Commit 55a0d7b2 authored by Valentin Valls's avatar Valentin Valls
Browse files

Update the documentation

parent d4bdecbe
...@@ -16,37 +16,10 @@ This Qt application is started automatically when a new plot is created. ...@@ -16,37 +16,10 @@ This Qt application is started automatically when a new plot is created.
This interface supports several types of plot: This interface supports several types of plot:
- **curve plot**: - **curve plot**:
* plotting one or several 1D data as curves
* Optional x-axis data can be provided
* the plot is created using ``plot_curve``
- **scatter plot**: - **scatter plot**:
* plotting one or several scattered data
* each scatter is a group of three 1D data of same length
* the plot is created using ``plot_scatter``
- **image plot**: - **image plot**:
* plot one or several image on top of each other
* the image order can be controlled using a depth parameter
* the plot is created using ``plot_image``
- **image + histogram plot**:
* plot a single 2D image (greyscale or colormap)
* two histograms along the X and Y dimensions are displayed
* the plot is created using ``plot_image_with_histogram``
- **image stack plot**: - **image stack plot**:
- And few others
* plot a single stack of image
* a slider is provided to browse the images
* the plot is created using ``plot_image_stack``
An extra helper called ``plot`` is provided to automatically infer
a suitable type of plot from the data provided.
Basic interface Basic interface
--------------- ---------------
...@@ -59,80 +32,14 @@ as an argument and return a plot: ...@@ -59,80 +32,14 @@ as an argument and return a plot:
>>> plot(mydata, name="My plot") >>> plot(mydata, name="My plot")
ImagePlot(plot_id=1, flint_pid=17450) ImagePlot(plot_id=1, flint_pid=17450)
Extra keyword arguments are forwarded to silx:
>>> p = plot(mydata, xlabel='A', ylabel='b')
From then on, all the interaction with the corresponding plot window goes
through the plot object. For instance, it provides a ``plot`` method
to add and display extra data:
>>> p.plot(some_extra_data, yaxis='right')
Advanced interface Advanced interface
------------------ ------------------
For a finer control over the plotted data, the data management is There is way to have finer control of the plot content, especially to create
separated from the plot management. In order to add more data to plot containing many curves.
the plot, use the following interface:
>>> p.add_data(cos_data, field='cos')
This data is now identified using its field, ``'cos'``. A dict or
a structured numpy array can also be provided. In this case,
the fields of the provided data structure are used as identifiers:
>>> p.add_data({'cos': cos_data, 'sin': sin_data})
The plot selection is then done through the ``select_data`` method.
For a curve plot, the expected arguments are the names of the data
to use for X and Y:
>>> p.select_data('sin', 'cos')
Again, the extra keyword arguments will be forwarded to silx:
>>> p.select_data('sin', 'cos', color='green', symbol='x')
The curve can then be deselected:
>>> p.deselect_data('sin', 'cos')
And the data can be cleared:
>>> p.clear_data()
Plot interaction
In order to interact with a given plot, several methods are provided.
The ``select_points`` method allows the user to select a given number of point
on the corresponding plot using their mouse.
>>> a, b, c = p.select_points(3)
# Blocks until the user selects the 3 points
>>> a
(1.2, 3.4)
The ``select_shape`` methods allows the user to select a given shape on the
corresponding plot using their mouse. The available shapes are:
- ``'rectangle'``: rectangle selection
- ``'line'``: line selection
- ``'hline'``: horizontal line selection
- ``'vline'``: vertical line selection
- ``'polygon'``: polygon selection
The return values are shown in the following example:
>>> topleft, bottomright = p.select_shape('rectangle') See the `online BLISS documentation <>`
>>> start, stop = p.select_shape('line') for detailed explanation and examples.
>>> left, right = p.select_shape('hline')
>>> bottom, top = p.select_shape('vline')
>>> points = p.select_shape('polygon')
""" """
from typing import List from typing import List
...@@ -104,6 +104,63 @@ p = f.get_plot("curve", name="My heart") ...@@ -104,6 +104,63 @@ p = f.get_plot("curve", name="My heart")
p.add_curve(x, y, legend="heart") p.add_curve(x, y, legend="heart")
``` ```
## Descriptive 1D plot
The 1D plot also provides a descriptive mode. In this mode, there is a separation
between the data and the way it is rendered.
The description of the rendering is done by a layer of items. First this
description have to be provided, then the data can be set.
When data for axis are shared, it's also a convenient way to only transfer data
import numpy
# Create the plot
f = flint()
p = f.get_plot("curve", name="My plot")
# Create the data
t = numpy.linspace(0, 10 * numpy.pi, 100)
s1 = numpy.sin(t)
s2 = numpy.sin(t + numpy.pi * 0.5)
s3 = numpy.sin(t + numpy.pi * 1.0)
s4 = numpy.sin(t + numpy.pi * 1.5)
# Describe the plot
p.add_curve_item("t", "s1")
p.add_curve_item("t", "s2")
p.add_curve_item("t", "s3")
p.add_curve_item("t", "s4")
# Transfer the data / and update the plot
p.set_data(t=t, s1=s1, s2=s2, s3=s3, s4=s4)
# As the plot description is already known
# Theplot can be updated the same way again
p.set_data(t=t+1, s1=s1+1, s2=s2+1, s3=s3+1, s4=s4+1)
# Clean up the plot
For complex plot, if you want to handle properly the refresh of the plot
a transaction can be used. It will enforce a signle update of the plot at the
end of the transaction.
with p.transaction():
p.add_curve_item("x", "y", legend="item1")
p.add_curve_item("x", "w", legend="item2")
p.append_data(x=[2, 3, 4, 5])
p.set_data(y=[6, 5, 6, 5, 6])
## Scatter plot ## Scatter plot
A 2D scatter plot is provided. A 2D scatter plot is provided.
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