python-chaco 4.5.0-1 / usr / lib / python2.7 / dist-packages / chaco / shell / commands.py

""" Defines commands for the Chaco shell.
"""

try:
    from wx import GetApp
except ImportError:
    GetApp = lambda: None

from chaco.api import Plot, color_map_name_dict
from chaco.scales.api import ScaleSystem
from chaco.tools.api import PanTool, ZoomTool

# Note: these are imported to be exposed in the namespace.
from chaco.scales.api import (FixedScale, Pow10Scale, LogScale,
    CalendarScaleSystem)
from chaco.default_colormaps import *

import plot_maker
from session import PlotSession

session = PlotSession()


#------------------------------------------------------------------------
# General help commands
#------------------------------------------------------------------------

def chaco_commands():
    """
    Prints the current list of all shell commands.  Information
    on each command is available in that command's docstring (__doc__).

    Window/Plot Management
    ----------------------
    figure
        creates a new figure window
    activate
        activates an existing window or plot
    close
        closes a window
    curplot
        returns a reference to the active window's Plot object
    show
        starts the GUI and displays windows (should only be used in scripts)

    Plotting
    --------
    plot
        plots some data
    imread
        creates an array from an image file on disk
    imshow
        creates an image plot from a file on disk
    pcolor
        plots some scalar data as a pseudocolor image
    contour
        creates a contour line plot of some scalar data
    contourf
        creates a contour poly plot of some scalar data
    loglog
        plots an x-y line or scatter plot on log-log scale
    semilogx
        plots an x-y line or scatter plot with a log x-scale
    semilogy
        plots an x-y line or scatter plot with a log y-scale
    hold
        turns "hold" on or off
    show
        shows plot on screen; used when running from script


    Axes, Annotations, Legends
    --------------------------
    xaxis
        toggles the horizontal axis, sets the interval
    yaxis
        toggles the vertical axis, sets the interval
    xgrid
        toggles the grid running along the X axis
    ygrid
        toggles the grid running along the Y axis
    xtitle
        sets the title of a horizontal axis
    ytitle
        sets the title of a vertical axis
    xscale
        sets the tick scale system of the X axis
    yscale
        sets the tick scale system of the Y axis
    title
        sets the title of the plot


    Tools
    -----
    colormap
        sets the current colormap

    IO
    --
    save
        saves the current plot to a file (png, bmp, jpg, pdf)
    """
    print chaco_commands.__doc__

    # The following are not implemented yet
    """
    tool -- toggles certain tools on or off
    load -- loads a saved plot from file into the active plot area
    scatter -- plots some data as a scatterplot (unordered X/Y data)
    line -- plots some data as an ordered set of of X,Y points
    label -- adds a label at a data point
    legend -- creates a legend and adds it to the plot

    Layout
    ------
    names -- temporarily overlays plot areas with their names
    hidenames -- force remove the name overlays from show_names
    happend -- create a new plot area horizontally after the active plot
    vappend -- create a new plot area vertically after the active plot
    hsplit -- splits the current plot into two horizontal subplots
    vsplit -- splits the current plot into two vertical subplots
    save_layout -- saves the current layout of plots and plots areas
    load_layout -- loads a saved layout of plot areas and applies it to the
                   current set of plots

    Sessions
    --------
    save_session -- saves the current "workspace", defined as the set of
                    active windows and plots
    load_session -- restores a previously-saved session
    save_prefs -- saves the current session's preferences, either in a
                  separate file or as the chaco.shell defaults
    load_prefs -- loads a previously-saved set of preferences
    """

#------------------------------------------------------------------------
# Window management commands
#------------------------------------------------------------------------

def figure(name=None, title=None):
    """ Creates a new figure window and returns its index.

    Parameters
    ----------
    name : string
        The name to use for this window. If this parameter is provided, then
        this name can be used instead of the window's integer index in other
        window-related functions.
    title : string
        The title of the plot window. If this is blank but *name* is provided,
        then that is used. If neither *name* nor *title* is provided, then the
        method uses the value of default_window_name in the Preferences.
    """
    win = session.new_window(name, title)
    activate(win)
    return win


def activate(ident=None):
    """ Activates and raises a figure window.

    Parameters
    ----------
    ident : integer or string
        Index or name of the window.  If neither is specified,
        then the function raises the currently active window.
    """
    if ident is not None:
        win = session.get_window(ident)
    else:
        win = session.active_window

    if win is not None:
        session.active_window = win
        win.raise_window()
    return

def show():
    """ Shows all the figure windows that have been created thus far, and
    creates a GUI main loop. This function is useful in scripts to show plots
    and keep their windows open, and has no effect when used from the
    interpreter prompt.
    """

    from traits.etsconfig.api import ETSConfig
    from pyface.util import guisupport
    is_event_loop_running = getattr(guisupport, 'is_event_loop_running_' + ETSConfig.toolkit)
    start_event_loop = getattr(guisupport, 'start_event_loop_' + ETSConfig.toolkit)

    if not is_event_loop_running():
        frame = session.active_window
        frame.raise_window()
        start_event_loop()
    return


def close(ident=None):
    """ Closes a figure window

    Parameters
    ----------
    ident : integer or string
        Index or name of the window to close, or "all".  If nothing
        is specified, then the function closes the active window.
    """
    win_list = []
    if ident is None:
        win_list.append(session.active_window)
    elif ident == 'all':
        win_list = session.windows
    else:
        win_list.append(session.get_window(ident))

    for win in win_list:
        win.close()
    return

def colormap(map):
    """Sets the active colormap.

    Parameters
    ----------
    map : a string, or a callable
         The color map to use; if it is a string, it is the name of a default
         colormap; if it is a callable, it must return an AbstractColorMap.
    """
    if isinstance(map, basestring):
        session.colormap = color_map_name_dict[map]
    else:
        session.colormap = map


def hold(state=None):
    """ Turns "hold" on or off, or toggles the current state if none
    is given.

    Parameters
    ----------
    state : Boolean
        The desired hold state.
    """
    if state is None:
        session.hold = not session.hold
    else:
        session.hold = state
    return

def curplot():
    if session.active_window:
        return session.active_window.get_container()
    else:
        return None

#------------------------------------------------------------------------
# Plotting functions
#------------------------------------------------------------------------

def _do_plot_boilerplate(kwargs, image=False):
    """ Used by various plotting functions.  Checks/handles hold state,
    returns a Plot object for the plotting function to use.
    """

    if kwargs.has_key("hold"):
        hold(kwargs["hold"])
        del kwargs["hold"]

    # Check for an active window; if none, open one.
    if len(session.windows) == 0:
        if image:
            win = session.new_window(is_image=True)
            activate(win)
        else:
            figure()

    cont = session.active_window.get_container()

    if not cont:
        cont = Plot(session.data)
        session.active_window.set_container(cont)

    existing_tools = [type(t) for t in (cont.tools + cont.overlays)]
    if not PanTool in existing_tools:
        cont.tools.append(PanTool(cont))
    if not ZoomTool in existing_tools:
        cont.overlays.append(ZoomTool(cont, tool_mode="box", always_on=True, drag_button="right"))

    if not session.hold:
        cont.delplot(*cont.plots.keys())

    return cont


def plot(*data, **kwargs):
    """ Plots data in a Matlab-compatible way.  Data is assumed to be
    X vs Y.  Any additional *kwargs* passed in are broadcast to all plots.

    Example::

        x = arange(-pi, pi, pi/100.)
        plot(x, sin(x), "b-")

    To use previous data, specify names instead of actual data arrays.
    """

    cont = _do_plot_boilerplate(kwargs)

    plots = plot_maker.do_plot(session.data, cont,
                               *data, **kwargs)

    cont.request_redraw()
    return


def semilogx(*data, **kwargs):
    """ Plots data on a semilog scale in a Matlab-compatible way.  Data is
    assumed to be X vs Y.  Any additional *kwargs* passed in are broadcast
    to all plots.

    Example::

        x = linspace(0.01, 10.0 100)
        semilogx(x, sqrt(x), "b-")

    To use previous data, specify names instead of actual data arrays.

    Adding a semilog plot to an active plot with a currently different scale
    rescales the plot.
    """
    kwargs["index_scale"] = "log"
    plot(*data, **kwargs)


def semilogy(*data, **kwargs):
    """ Plots data on a semilog scale in a Matlab-compatible way.  Data is
    assumed to be X vs Y.  Any additional *kwargs* passed in are broadcast
    to all plots.

    Example::

        x = linspace(0, 10.0, 100)
        semilogy(x, exp(x), "b-")

    To use previous data, specify names instead of actual data arrays.

    Adding a semilog plot to an active plot with a currently different scale
    rescales the plot.
    """
    kwargs["value_scale"] = "log"
    plot(*data, **kwargs)


def loglog(*data, **kwargs):
    """ Plots data on a log-log scale in a Matlab-compatible way.  Data is
    assumed to be X vs Y.  Any additional *kwargs* passed in are broadcast
    to all plots.

    Example::

        x = linspace(0.001, 10.0, 100)
        loglog(x, x**2, "b-")

    To use previous data, specify names instead of actual data arrays.

    Adding a log-log plot to an active plot with a currently different scale
    rescales the plot.
    """
    kwargs["index_scale"] = "log"
    kwargs["value_scale"] = "log"
    plot(*data, **kwargs)


def imread(*data, **kwargs):
    """ Returns image file as an array. """

    return plot_maker.do_imread(*data, **kwargs)


def imshow(*data, **kwargs):
    """ Creates an image plot from a file on disk.  Takes either
    filename or image data.  Any additional *kwargs* passed in are broadcast
    to all plots.

    Example 1::

        imshow("example.jpg")

    Example 2::

        image = ImageData.fromfile("example.jpg")
        imshow(image)

    To use previous data, specify names instead of filename or data arrays.

    """

    cont = _do_plot_boilerplate(kwargs, image=True)

    if "colormap" not in kwargs:
        kwargs["colormap"] = session.colormap
    plots = plot_maker.do_imshow(session.data, cont,
                                 *data, **kwargs)
    cont.request_redraw()
    return


def pcolor(*data, **kwargs):
    """ Colormaps scalar data in a roughly Matlab-compatible way. Data are
    assumed to be a scalar image.  Any additional *kwargs* passed in are
    broadcast to all plots.

    Example::

        xs = linspace(0,10,100)
        ys = linspace(0,20,200)
        x,y=meshgrid(xs,ys)
        z = sin(x)*y
        pcolor(x, y, z)

    To use previous data, specify names instead of actual data arrays.
    """

    cont = _do_plot_boilerplate(kwargs)

    plots = plot_maker.do_pcolor(session.data, session.colormap, cont,
                                 *data, **kwargs)
    cont.request_redraw()
    return



def contour(*data, **kwargs):
    """ Contour line plots of scalar data in a roughly Matlab-compatible way.
    Data are assumed to be a scalar image.  Any additional *kwargs* passed in
    are broadcast to all plots.

    Example::

        xs = linspace(0,10,100)
        ys = linspace(0,20,200)
        x,y=meshgrid(xs,ys)
        z = sin(x)*y
        contour(z)

    To use previous data, specify names instead of actual data arrays.
    """

    cont = _do_plot_boilerplate(kwargs)

    plots = plot_maker.do_contour(session.data, session.colormap, cont,
                                  "line", *data, **kwargs)
    cont.request_redraw()
    return



def contourf(*data, **kwargs):
    """ Contour polygon plots of scalar data in a roughly Matlab-compatible way.
    Data are assumed to be a scalar image.  Any additional *kwargs* passed in
    are broadcast to all plots.

    Example::

        xs = linspace(0,10,100)
        ys = linspace(0,20,200)
        x,y=meshgrid(xs,ys)
        z = sin(x)*y
        contourf(z)

    To use previous data, specify names instead of actual data arrays.
    """

    cont = _do_plot_boilerplate(kwargs)

    plots = plot_maker.do_contour(session.data, session.colormap, cont,
                                  "poly", *data, **kwargs)
    cont.request_redraw()
    return



def plotv(*args, **kwargs):
    """ Creates a plot of a particular type, or using a "best guess"
    approach based on the data, using chaco semantics.

    The number and shape of data arrays determine how the data is
    interpreted, and how many plots are created.

    Single-dimensional arrays (shape = (N,))
    ----------------------------------------
    1. Single array: the data is treated as the value array, and an index
       array is generated automatically using arange(len(value))
    2. Multiple arrays: the first array is treated as the index array, and
       each subsequent array is used as the value for a new plot.  All of
       the plots share a common index (first array).

    Multi-dimensional arrays (shape = (N,2) or (2,N))
    -------------------------------------------------
    1. Single array (NxM or MxN, N > M): interpreted as M-1 plots of
       N data points each, just like in the multiple 1D array case above.
    2. Multiple arrays: each array is treated as a separate set of inter-
       related plots, with its own index and value data sources

    Keyword Arguments
    -----------------
    type
        comma-separated combination of "line", "scatter", "polar"
    sort
        "ascending", "descending", or "none", indicating the sorting order
        of the array that will be used as the index
    color
        the color of the plot line and/or marker
    bgcolor
        the background color of the plot
    grid
        boolean specifying whether or not to draw a grid on the plot
    axis
        boolean specifying whether or not to draw an axis on the plot
    orientation
        "h" for index on the X axis, "v" for index on the Y axis

    Scatter plot keywords
    ---------------------
    marker
        the type of marker to use (square, diamond, circle, cross,
        crossed circle, triangle, inverted triangle, plus, dot, pixel
    marker_size
        the size (in pixels) of the marker
    outline_color
        the color of the marker outline

    Line plot keywords
    ------------------
    width
        the thickness of the line
    dash
        the dash style to use (solid, dot dash, dash, dot, long dash)
    """

    cont = _do_plot_boilerplate(kwargs)
    plots = plot_maker.do_plotv(session, *args, **kwargs)
    cont.add(*plots)
    cont.request_redraw()
    return


#-----------------------------------------------------------------------------
# Annotations
#-----------------------------------------------------------------------------

def xtitle(text):
    """ Sets the horizontal axis label to *text*. """
    p = curplot()
    if p:
        p.x_axis.title = text
        p.request_redraw()


def ytitle(text):
    """ Sets the vertical axis label to *text*. """
    p = curplot()
    if p:
        p.y_axis.title = text
        p.request_redraw()

def title(text):
    """ Sets the plot title to *text*. """
    p = curplot()
    if p:
        p.title = text
        p.request_redraw()

_axis_params = """Parameters
    ----------
    title : str
        The text of the title
    title_font : KivaFont('modern 12')
        The font in which to render the title
    title_color : color ('color_name' or (red, green, blue, [alpha]) tuple)
        The color in which to render the title
    tick_weight : float
        The thickness (in pixels) of each tick
    tick_color : color ('color_name' or (red, green, blue, [alpha]) tuple)
        The color of the ticks
    tick_label_font : KivaFont('modern 10')
        The font in which to render the tick labels
    tick_label_color : color ('color_name' or (red, green, blue, [alpha]) tuple)
        The color of the tick labels
    tick_label_formatter : callable
        A callable that is passed the numerical value of each tick label and
        which should return a string.
    tick_in : int
        The number of pixels by which the ticks go "into" the plot area
    tick_out : int
        The number of pixels by which the ticks extend into the label area
    tick_visible : bool
        Are ticks visible at all?
    tick_interval : 'auto' or float
        What is the dataspace interval between ticks?
    orientation : Enum("top", "bottom", "left", "right")
        The location of the axis relative to the plot.  This determines where
        the axis title is located relative to the axis line.
    axis_line_visible : bool
        Is the axis line visible?
    axis_line_color : color ('color_name' or (red, green, blue, [alpha]) tuple)
        The color of the axis line
    axis_line_weight : float
        The line thickness (in pixels) of the axis line
    axis_line_style : LineStyle('solid')
        The dash style of the axis line"""

def xaxis(**kwds):
    """ Configures the x-axis.

    Usage
    -----
    * ``xaxis()``: toggles the horizontal axis on or off.
    * ``xaxis(**kwds)``: set parameters of the horizontal axis.

    %s
    """ % _axis_params
    p = curplot()
    if p:
        if kwds:
            p.x_axis.set(**kwds)
        else:
            p.x_axis.visible ^= True
        p.request_redraw()

xaxis.__doc__ = """ Configures the x-axis.

    Usage
    -----
    * ``xaxis()``: toggles the horizontal axis on or off.
    * ``xaxis(**kwds)``: set parameters of the horizontal axis.

    %s
    """ % _axis_params

def yaxis(**kwds):
    """ Configures the y-axis.

    Usage
    -----
    * ``yaxis()``: toggles the vertical axis on or off.
    * ``yaxis(**kwds)``: set parameters of the vertical axis.

    %s
    """ % _axis_params
    p = curplot()
    if p:
        if kwds:
            p.y_axis.set(**kwds)
        else:
            p.y_axis.visible ^= True
        p.request_redraw()

yaxis.__doc__ =     """ Configures the y-axis.

    Usage
    -----
    * ``yaxis()``: toggles the vertical axis on or off.
    * ``yaxis(**kwds)``: set parameters of the vertical axis.

    %s
    """ % _axis_params


def xgrid():
    """ Toggles the grid perpendicular to the X axis. """
    p = curplot()
    if p:
        p.x_grid.visible ^= True
        p.request_redraw()

def ygrid():
    """ Toggles the grid perpendicular to the Y axis. """
    p = curplot()
    if p:
        p.y_grid.visible ^= True
        p.request_redraw()

def _set_scale(axis, system):
    p = curplot()
    if p:
        if axis == 'x':
            log_linear_trait = 'index_scale'
            ticks = p.x_ticks
        else:
            log_linear_trait = 'value_scale'
            ticks = p.y_ticks
        if system == 'time':
            system = CalendarScaleSystem()
        if isinstance(system, basestring):
            setattr(p, log_linear_trait, system)
        else:
            if system is None:
                system = dict(linear=p.linear_scale, log=p.log_scale).get(
                    p.get(log_linear_trait), p.linear_scale)
            ticks.scale = system
        p.request_redraw()

def xscale(system=None):
    """ Change the scale system for the X-axis ticks.

    Usage
    -----
    * ``xscale()``: revert the scale system to the default.
    * ``xscale('time')``: use the calendar scale system for time series.
    * ``xscale('log')``: use a generic log-scale.
    * ``xscale('linear')``: use a generic linear-scale.
    * ``xscale(some_scale_system)``: use an arbitrary ScaleSystem object.
    """
    _set_scale('x', system)

def yscale(system=None):
    """ Change the scale system for the Y-axis ticks.

    Usage
    -----
    * ``yscale()``: revert the scale system to the default.
    * ``yscale('time')``: use the calendar scale system for time series.
    * ``yscale('log')``: use a generic log-scale.
    * ``yscale('linear')``: use a generic linear-scale.
    * ``yscale(some_scale_system)``: use an arbitrary ScaleSystem object.
    """
    _set_scale('y', system)

def legend(setting=None):
    """ Sets or toggles the presence of the legend

    Usage
    -----
    * ``legend()``: toggles the legend; if it is currently visible, it is hideen, and if it is currently hidden, then it is displayed
    * ``legend(True)``: shows the legend
    * ``legend(False)``: hides the legend
    """
    p = curplot()
    if p:
        if setting is None:
            setting = not p.legend.visible
        p.legend.visible = setting
        p.request_redraw()


#-----------------------------------------------------------------------------
# Tools
#-----------------------------------------------------------------------------

def tool():
    """ Toggles tools on and off. """
    p = curplot()
    if p:
        pass



#-----------------------------------------------------------------------------
# Saving and IO
#-----------------------------------------------------------------------------

def save(filename="chacoplot.png", dpi=72, pagesize="letter", dest_box=None, units="inch"):
    """ Saves the active plot to an file.  Currently supported file types
    are: bmp, png, jpg.
    """
    p = curplot()
    if not p:
        print "Doing nothing because there is no active plot."
        return

    import os.path
    ext = os.path.splitext(filename)[-1]
    if ext == ".pdf":
        print "Warning: the PDF backend is still a little buggy."
        from chaco.pdf_graphics_context import PdfPlotGraphicsContext
        # Set some default PDF options if none are provided
        if dest_box is None:
            dest_box = (0.5, 0.5, -0.5, -0.5)
        gc = PdfPlotGraphicsContext(filename = filename,
                                    pagesize = pagesize,
                                    dest_box = dest_box,
                                    dest_box_units = units)

        # temporarily turn off the backbuffer for offscreen rendering
        use_backbuffer = p.use_backbuffer
        p.use_backbuffer = False
        gc.render_component(p)
        p.use_backbuffer = use_backbuffer

        gc.save()
        del gc
        print "Saved to", filename

    elif ext in [".bmp", ".png", ".jpg"]:
        from chaco.api import PlotGraphicsContext
        gc = PlotGraphicsContext(tuple(p.outer_bounds), dpi=dpi)

        # temporarily turn off the backbuffer for offscreen rendering
        use_backbuffer = p.use_backbuffer
        p.use_backbuffer = False
        gc.render_component(p)
        p.use_backbuffer = use_backbuffer

        gc.save(filename)
        del gc
        print "Saved to", filename
    else:
        print "Format not yet supported:", ext
        print "Currently supported formats are: bmp, png, jpg."
    return



# EOF