour. Enter “green” instead of “black” and
press enter. Try making the axis label bold.
Now you can try plotting a function on the graph. If the graph, or its children are selected, you will then be able to
click the “function” button at the top (a red curve on a graph). You will see a straight line (y=x) added to the plot.
If you select “function1”, you will be able to edit the functional form plotted and the style of its line. Change the
function to x**2 (x-squared).
We will now try plotting data on the graph. Go to your favourite text editor and save the following data as test.dat:
1
2.05
2.98
4.02

0.1
0.12
0.08
0.04

-0.12
-0.14
-0.1
-0.1

1.6. My first plot

1.1
4.08
2.9
15.3

0.1
0.12
0.11
1.0

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The first three columns are the x data to plot plus its asymmetric errors. The final two columns are the y data plus its
symmetric errors. In Veusz, go to the “Data” menu and select “Import”. Type the filename into the filename box, or
use the “Browse...” button to search for the file. You will see a preview of the data pop up in the box below. Enter
x,+,- y,+- into the descriptors edit box (note that commas and spaces in the descriptor are almost interchangeable in
Veusz 1.6 or newer). This describes the format of the data which describes dataset “x” plus its asymmetric errors, and
“y” with its symmetric errors. If you now click “Import”, you will see it has imported datasets x and y.
To plot the data you should now click on graph1 in the tree window. You are now able to click on the “xy” button
(which looks like points plotted on a graph). You will see your data plotted on the graph. Veusz plots datasets x and y
by default, but you can change these in the properties of the “xy” plotter.
You are able to choose from a variety of markers to plot. You can remove the plot line by choosing the “Plot Line”
subsetting, and clicking on the “hide” option. You can change the colour of the marker by going to the “Marker Fill”
subsetting, and entering a new colour (e.g. red), into the colour property.

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CHAPTER

TWO

READING DATA

Currently Veusz supports reading data from files with text, CSV, HDF5, FITS, 2D text or CSV, QDP, binary and
NPY/NPZ formats. Use the Data → Import dialog to read data, or the importing commands in the API can be used.
In addition, the user can load or write import plugins in Python which load data into Veusz in an arbitrary format.
At the moment QDP, binary and NPY/NPZ files are supported with this method. The HDF5 file format is the most
sophisticated, and is recommended for complex datasets.
By default, data are “linked” to the file imported from. This means that the data are not stored in the Veusz saved file
and are reloaded from the original data file when opening. In addition, the user can use the Data → Reload menu
option to reload data from linked files. Unselect the linked option when importing to remove the association with the
data file and to store the data in the Veusz saved document.
Note that a prefix and suffix can be given when importing. These are added to the front or back of each dataset name
imported. They are convenient for grouping data together.

We list the various types of import below.

2.1 Standard text import
The default text import operates on simple text files. The data are assumed to be in columns separated by whitespace.
Each column corresponds to dataset (or its error bars). Each row is an entry in the dataset.

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The way the data are read is goverened by a simple “descriptor”. This can simply be a list of dataset names separated
by spaces. If no descriptor is given, the columns are treated as separate datasets and are given names col1, col2, etc.
Veusz attempts to automatically determine the type of the data.
When reading in data, Veusz treats any whitespace as separating columns. The columns do not actually need to be
aligned. Furthermore a \ symbol can be placed at the end of a line to mark a continuation. Veusz will read the next line
as if it were placed at the end of the current line. In addition comments and blank lines are ignored (unless in block
mode). Comments start with a #, ;, ! or %, and continue until the end of the line. The special value nan can be used to
specify a break in a dataset.
If the option to read data in blocks is enabled, Veusz treats blank lines (or lines starting with the word no) as block
separators. For each dataset in the descriptor, separate datasets are created for each block, using a numeric suffix
giving the block number, e.g. _1, _2.

2.1.1 Data types in text import
Veusz supports reading in several types of data. The type of data can be added in round brackets after the name in the
descriptor. Veusz will try to guess the type of data based on the first value, so you should specify it if there is any form
of ambiguity (e.g. is 3 text or a number). Supported types are numbers (use numeric in brackets) and text (use text in
brackets). An example descriptor would be x(numeric) +- y(numeric) + - label(text) for an x dataset followed by its
symmetric errors, a y dataset followed by two columns of asymmetric errors, and a final column of text for the label
dataset.
A text column does not need quotation unless it contains space characters or escape characters. However make sure
you deselect the “ignore text” option in the import dialog. This ignores lines of text to ease the import of data from
other applications. Quotation marks are recommended around text if you wish to avoid ambiguity. Text is quoted
according to the Python rules for text. Double or single quotation marks can be used, e.g. “A ‘test”’, ‘A second
“test”’. Quotes can be escaped by prefixing them with a backslash, e.g. “A new \”test\”“. If the data are generated
from a Python script, the repr function provides the text in a suitable form.
Dates and times are also supported with the syntax dataset(date). Dates must be in ISO format YYYY-MM-DD. Times
are in 24 hour format hh:mm:ss.ss. Dates with times are written YYYY-MM-DDThh:mm:ss.ss (this is a standard ISO
format, see http://www.w3.org/TR/NOTE-datetime). Dates are stored within Veusz as a number which is the number
of seconds since the start of January 1st 2009. Veusz also supports dates and times in the local format, though take
note that the same file and data may not work on a system in a different location.

2.1.2 Descriptors
A list of datasets, or a “Descriptor”, is given in the Import dialog to describe how the data are formatted in the import
file. The descriptor at its simplest is a space or comma-separated list of the names of the datasets to import. These are
columns in the file.
Following a dataset name the text +, -, or +- can be given to say that the following column is a positive error bar,
negative error bar or symmetric error bar for the previous (non error bar) dataset. These symbols should be separated
from the dataset name or previous symbol with a space or a comma symbol.
In addition, if multiple numbered columns should be imported, the dataset name can be followed by square brackets
containing a range in the form [a:b] to number columns a to b, or [:] to number remaining columns. See below for
examples of this use.
Dataset names can contain virtually any character, even unicode characters. If the name contains non alpha-numeric
characters (characters outside of A-Z, a-z and 0-9), then the dataset name should be contained within back-tick characters. An example descriptor is `length data (m)`,+- `speed (mps)`,+,-, for two datasets with spaces
and brackets in their names.

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Instead of specifying the descriptor in the Import dialog, the descriptor can be placed in the data file using a descriptor
statement on a separate line, consisting of “descriptor” followed by the descriptor. Multiple descriptors can be placed
in a single file, for example:
# here is one section
descriptor x,+- y,+,1 0.5 2 0.1 -0.1
2 0.3 4 0.2 -0.1
# my next block
descriptor alpha beta gamma
1 2 3
4 5 6
7 8 9
# etc...

2.1.3 Descriptor examples
1. x y two columns are present in the file, they will be read in as datasets x and y.
2. x,+- y,+,- or x +- y + - two datasets are in the file. Dataset “x” consists of the first two columns. The
first column are the values and the second are the symmetric errors. “y” consists of three columns (note the
comma between + and -). The first column are the values, the second positive asymmetric errors, and the third
negative asymmetric errors. Suppose the input file contains:
1.0 0.3 2
1.5 0.2 2.3
2.19 0.02 5

0.1 -0.2
2e-2 -0.3E0
0.1 -0.1

Then x will contain 1+-0.3, 1.5+-0.2, 2.19+-0.02. y will contain 2 +0.1 -0.2, 2.3 +0.02 -0.3, 5 +0.1 -0.1.
3. x[1:2] y[:] the first column is the data x_1, the second x_2. Subsequent columns are read as y[1] to y[n].
4. y[:]+- read each pair of columns as a dataset and its symmetric error, calling them y[1] to y[n].
5. foo,,+- read the first column as the foo dataset, skip a column, and read the third column as its symmetric
error.

2.2 CSV files
CVS (comma separated variable) files are often written from other programs, such as spreadsheets, including Excel
and Gnumeric. Veusz supports reading from these files.
In the import dialog choose “CSV”, then choose a filename to import from. In the CSV file the user should place the
data in either rows or columns. Veusz will use a name above a column or to the left of a row to specify what the dataset
name should be. The user can use new names further down in columns or right in rows to specify a different dataset
name. Names do not have to be used, and Veusz will assign default col and row names if not given. You can also
specify a prefix which is prepended to each dataset name read from the file.
To specify symmetric errors for a column, put +- as the dataset name in the next column or row. Asymmetric errors
can be stated with + and - in the columns.
The data type in CSV files are automatically detected unless specified. The data type can be given in brackets after the
column name, e.g. name (text), where the data type is date, numeric or text. Explicit data types are needed if the data
look like a different data type (e.g. a text item of 1.23). The date format in CSV files can be specified in the import
dialog box - see the examples given. In addition CSV files support numbers in European format (e.g. 2,34 rather than
2.34), depending on the setting in the dialog box.
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2.3 HDF5 files
HDF5 is a flexible data format. Datasets and tables can be stored in a hierarchical arrangements of groups within a
file. Veusz supports reading 1D numeric, text, date-time, 2D numeric or n-dimensional numeric data from HDF files.
The h5py Python module must be installed to use HDF5 files (included in binary releases).
In the import dialog box, choose which individual datasets to import, or selecting a group to import all the datasets
within the group. If selecting a group, datasets in the group incompatible with Veusz are ignored.
A name can be provided for each dataset imported by entering one under “Import as”. If one is not given, the dataset
or column name is used. The name can also be specified by setting the HDF5 dataset attribute vsz_name to the
name. Note that for compound datasets (tables), vsz_ attributes for columns are given by appending the suffix
_columnname to the attribute.

2.3.1 Error bars
Error bars are supported in two ways. The first way is to combine 1D datasets. For the datasets which are error
bars, use a name which is the same as the main dataset but with the suffix (+-), (+) or (-), for symmetric, postive or
negative error bars, respectively. The second method is to use a 2D dataset with two or three columns, for symmetric or
asymmetric error bars, respectively. Click on the dataset in the dialog and choose the option to import as a 1D dataset.
This second method can also be enabled by adding an HDF5 attribute vsz_twod_as_oned set to a non-zero value
for the dataset.

2.3.2 Slices
You may wish to reduce the dimensions of a dataset before importing by slicing. You can also give a slice to import a
subset of a dataset. When importing, in the slice column you can give a slice expression. This should have the same
number of entries as the dataset has dimensions, separated by commas. An entry can be a single number, to select a
particular row or column. Alternatively it could be an expression like a:b:c or a:b, where a is the starting index, b
is one beyond the stopping index and optionally c is the step size. A slice can also be specified by providing an HDF5
attribute vsz_slice for the dataset.

2.3.3 2D data ranges
2D data have an associated X and Y range. By default the number of pixels of the image are used to give this range.
A range can be specified by clicking on the dataset and entering a minimum and maximum X and Y coordinates.
Alternatively, provide the HDF5 attribute for the dataset vsz_range, which should be set to an array of four values
(minimum x, minimum y, maximum x, maximum y).

2.3.4 Dates
Date/time datasets can be made from a 1D numeric dataset or from a text dataset. For the 1D dataset, use the number
of seconds relative to the start of the year 2009 (this is Veusz format) or the year 1970 (this is Unix format). In the
import dialog, click on the name of the dataset and choose the date option. To specify a date format in the HDF5 file,
set the attribute vsz_convert_datetime to either veusz or unix.
For text datasets, dates must be given in the right format, selected in the import dialog after clicking on the dataset
name. As in other file formats, by default Veusz uses ISO 8601 format, which looks like 2013-12-22T21:08:07, where
the date and time parts are optional. The T is also optional. You can also provide your own format when importing by
giving a date expression using YYYY, MM, DD, hh, mm and ss (e.g. YYYY-MM-DD|T|hh:mm:ss), where vertical bars
mark optional parts of the expression. To automate this, set the attribute vsz_convert_datetime to the format
expression or iso to specify ISO format.
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2.4 2D text or CSV format
Veusz can import 2D data from standard text or CSV files. In this case the data should consist of a matrix of data
values, with the columns separated by one or more spaces or tabs and the rows on different lines.
In addition to the data the file can contain lines at the top which affect the import. Such specifiers are used, for example,
to change the coordinates of the pixels in the file. By default the first pixels coordinates is between 0 and 1, with the
centre at 0.5. Subsequent pixels are 1 greater. Note that the lowest coordinate pixel is the bottom-left value in the
table of imported values. When using specifiers in CSV files, put the different parts (separated by spaces) in separate
columns. Below are listed the specifiers:
1. xrange A B - make the 2D dataset span the coordinate range A to B in the x-axis (where A and B are
numbers). Note that the range is inclusive, so a 1 pixel wide image with A=0 and B=1 would have the pixel
centre at 0.5. The pixels are assumed to have the same spacing. Do not use this as the same time as the xedge
or xcent options.
2. yrange A B - make the 2D dataset span the coordinate range A to B in the y-axis (where A and B are
numbers).
3. xedge A B C... - rather than assume the pixels have the same spacing, give the coordinates of the edges
of the pixels in the x-axis. The numbers should be space-separated and there should be one more number than
pixels. Do not give xrange or xcent if this is given. If the values are increasing, the lowest coordinate
value is at the left of the dataset, otherwise if they are decreasing, it is on the right (unless the rows/columns are
inverted or transposed).
4. yedge A B C... - rather than assume the pixels have the same spacing, give the coordinates of the edges
of the pixels in the y-axis. If the values are increasing, the lowest coordinate value is at the bottom row. If they
instead decrease, it is at the top.
5. xcent A B C... - rather than give a total range or pixel edges, give the centres of the pixels. There should
be the same number of values as pixels in the image. Do not give xrange or xedge if this is given. The order
of the values specify whether the pixels are left to right or right to left.
6. ycent A B C... - rather than give a total range or pixel edges, give the centres of the pixels. The value
order specifies whether the pixels are bottom to top, or top to bottom.
7. invertrows - invert the rows after reading the data.
8. invertcols - invert the columns after reading the data.
9. transpose - swap rows and columns after importing data.
10. gridatedge - the first row and leftmost column give the positions of the centres of the pixels. This is also an
option in the import dialog. The values should be increasing or decreasing.

2.5 FITS files
1D, 2D or n-dimensional data can be read from FITS files. 1D or 2D data can be read from image, primary or table
HDUs. nD data can be read from from image or primary extensions. Note that pyfits or astropy must be installed to
get FITS support.
The import dialog box uses a tree to show the structure of the FITS file. The user can choose to import the whole file,
by clicking the check box at the top. They can import data from a particular HDU by selecting that, or individual table
columns can be selected.
In the dialog box, a dataset can be given a name for the dataset. Otherwise the HDU or table column name is used.
Note that a prefix and/or suffix can be specified to be added to all dataset names.

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If dataset y should have an error bar specified by column yerr, then in the name for yerr, enter ‘y (+-)’. Asymmetric
error bars can be specified using (+) and (-) on inidividual columns.
The slice column can be used to only import a subset of the dataset imported. This uses Python slicing syntax, which
is comma-separated list of ranges and steps. A range is specified like 10:20, which selects the 11th to 20th items (the
indices are numbered from 0, and the final index is one past the index you actually want). A stepped range can look
like 10:20:2, which selects every other item in that range. Each of these numbers are optional, so : selects all items
on that dimension. For example the slice :,10:14:2 selects all values on the first dimension, but only the 11th and 13th
items on the next axis.
When importing 2D data the user can specify whether to treat this as 1D plus error bars (dimensions should have 2 or
3 columns), or specify a range in 2D space the data covers. Veusz will also attempt to use WCS information in the file
for the 2D range if not specified. The standard mode is to use the CDELT, CRVAL and CRPIX keywords to specify
a linear range for the data. Alternatively the user can specify pixel numbering (numbering from 0 to N-1). There is a
fraction option for using a range of 0 to 1. Finally there is a pixel numbering scheme which numbers in pixels from
the CRPIX keyword items.
Some of these options can be specified in the FITS file using the ‘VEUSZ’ header keyword. This header keyword can
be added with the value ‘KEY=VALUE’ (applying to the whole HDU) or ‘COLUMN: KEY=VALUE’ (applying to a
particular column in a table). Supported options for KEY are:
name provide name for dataset in VALUE
slice VALUE is slice to apply when importing dataset
range range of data for 2D dataset in form [minx, miny, maxx, maxy]
xrange/yrange range of dataset individually in x or y
xcent/ycent set to list of values giving centers of pixels
xedge/yedge set to list of values giving edges of pixels
twod_as_oned treat as 1D data with error bars if VALUE=1
wcsmode use specific WCS mode for 2D dataset (should be pixel/pixel_wcs/linear_wcs/fraction)

2.6 Reading other data formats
As mentioned above, a user may write some Python code to read a data file or set of data files. To write a plugin which
is incorportated into Veusz, see https://github.com/veusz/veusz/wiki/ImportPlugins
You can also include Python code in an input file to read data, which we describe here. Suppose an input file “in.dat”
contains the following data:
1
2
3
4

2
4
9
16

Of course this data could be read using the ImportFile command. However, you could also read it with the following
Veusz script (which could be saved to a file and loaded with execfile or Load. The script also places symmetric
errors of 0.1 on the x dataset.
x = []
y = []
for line in open("in.dat"):
parts = [float(i) for i in line.split()]
x.append(parts[0])

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y.append(parts[1])
SetData('x', x, symerr=0.1)
SetData('y', y)

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THREE

MANIPULATING DATASETS

Imported datasets can easily be modified in the Data Editor dialog box. This dialog box can also be used to create new
datasets from scratch by typing them in. The Data Create dialog box is used to new datasets as a numerical sequence,
parametrically or based on other datasets given expressions. If you want to plot a function of a dataset, you often do
not have to create a new dataset. Veusz allows to enter expressions directly in many places.

3.1 Using dataset plugins
Dataset plugins can be used to perform arbitrary manipulation of datasets. Veusz includes several plugins for mathematical operation of data and other dataset manipulations, such as concatenation or splitting. If you wish to write your
own plugins look at https://github.com/veusz/veusz/wiki/DatasetPlugins.

3.2 Using expressions to create new datasets
For instance, if the user has already imported dataset d, then they can create d2 which consists of d**2. Expressions
are in Python numpy syntax and can include the usual mathematical functions.

Expressions for error bars can also be given. By appending _data, _serr, _perr or _nerr to the name of the
dataset in the expression, the user can base their expression on particular parts of the given dataset (the main data,

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symmetric errors, positive errors or negative errors). Otherwise the program uses the same parts as is currently being
specified.
If a dataset name contains non alphanumeric characters, its name should be quoted in the expression in back-tick
characters, e.g. `length (cm)`*2.
The numpy functionality is particularly useful for doing more complicated expressions. For instance, a conditional
expression can be written as where(x
Use a dataset plugin. pluginname: name of plugin to use fields: dict of input values to plugin datasetnames: dict
mapping old names to new names of datasets if they are renamed. The new name None means dataset is deleted

5.2.9 EnableToolbar
EnableToolbar(enable=True)
Enable/disable the zooming toolbar in the plotwindow. This command is only supported in embedded mode or from
veusz –listen.

5.2.10 Export
Export(filename, color=True, page=0, dpi=100, antialias=True, quality=85,
backcolor='#ffffff00', pdfdpi=150, svgtextastext=False)
Export the page given to the filename given. The filename must end with the correct extension to get the right
sort of output file. Currrenly supported extensions are ‘.eps’, ‘.pdf’, ‘.ps’, ‘.svg’, ‘.jpg’, ‘.jpeg’, ‘.bmp’ and ‘.png’.
If color is True, then the output is in colour, else greyscale. page is the page number of the document to export
(starting from 0 for the first page!). A list of pages can be given for multipage formats (.pdf or .ps). dpi is the number
of dots per inch for bitmap output files. antialias - antialiases output if True. quality is a quality parameter for
jpeg output. backcolor is the background color for bitmap files, which is a name or a #RRGGBBAA value (red,
green, blue, alpha). pdfdpi is the dpi to use when exporting EPS or PDF files. svgtextastext says whether to
export SVG text as text, rather than curves.

5.2.11 FilterDatasets
FilterDatasets(filterexpr, datasets, prefix="", suffix="", invert=False,
replaceblanks=False)
Filter a list of datasets given. Creates new datasets for each with prefix and suffix added to input dataset names.
filterexpr is an input numpy eexpression for filtering the datasets. If invert is set, the filter condition is inverted. If
replaceblanks is set, filtered values are not removed, but replaced with a blank or NaN value. This command only
works on 1D numeric, date or text datasets.

5.2.12 ForceUpdate
ForceUpdate()
Force the window to be updated to reflect the current state of the document. Often used when periodic updates have
been disabled (see SetUpdateInterval). This command is only supported in embedded mode or from veusz –listen.

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5.2.13 Get
Get('settingpath')
Returns: The value of the setting given by the path.
>>> Get('/page1/graph1/x/min')
'Auto'

5.2.14 GetChildren
GetChildren(where='.')
Returns: The names of the widgets which are children of the path given

5.2.15 GetClick
GetClick()
Waits for the user to click on a graph and returns the position of the click on appropriate axes. Command only works
in embedded mode.
Returns: A list containing tuples of the form (axispath, val) for each axis for which the click was in range. The value
is the value on the axis for the click.

5.2.16 GetColormap
GetColormap(name, invert=False, nvals=256)
Returns a colormap as a numpy array of red, green, blue, alpha values (ranging from 0 to 255) with the number of
steps given.

5.2.17 GetData
GetData(name)
Returns: For a 1D dataset, a tuple containing the dataset with the name given. The value is (data, symerr, negerr,
poserr), with each a numpy array of the same size or None. data are the values of the dataset, symerr are the symmetric
errors (if set), negerr and poserr and negative and positive asymmetric errors (if set). If a text dataset, return a list of
text elements. If the dataset is a date-time dataset, return a list of Python datetime objects. If the dataset is a 2D dataset
return the tuple (data, rangex, rangey), where data is a 2D numpy array and rangex/y are tuples giving the range of the
x and y coordinates of the data. If it is an ND dataset, return an n-dimensional array.
data = GetData('x')
SetData('x', data[0]*0.1, \*data[1:])

5.2.18 GetDataType
GetDataType(name)
Get type of dataset with name given. Returns ‘1d’ for a 1d dataset, ‘2d’ for a 2d dataset, ‘text’ for a text dataset and
‘datetime’ for a datetime dataset.

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5.2.19 GetDatasets
GetDatasets()
Returns: The names of the datasets in the current document.

5.2.20 GPL
GPL()
Print out the GNU Public Licence, which Veusz is licenced under.

5.2.21 ImportFile
ImportFile('filename', 'descriptor', linked=False, prefix='', suffix='',
encoding='utf_8', renames={})
Imports data from a file. The arguments are the filename to load data from and the descriptor.
The format of the descriptor is a list of variable names representing the columns of the data. For more information see
Descriptors.
If the linked parameter is set to True, if the document is saved, the data imported will not be saved with the document,
but will be reread from the filename given the next time the document is opened. The linked parameter is optional.
If prefix and/or suffix are set, then the prefix and suffix are added to each dataset name. If set, renames maps imported
dataset names to final dataset names after import.
Returns: A tuple containing a list of the imported datasets and the number of conversions which failed for a dataset.
Changed in version 0.5: A tuple is returned rather than just the number of imported variables.

5.2.22 ImportFile2D
ImportFile2D('filename', datasets, xrange=None, yrange=None, invertrows=False,
invertcols=False, transpose=False, prefix='', suffix='', linked=False,
encoding='utf8', renames={})
Imports two-dimensional data from a file. The required arguments are the filename to load data from and the dataset
name, or a list of names to use.
filename is a string which contains the filename to use. datasets is either a string (for a single dataset), or a list of
strings (for multiple datasets).
The xrange parameter is a tuple which contains the range of the X-axis along the two-dimensional dataset, for example
(-1., 1.) represents an inclusive range of -1 to 1. The yrange parameter specifies the range of the Y-axis similarly. If
they are not specified, (0, N) is the default, where N is the number of datapoints along a particular axis.
invertrows and invertcols if set to True, invert the rows and columns respectively after they are read by Veusz. transpose
swaps the rows and columns.
If prefix and/or suffix are set, they are prepended or appended to imported dataset names. If set, renames maps
imported dataset names to final dataset names after import.
If the linked parameter is True, then the datasets are linked to the imported file, and are not saved within a saved
document.

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The file format this command accepts is a two-dimensional matrix of numbers, with the columns separated by spaces or
tabs, and the rows separated by new lines. The X-coordinate is taken to be in the direction of the columns. Comments
are supported (use #, ! or %), as are continuation characters (\). Separate datasets are deliminated by using blank lines.
In addition to the matrix of numbers, the various optional parameters this command takes can also be specified in the
data file. These commands should be given on separate lines before the matrix of numbers. They are:
1. xrange A B
2. yrange C D
3. invertrows
4. invertcols
5. transpose

5.2.23 ImportFileCSV
ImportFileCSV('filename', readrows=False, dsprefix='', dssuffix='',
linked=False, encoding='utf_8', renames={})
This command imports data from a CSV format file. Data are read from the file using the dataset names given at
the top of the files in columns. Please see the reading data section of this manual for more information. dsprefix is
prepended to each dataset name and dssuffix is added (the prefix option is deprecated and also addeds an underscore
to the dataset name). linked specifies whether the data will be linked to the file. renames, if set, provides new names
for datasets after import.

5.2.24 ImportFileFITS
ImportFileFits(filename, items, namemap={}, slices={}, twodranges={},
twod_as_oned=set([]), wcsmodes={}, prefix='', suffix='', renames={},
linked=False)
Import data from a FITS file.
items is a list of datasets to be imported. items are formatted like the following:
'/':
import whole file
'/hduname':
import whole HDU (image or table)
'/hduname/column': import column from table HDU

all values in items should be lower case.
HDU names have to follow a Veusz-specific naming. If the HDU has a standard name (e.g. primary or events), then
this is used. If the HDU has a EXTVER keyword then this number is appended to this name. An extra number is
appended if this name is not unique. If the HDU has no name, then the name used should be ‘hduX’, where X is the
HDU number (0 is the primary HDU).
namemap maps an input dataset (using the scheme above for items) to a Veusz dataset name. Special suffixes can be
used on the Veusz dataset name to indicate that the dataset should be imported specially.
'foo (+)': import as +ve error for dataset foo
'foo (-)': import as -ve error for dataset foo
'foo (+-)': import as symmetric error for dataset foo

slices is an optional dict specifying slices to be selected when importing. For each dataset to be sliced, provide a tuple
of values, one for each dimension. The values should be a single integer to select that index, or a tuple (start, stop,
step), where the entries are integers or None.
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twodranges is an optional dict giving data ranges for 2D datasets. It maps names to (minx, miny, maxx, maxy).
twod_as_oned: optional set containing 2D datasets to attempt to read as 1D, treating extra columns as error bars
wcsmodes is an optional dict specfying the WCS import mode for 2D datasets in HDUs. The keys are ‘/hduname’
and the values can be ‘pixel’: number pixel range from 0 to maximum (default) ‘pixel_wcs’: pixel number relative
to WCS reference pixel ‘linear_wcs’: linear coordinate system from the WCS keywords ‘fraction’: fractional values
from 0 to 1.
renames is an optional dict mapping old to new dataset names, to be renamed after importing
linked specifies that the dataset is linked to the file.
Values under the VEUSZ header keyword can be used to override defaults:
'name': override name for dataset
'slice': slice on importing (use format "start:stop:step,...")
'range': should be 4 item array to specify x and y ranges:
[minx, miny, maxx, maxy]
'xrange' / 'yrange': individual ranges for x and y
'xcent' / 'ycent': arrays giving the centres of pixels
'xedge' / 'yedge': arrays giving the edges of pixels
'twod_as_oned': treat 2d dataset as 1d dataset with errors
'wcsmode': use specific WCS mode for dataset (see values above)
These are specified under the VEUSZ header keyword in the form
KEY=VALUE
or for column-specific values
COLUMNNAME: KEY=VALUE

Returns: list of imported datasets

5.2.25 ImportFileHDF5
ImportFileHDF5(filename, items, namemap={}, slices={}, twodranges={},
twod_as_oned=set([]), convert_datetime={}, prefix='', suffix='', renames={},
linked=False)
Import data from a HDF5 file. items is a list of groups and datasets which can be imported. If a group is imported, all
child datasets are imported. namemap maps an input dataset to a veusz dataset name. Special suffixes can be used on
the veusz dataset name to indicate that the dataset should be imported specially.
'foo (+)': import as +ve error for dataset foo
'foo (-)': import as -ve error for dataset foo
'foo (+-)': import as symmetric error for dataset foo

slices is an optional dict specifying slices to be selected when importing. For each dataset to be sliced, provide a tuple
of values, one for each dimension. The values should be a single integer to select that index, or a tuple (start, stop,
step), where the entries are integers or None.
twodranges is an optional dict giving data ranges for 2d datasets. It maps names to (minx, miny, maxx, maxy).
twod_as_oned: optional set containing 2d datasets to attempt to read as 1d
convert_datetime should be a dict mapping hdf name to specify date/time importing. For a 1d numeric dataset: if this
is set to ‘veusz’, this is the number of seconds since 2009-01-01, if this is set to ‘unix’, this is the number of seconds
since 1970-01-01. For a text dataset, this should give the format of the date/time, e.g. ‘YYYY-MM-DD|T|hh:mm:ss’
or ‘iso’ for iso format.
renames is a dict mapping old to new dataset names, to be renamed after importing. linked specifies that the dataset is
linked to the file.

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Attributes can be used in datasets to override defaults:
'vsz_name': set to override name for dataset in veusz
'vsz_slice': slice on importing (use format "start:stop:step,...")
'vsz_range': should be 4 item array to specify x and y ranges:
[minx, miny, maxx, maxy]
'vsz_twod_as_oned': treat 2d dataset as 1d dataset with errors
'vsz_convert_datetime': treat as date/time, set to one of the values
above.

For compound datasets these attributes can be given on a per-column basis using attribute names
vsz_attributename_columnname.
Returns: list of imported datasets

5.2.26 ImportFileND
def ImportFileND(comm, filename, dataset, shape=None, transpose=False,
mode='text', csvdelimiter=',', csvtextdelimiter='"', csvlocale='en_US',
prefix="", suffix="", encoding='utf_8', linked=False)
Import an n-dimensional dataset from a file. The file should either be in CSV format (mode=’csv’) or whitespaceseparated text (mode=’text’). A one-dimensional dataset is given as a list of numbers on a single line/row. A twodimensional dataset is given by a set of rows. A three-dimensional dataset is given by a set of two-dimensional
datasets, with blank lines between them. a four-dimensional dataset is given by a set of three-dimensional datasets
with two blank lines between each. Each additional dataset increases the separating number of blank lines by one.
Alternatively, the numbers can be given in any form (number of numbers on each row) and “shape” is included to
reshape the data into the desired shape.
In the file, or included as parameters above, the command “shape num1 num2...” can be included to reshape the output
dataset to the shape given by the numbers in the row after “shape” (these should be in separate columns in CSV format).
If one of these numbers is -1, then this dimension is inferred from the number of values and the other dimensions.
Also supported is the “transpose” command or optional argument which reverses the order of the dimensions.

5.2.27 ImportFilePlugin
ImportFilePlugin('pluginname', 'filename', **pluginargs, linked=False,
encoding='utf_8', prefix='', suffix='', renames={})
Import data from file using import plugin ‘pluginname’. The arguments to the plugin are given, plus optionally a
text encoding, and prefix and suffix to prepend or append to dataset names. renames, if set, provides new names for
datasets after import.

5.2.28 ImportFITSFile
ImportFITSFile(datasetname, filename, hdu, datacol='A', symerrcol='B',
poserrcol='C', negerrcol='D', linked=True/False, renames={})
This command is deprecated. Please do not use in new code, but instead use ImportFileFITS.
This command does a simple import from a FITS file. The FITS format is used within the astronomical community to
transport binary data. For a more powerful FITS interface, you can use PyFITS within your scripts.
The datasetname is the name of the dataset to import, the filename is the name of the FITS file to import from. The
hdu parameter specifies the HDU to import data from (numerical or a name).

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If the HDU specified is a primary HDU or image extension, then a two-dimensional dataset is loaded from the file.
The optional parameters (other than linked) are ignored. Any WCS information within the HDU are used to provide a
suitable xrange and yrange.
If the HDU is a table, then the datacol parameter must be specified (and optionally symerrcol, poserrcol and negerrcol).
The dataset is read in from the named column in the table. Any errors are read in from the other specified columns.
If linked is True, then the dataset is not saved with a saved document, but is reread from the data file each time the
document is loaded. renames, if set, provides new names for datasets after import.

5.2.29 ImportString
ImportString('descriptor', 'data')
Like, ImportFile, but loads the data from the specfied string rather than a file. This allows data to be easily embedded
within a document. The data string is usually a multi-line Python string.
Returns: A tuple containing a list of the imported datasets and the number of conversions which failed for a dataset.
Changed in version 0.5: A tuple is returned rather than just the number of imported variables.
ImportString('x y', '''
1
2
2
5
3
10
''')

5.2.30 ImportString2D
ImportString2D(datasets, string, xrange=None, yrange=None, invertrows=None,
invertcols=None, transpose=None)
Imports a two-dimensional dataset from the string given. This is similar to the ImportFile2D command, with the same
dataset format within the string. The optional values are also listed there. The various controlling parameters can be
set within the string. See the ImportFile2D section for details.

5.2.31 ImportStringND
ImportStringND(dataset, string, shape=None, transpose=False)
Imports a n-dimensional dataset from the string given. This is similar to the ImportFileND command. Please look
there for more detail and the description of the optional parameters and in-stream allowed parameters.

5.2.32 IsClosed
IsClosed()
Returns a boolean value telling the caller whether the plotting window has been closed.
Note: this command is only supported in the embedding interface.

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5.2.33 List
List(where='.')
List the widgets which are contained within the widget with the path given, the type of widgets, and a brief description.

5.2.34 Load
Load('filename.vsz')
Loads the veusz script file given. The script file can be any Python code. The code is executed using the Veusz
interpreter.
Note: this command is only supported at the command line and not in a script. Scripts may use the python execfile
function instead.

5.2.35 MoveToPage
MoveToPage(pagenum)
Updates window to show the page number given of the document.
Note: this command is only supported in the embedding interface or veusz –listen.

5.2.36 ReloadData
ReloadData()
Reload any datasets which have been linked to files.
Returns: A tuple containing a list of the imported datasets and the number of conversions which failed for a dataset.

5.2.37 Rename
Remove('widgetpath', 'newname')
Rename the widget at the path given to a new name. This command does not move widgets. See To for a description
of the path syntax. ‘.’ can be used to select the current widget.

5.2.38 Remove
Remove('widgetpath')
Remove the widget selected using the path. See To for a description of the path syntax.

5.2.39 ResizeWindow
ResizeWindow(width, height)
Resizes window to be width by height pixels.
Note: this command is only supported in the embedding interface or veusz –listen.

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5.2.40 Save
Save('filename.vsz')
Save the current document under the filename given.

5.2.41 Set
Set('settingpath', val)
Set the setting given by the path to the value given. If the type of val is incorrect, an InvalidType exception is
thrown. The path to the setting is the optional path to the widget the setting is contained within, an optional subsetting
specifier, and the setting itself.
Set('page1/graph1/x/min', -10.)

5.2.42 SetAntiAliasing
SetAntiAliasing(on)
Enable or disable anti aliasing in the plot window, replotting the image.

5.2.43 SetData
SetData(name, val, symerr=None, negerr=None, poserr=None)
Set the dataset name with the values given. If None is given for an item, it will be left blank. val is the actual data,
symerr are the symmetric errors, negerr and poserr and the getative and positive asymmetric errors. The data can be
given as lists or numpys.

5.2.44 SetDataExpression
SetDataExpression(name, val, symerr=None, negerr=None, poserr=None,
linked=False, parametric=None)
Create a new dataset based on the expressions given. The expressions are Python syntax expressions based on existing
datasets.
If linked is True, the dataset will change as the datasets in the expressions change.
Parametric can be set to a tuple of (minval, maxval, numitems). t in the expression will iterate from minval to maxval
in numitems values.

5.2.45 SetDataND
SetDataRange(name, val)
Set a n-dimensional dataset to be the values given by val. val should be an n-dimensional numpy array of values, or a
list of lists.

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5.2.46 SetDataRange
SetDataRange(name, numsteps, val, symerr=None, negerr=None, poserr=None,
linked=False)
Set dataset to be a range of values with numsteps steps. val is tuple made up of (minimum value, maximum value).
symerr, negerr and poserr are optional tuples for the error bars.
If linked is True, the dataset can be saved in a document as a SetDataRange, otherwise it is expanded to the values
which would make it up.

5.2.47 SetData2D
SetData2D('name', val, xrange=(A,B), yrange=(C,D), xgrid=[1,2,3...], ygrid=[4,
5,6...])
Creates a two-dimensional dataset with the name given. val is either a two-dimensional numpy array, or is a list of
lists, with each list in the list representing a row. Do not give xrange if xgrid is set and do not give yrange if ygrid is
set, and vice versa.
xrange and yrange are optional tuples giving the inclusive range of the X and Y coordinates of the data. xgrid and
ygrid are optional lists, tuples or arrays which give the coordinates of the edges of the pixels. There should be one
more item in each array than pixels.

5.2.48 SetData2DExpression
SetData2DExpression('name', expr, linked=False)
Create a 2D dataset based on expressions. name is the new dataset name expr is an expression which should return a
2D array linked specifies whether to permanently link the dataset to the expressions.

5.2.49 SetData2DExpressionXYZ
SetData2DExpressionXYZ('name', 'xexpr', 'yexpr', 'zexpr', linked=False)
Create a 2D dataset based on three 1D expressions. The x, y expressions need to evaluate to a grid of x, y points, with
the z expression as the 2D value at that point. Currently only linear fixed grids are supported. This function is intended
to convert calculations or measurements at fixed points into a 2D dataset easily. Missing values are filled with NaN.

5.2.50 SetData2DXYFunc
SetData2DXYFunc('name', xstep, ystep, 'expr', linked=False)
Construct a 2D dataset using a mathematical expression of “x” and “y”. The x values are specified as (min, max, step)
in xstep as a tuple, the y values similarly. If linked remains as False, then a real 2D dataset is created, where values
can be modified and the data are stored in the saved file.

5.2.51 SetDataDateTime
SetDataDateTime('name', vals)
Creates a datetime dataset of name given. vals is a list of Python datetime objects.

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5.2.52 SetDataText
SetDataText(name, val)
Set the text dataset name with the values given. val must be a type that can be converted into a Python list.
SetDataText('mylabel', ['oranges', 'apples', 'pears', 'spam'])

5.2.53 SetToReference
SetToReference(setting, refval)
Link setting given to other setting refval.

5.2.54 SetUpdateInterval
SetUpdateInterval(interval)
Tells window to update every interval milliseconds at most. The value 0 disables updates until this function is called
with a non-zero. The value -1 tells Veusz to update the window every time the document has changed. This will make
things slow if repeated changes are made to the document. Disabling updates and using the ForceUpdate command
will allow the user to control updates directly.
Note: this command is only supported in the embedding interface or veusz –listen.

5.2.55 SetVerbose
SetVerbose(v=True)
If v is True, then extra information is printed out by commands.

5.2.56 StartSecondView
StartSecondView(name = 'window title')
In the embedding interface, this method will open a new Embedding interface onto the same document, returning the
object. This new window provides a second view onto the document. It can, for instance, show a different page to the
primary view. name is a window title for the new window.
Note: this command is only supported in the embedding interface.

5.2.57 TagDatasets
TagDatasets('tag', ['ds1', 'ds2'...])
Adds the tag to the list of datasets given..

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5.2.58 To
To('widgetpath')
The To command takes a path to a widget and moves to that widget. For example, this may be “/”, the root widget,
“graph1”, “/page1/graph1/x”, ”../x”. The syntax is designed to mimic Unix paths for files. “/” represents the base
widget (where the pages reside), and ”..” represents the widget next up the tree.

5.2.59 Quit
Quit()
Quits Veusz. This is only supported in veusz –listen.

5.2.60 WaitForClose
WaitForClose()
Wait until the plotting window has been closed.
Note: this command is only supported in the embedding interface.

5.2.61 Zoom
Zoom(factor)
Sets the plot zoom factor, relative to a 1:1 scaling. factor can also be “width”, “height” or “page”, to zoom to the page
width, height or page, respectively.
This is only supported in embedded mode or veusz –listen.

5.3 Security
With the 1.0 release of Veusz, input scripts and expressions are checked for possible security risks. Only a limited subset of Python functionality is allowed, or a dialog box is opened allowing the user to cancel the operation. Specifically
you cannot import modules, get attributes of Python objects, access globals() or locals() or do any sort of file reading
or manipulation. Basically anything which might break in Veusz or modify a system is not supported. In addition
internal Veusz functions which can modify a system are also warned against, specifically Print(), Save() and Export().
If you are running your own scripts and do not want to be bothered by these dialogs, you can run veusz with the
--unsafe-mode option.

5.4 Using Veusz from other programs
5.4.1 Non-Qt Python programs
Veusz can be used as a Python module for plotting data. There are two ways to use the module: (1) with an older
path-based Veusz commands, used in Veusz saved document files or (2) using an object-oriented interface. With the
old style method the user uses a unix-path inspired API to navigate the widget tree and add or manipulate widgets.
With the new style interface, the user navigates the tree with attributes of the Root object to access Nodes. The new
interface is likely to be easier to use unless you are directly translating saved files.

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5.4.2 Older path-based interface
"""An example embedding program. Veusz needs to be installed into
the Python path for this to work (use setup.py)
This animates a sin plot, then finishes
"""
import time
import numpy
import veusz.embed as veusz
# construct a Veusz embedded window
# many of these can be opened at any time
g = veusz.Embedded('window title')
g.EnableToolbar()
# construct the plot
g.To( g.Add('page') )
g.To( g.Add('graph') )
g.Add('xy', marker='tiehorz', MarkerFill__color='green')
# this stops intelligent axis extending
g.Set('x/autoExtend', False)
g.Set('x/autoExtendZero', False)
# zoom out
g.Zoom(0.8)
# loop, changing the values of the x and y datasets
for i in range(10):
x = numpy.arange(0+i/2., 7.+i/2., 0.05)
y = numpy.sin(x)
g.SetData('x', x)
g.SetData('y', y)
# wait to animate the graph
time.sleep(2)
# let the user see the final result
print "Waiting for 10 seconds"
time.sleep(10)
print "Done!"
# close the window (this is not strictly necessary)
g.Close()

The embed interface has the methods listed in the command line interface listed in the Veusz manual https://veusz.
github.io/docs/manual.html
Multiple Windows are supported by creating more than one Embedded object. Other useful methods include:
• WaitForClose() - wait until window has closed
• GetClick() - return a list of (axis, value) tuples where the user clicks on a graph
• ResizeWndow(width, height) - resize window to be width x height pixels
• SetUpdateInterval(interval) - set update interval in ms or 0 to disable

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• MoveToPage(page) - display page given (starting from 1)
• IsClosed() - has the page been closed
• Zoom(factor) - set zoom level (float) or ‘page’, ‘width’, ‘height’
• Close() - close window
• SetAntiAliasing(enable) - enable or disable antialiasing
• EnableToolbar(enable=True) - enable plot toolbar
• StartSecondView(name='Veusz') - start a second view onto the document of the current Embedded
object. Returns a new Embedded object.
• Wipe() - wipe the document of all widgets and datasets.

5.4.3 New-style object interface
In Veusz 1.9 or late a new style of object interface is present, which makes it easier to construct the widget tree. Each
widget, group of settings or setting is stored as a Node object, or its subclass, in a tree. The root document widget can
be accessed with the Root object. The dot operator ”.” finds children inside other nodes. In Veusz some widgets can
contain other widgets (Root, pages, graphs, grids). Widgets contain setting nodes, accessed as attributes. Widgets can
also contain groups of settings, again accessed as attributes.
An example tree for a document (not complete) might look like this
Root
\-- page1
\-- graph1
\-- x
\-- y
\-- function
\-- grid1
\-- graph2
\-- xy1
\-- xData
\-- yData
\-- PlotLine
\-- width
...
...
\-- x
\-- y
\-- graph3
\-- contour1
\-- x
\-- y

(page widget)
(graph widget)
(axis widget)
(axis widget)
(function widget)
(grid widget)
(graph widget)
(xy widget)
(setting)
(setting)
(setting group)
(setting)

(axis widget)
(axis widget)
(graph widget)
(contour widget)
(axis widget)
(axis widget)

Here the user could access the xData setting node of the xy1 widget using Root.page1.graph2.xy1.xData.
To actually read or modify the value of a setting, you should get or set the val property of the setting node. The line
width could be changed like this
graph = embed.Root.page1.graph2
graph.xy1.PlotLine.width.val = '2pt'

For instance, this constructs a simple x-squared plot which changes to x-cubed:

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import veusz.embed as veusz
import time
# open a new window and return a new Embedded object
embed = veusz.Embedded('window title')
# make a new page, but adding a page widget to the root widget
page = embed.Root.Add('page')
# add a new graph widget to the page
graph = page.Add('graph')
# add a function widget to the graph. The Add() method can take a list of settings
# to set after widget creation. Here, "function='x**2'" is equivalent to
# function.function.val = 'x**2'
function = graph.Add('function', function='x**2')
time.sleep(2)
function.function.val = 'x**3'
# this is the same if the widgets have the default names
Root.page1.graph1.function1.function.val = 'x**3'

If the document contains a page called “page1” then Root.page1 is the object representing the page. Similarly,
Root.page1.graph1 is a graph called graph1 in the page. You can also use dictionary-style indexing to get
child widgets, e.g. Root[’page1’][’graph1’]. This style is easier to use if the names of widgets contain spaces or if
widget names shadow methods or properties of the Node object, i.e. if you do not control the widget names.
Widget nodes can contain as children other widgets, groups of settings, or settings. Groups of settings can contain
child settings. Settings cannot contain other nodes. Here are the useful operations of Nodes:
class Node(object):
"""properties:
path - return path to object in document, e.g. /page1/graph1/function1
type - type of node: "widget", "settinggroup" or "setting"
name - name of this node, e.g. "graph1"
children - a generator to return all the child Nodes of this Node, e.g.
for c in Root.children:
print c.path
children_widgets - generator to return child widget Nodes of this Node
children_settinggroups - generator for child setting groups of this Node
children_settings - a generator to get the child settings
childnames - return a list of the names of the children of this Node
childnames_widgets - return a list of the names of the child widgets
childnames_settinggroups - return a list of the names of the setting groups
childnames_settings - return a list of the names of the settings
parent - return the Node corresponding to the parent widget of this Node
__getattr__ - get a child Node with name given, e.g. Root.page1
__getitem__ - get a child Node with name given, e.g. Root['page1']
"""
def fromPath(self, path):
"""Returns a new Node corresponding to the path given, e.g. '/page1/graph1'"""
class SettingNode(Node):
"""A node which corresponds to a setting. Extra properties:
val - get or set the setting value corresponding to this value, e.g.
Root.page1.graph1.leftMargin.val = '2cm'
"""
class SettingGroupNode(Node):

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"""A node corresponding to a setting group. No extra properties."""
class WidgetNode(Node):
"""A node corresponding to a widget.
property:
widgettype - get Veusz type of widget
Methods are below."""
def WalkWidgets(self, widgettype=None):
"""Generator to walk widget tree and get widgets below this
WidgetNode of type given.
widgettype is a Veusz widget type name or None to get all
widgets."""
def Add(self, widgettype, *args, **args_opt):
"""Add a widget of the type given, returning the Node instance.
"""
def Rename(self, newname):
"""Renames widget to name given.
Existing Nodes corresponding to children are no longer valid."""
def Action(self, action):
"""Applies action on widget."""
def Remove(self):
"""Removes a widget and its children.
Existing Nodes corresponding to children are no longer valid."""

Note that Nodes are temporary objects which are created on the fly. A real widget in Veusz can have several different
WidgetNode objects. The operators == and != can test whether a Node points to the same widget, setting or setting
group.
Here is an example to set all functions in the document to be x**2:
for n in Root.WalkWidgets(widgettype='function'):
n.function.val = 'x**2'

5.4.4 Translating old to new style
Here is an example how you might translate the old to new style interface (this is taken from the sin.vsz example).
# old (from saved document file)
Add('page', name='page1')
To('page1')
Add('graph', name='graph1', autoadd=False)
To('graph1')
Add('axis', name='x')
To('x')
Set('label', '\\\\italic{x}')
To('..')
Add('axis', name='y')
To('y')

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Set('label', 'sin \\\\italic{x}')
Set('direction', 'vertical')
To('..')
Add('xy', name='xy1')
To('xy1')
Set('MarkerFill/color', 'cyan')
To('..')
Add('function', name='function1')
To('function1')
Set('function', 'sin(x)')
Set('Line/color', 'red')
To('..')
To('..')
To('..')
# new (in python)
import veusz.embed
embed = veusz.embed.Embedded('window title')
page = embed.Root.Add('page')
# note: autoAdd=False stops graph automatically adding own axes (used in saved files)
graph = page.Add('graph', autoadd=False)
x = graph.Add('axis', name='x')
x.label.val = '\\\\italic{x}'
y = graph.Add('axis', name='y')
y.direction.val = 'vertical'
xy = graph.Add('xy')
xy.MarkerFill.color.val = 'cyan'
func = graph.Add('function')
func.function.val = 'sin(x)'
func.Line.color.val = 'red'

PyQt programs
There is no direct PyQt interface. The standard embedding interface should work, however.
Non Python programs
Support for non Python programs is available in a limited form. External programs may execute Veusz using veusz
--listen. Veusz will read its input from the standard input, and write output to standard output. This is a full Python
execution environment, and supports all the scripting commands mentioned in Commands, a Quit() command, the
EnableToolbar() and the Zoom(factor) command listed above. Only one window is supported at once, but
many veusz --listen programs may be started.
veusz --listen may be used from the shell command line by doing something like:
veusz --listen < in.vsz

where in.vsz contains:
To(Add('page') )
To(Add('graph') )
SetData('x', arange(20))
SetData('y', arange(20)**2)
Add('xy')

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Zoom(0.5)
Export("foo.pdf")
Quit()

A program may interface with Veusz in this way by using the popen C Unix function, which allows a program to be
started having control of its standard input and output. Veusz can then be controlled by writing commands to an input
pipe.

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CHAPTER

SIX

INDICES AND TABLES

• genindex
• modindex
• search

47



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