silx.sx
: Using silx from Python Interpreter¶
This is a convenient package to use from Python or IPython interpreter. It loads the main features of silx and provides high-level functions.
>>> from silx import sx
When used in an interpreter is sets-up Qt and loads some silx widgets. In a jupyter / IPython notebook, to set-up Qt and loads silx widgets, you must then call:
>>> sx.enable_gui()
When used in IPython, it also runs %pylab
,
thus importing numpy and
matplotlib.
Plot functions¶
The following functions plot curves and images with silx widgets:
The ginput()
function handles user selection on those widgets.
Note
Those functions are not available from a notebook.
plot()
¶
-
plot
(*args, **kwargs)[source]¶ Plot curves in a
Plot1D
widget.How to use:
>>> from silx import sx >>> import numpy
Plot a single curve given some values:
>>> values = numpy.random.random(100) >>> plot_1curve = sx.plot(values, title='Random data')
Plot a single curve given the x and y values:
>>> angles = numpy.linspace(0, numpy.pi, 100) >>> sin_a = numpy.sin(angles) >>> plot_sinus = sx.plot(angles, sin_a, xlabel='angle (radian)', ylabel='sin(a)')
Plot many curves by giving a 2D array, provided xn, yn arrays:
>>> plot_curves = sx.plot(x0, y0, x1, y1, x2, y2, ...)
Plot curve with style giving a style string:
>>> plot_styled = sx.plot(x0, y0, 'ro-', x1, y1, 'b.')
Supported symbols:
- ‘o’ circle
- ‘.’ point
- ‘,’ pixel
- ‘+’ cross
- ‘x’ x-cross
- ‘d’ diamond
- ‘s’ square
Supported types of line:
- ‘ ‘ no line
- ‘-‘ solid line
- ‘–’ dashed line
- ‘-.’ dash-dot line
- ‘:’ dotted line
If provided, the names arguments color, linestyle, linewidth and marker override any style provided to a curve.
This function supports a subset of matplotlib.pyplot.plot arguments.
Parameters: - color (str) – Color to use for all curves (default: None)
- linestyle (str) – Type of line to use for all curves (default: None)
- linewidth (float) – With of all the curves (default: 1)
- marker (str) – Symbol to use for all the curves (default: None)
- title (str) – The title of the Plot widget (default: None)
- xlabel (str) – The label of the X axis (default: None)
- ylabel (str) – The label of the Y axis (default: None)
Returns: The widget plotting the curve(s)
Return type: silx.gui.plot.Plot1D
imshow()
¶
-
imshow
(data=None, cmap=None, norm='linear', vmin=None, vmax=None, aspect=False, origin='upper', scale=(1.0, 1.0), title='', xlabel='X', ylabel='Y')[source]¶ Plot an image in a
Plot2D
widget.How to use:
>>> from silx import sx >>> import numpy
>>> data = numpy.random.random(1024 * 1024).reshape(1024, 1024) >>> plt = sx.imshow(data, title='Random data')
By default, the image origin is displayed in the upper left corner of the plot. To invert the Y axis, and place the image origin in the lower left corner of the plot, use the origin parameter:
>>> plt = sx.imshow(data, origin='lower')
This function supports a subset of matplotlib.pyplot.imshow arguments.
Parameters: - data (numpy.ndarray-like with 2 dimensions) – data to plot as an image
- cmap (str) – The name of the colormap to use for the plot. It also supports a numpy array containing a RGB LUT, or a colors.Colormap instance.
- norm (str) – The normalization of the colormap: ‘linear’ (default) or ‘log’
- vmin (float) – The value to use for the min of the colormap
- vmax (float) – The value to use for the max of the colormap
- aspect (bool) – True to keep aspect ratio (Default: False)
- origin (str or 2-tuple of floats) – Either image origin as the Y axis orientation: ‘upper’ (default) or ‘lower’ or the coordinates (ox, oy) of the image origin in the plot.
- scale (2-tuple of floats) – (sx, sy) The scale of the image in the plot (i.e., the size of the image’s pixel in plot coordinates)
- title (str) – The title of the Plot widget
- xlabel (str) – The label of the X axis
- ylabel (str) – The label of the Y axis
Returns: The widget plotting the image
Return type: silx.gui.plot.Plot2D
scatter()
¶
-
scatter
(x=None, y=None, value=None, size=None, marker=None, cmap=None, norm='linear', vmin=None, vmax=None)[source]¶ Plot scattered data in a
ScatterView
widget.How to use:
>>> from silx import sx >>> import numpy
>>> x = numpy.random.random(100) >>> y = numpy.random.random(100) >>> values = numpy.random.random(100) >>> plt = sx.scatter(x, y, values, cmap='viridis')
Supported symbols:
- ‘o’ circle
- ‘.’ point
- ‘,’ pixel
- ‘+’ cross
- ‘x’ x-cross
- ‘d’ diamond
- ‘s’ square
This function supports a subset of matplotlib.pyplot.scatter arguments.
Parameters: - x (numpy.ndarray) – 1D array-like of x coordinates
- y (numpy.ndarray) – 1D array-like of y coordinates
- value (numpy.ndarray) – 1D array-like of data values
- size (float) – Size^2 of the markers
- marker (str) – Symbol used to represent the points
- cmap (str) – The name of the colormap to use for the plot
- norm (str) – The normalization of the colormap: ‘linear’ (default) or ‘log’
- vmin (float) – The value to use for the min of the colormap
- vmax (float) – The value to use for the max of the colormap
Returns: The widget plotting the scatter plot
Return type:
ginput()
¶
-
ginput
(n=1, timeout=30, plot=None)[source]¶ Get input points on a plot.
If no plot is provided, it uses a plot widget created with either
silx.sx.plot()
orsilx.sx.imshow()
.How to use:
>>> from silx import sx
>>> sx.imshow(image) # Plot the image >>> sx.ginput(1) # Request selection on the image plot ((0.598, 1.234))
How to get more information about the selected positions:
>>> positions = sx.ginput(1)
>>> positions[0].getData() # Returns value(s) at selected position
>>> positions[0].getIndices() # Returns data indices at selected position
>>> positions[0].getItem() # Returns plot item at selected position
Parameters: - n (int) – Number of points the user need to select
- timeout (float) – Timeout in seconds before ginput returns event if selection is not completed
- plot (silx.gui.plot.PlotWidget.PlotWidget) – An optional PlotWidget from which to get input
Returns: List of clicked points coordinates (x, y) in plot
Raises: ValueError – If provided plot is not a PlotWidget
3D plot functions¶
The following functions plot 3D data with silx widgets (it requires OpenGL):
contour3d()
for isosurfaces (and cut plane) in a 3D scalar fieldpoints3d()
for 2D/3D scatter plots
Note
Those functions are not available from a notebook.
contour3d()
¶
-
contour3d
(scalars, contours=1, copy=True, color=None, colormap='viridis', vmin=None, vmax=None, opacity=1.0)[source]¶ Plot isosurfaces of a 3D scalar field in a
ScalarFieldView
widget.How to use:
>>> from silx import sx
Provided data, a 3D scalar field as a numpy array of float32:
>>> plot3d_window = sx.contour3d(data)
Alternatively you can provide the level of the isosurfaces:
>>> plot3d_window = sx.contour3d(data, contours=[0.2, 0.4])
This function provides a subset of mayavi.mlab.contour3d arguments.
Parameters: - scalars (numpy.ndarray of float32 with 3 dimensions) – The 3D scalar field to visualize
- contours (Union[int, float, List[float]]) – Either the number of isosurfaces to draw (as an int) or the isosurface level (as a float) or a list of isosurface levels (as a list of float)
- copy (bool) – True (default) to make a copy of scalars. False to avoid this copy (do not modify provided data afterwards)
- color – Color.s to use for isosurfaces. Either a single color or a list of colors (one for each isosurface). A color can be defined by its name (as a str) or as RGB(A) as float or uint8.
- colormap (str) – If color is not provided, this colormap is used for coloring isosurfaces.
- vmin (Union[float, None]) – Minimum value of the colormap
- vmax (Union[float, None]) – Maximum value of the colormap
- opacity (float) – Transparency of the isosurfaces as a float in [0., 1.]
Returns: The widget used to visualize the data
Return type:
points3d()
¶
-
points3d
(x, y, z=None, values=0.0, copy=True, colormap='viridis', vmin=None, vmax=None, mode=None)[source]¶ Plot a 3D scatter plot in a
SceneWindow
widget.How to use:
>>> from silx import sx
Provided x, y, z, values, 4 numpy array of float32:
>>> plot3d_window = sx.points3d(x, y, z)
>>> plot3d_window = sx.points3d(x, y, z, values)
This function provides a subset of mayavi.mlab.points3d arguments.
Parameters: - x (numpy.ndarray) – X coordinates of the points
- y (numpy.ndarray) – Y coordinates of the points
- z (numpy.ndarray) – Z coordinates of the points (optional)
- values (numpy.ndarray) – Values at each point (optional)
- copy (bool) – True (default) to make a copy of scalars. False to avoid this copy (do not modify provided data afterwards)
- colormap (str) – Colormap to use for coding points as colors.
- vmin (Union[float, None]) – Minimum value of the colormap
- vmax (Union[float, None]) – Maximum value of the colormap
- mode (str) –
The type of marker to use
- Circle: ‘o’, ‘2dcircle’
- Diamond: ‘d’, ‘2ddiamond’
- Square: ‘s’, ‘2dsquare’
- Plus: ‘+’
- Cross: ‘x’, ‘2dcross’
- Star: ‘*’
- Vertical line: ‘|’
- Horizontal line: ‘_’, ‘2ddash’
- Point: ‘.’
- Pixel: ‘,’
Returns: The widget used to visualize the data
Return type:
Widgets¶
The widgets of the silx.gui.plot
package are also exposed in this package.
See silx.gui.plot
for documentation.
Input/Output¶
The content of the silx.io
package is also exposed in this package.
See silx.io
for documentation.