source: tags/Release2.1.0b/python/asaplotbase.py @ 1240

"""
ASAP plotting class based on matplotlib.
"""

import sys
from re import match

import matplotlib

from matplotlib.figure import Figure, Text
from matplotlib.font_manager import FontProperties as FP
from matplotlib.numerix import sqrt
from matplotlib import rc, rcParams
from asap import rcParams as asaprcParams
from matplotlib.ticker import OldScalarFormatter
from matplotlib.ticker import NullLocator
from matplotlib.transforms import blend_xy_sep_transform

if int(matplotlib.__version__.split(".")[1]) < 87:
    print "Warning: matplotlib version < 0.87. This might cause errors. Please upgrade."

#class MyFormatter(OldScalarFormatter):
#    def __call__(self, x, pos=None):
#        last = len(self.locs)-2
#        if pos==0:
#            return ''
#        else: return OldScalarFormatter.__call__(self, x, pos)

class asaplotbase:
    """
    ASAP plotting base class based on matplotlib.
    """

    def __init__(self, rows=1, cols=0, title='', size=(8,6), buffering=False):
        """
        Create a new instance of the ASAPlot plotting class.

        If rows < 1 then a separate call to set_panels() is required to define
        the panel layout; refer to the doctext for set_panels().
        """
        self.is_dead = False
        self.figure = Figure(figsize=size, facecolor='#ddddee')
        self.canvas = None

        self.set_title(title)
        self.subplots = []
        if rows > 0:
            self.set_panels(rows, cols)

        # Set matplotlib default colour sequence.
        self.colormap = "green red black cyan magenta orange blue purple yellow pink".split()

        c = asaprcParams['plotter.colours']
        if isinstance(c,str) and len(c) > 0:
            self.colormap = c.split()

        self.lsalias = {"line":  [1,0],
                        "dashdot": [4,2,1,2],
                        "dashed" : [4,2,4,2],
                        "dotted" : [1,2],
                        "dashdotdot": [4,2,1,2,1,2],
                        "dashdashdot": [4,2,4,2,1,2]
                        }

        styles = "line dashed dotted dashdot".split()
        c = asaprcParams['plotter.linestyles']
        if isinstance(c,str) and len(c) > 0:
            styles = c.split()
        s = []
        for ls in styles:
            if self.lsalias.has_key(ls):
                s.append(self.lsalias.get(ls))
            else:
                s.append('-')
        self.linestyles = s

        self.color = 0;
        self.linestyle = 0;
        self.attributes = {}
        self.loc = 0

        self.buffering = buffering

    def clear(self):
        """
        Delete all lines from the plot.  Line numbering will restart from 0.
        """

        for i in range(len(self.lines)):
           self.delete(i)
        self.axes.clear()
        self.color = 0
        self.lines = []

    def palette(self, color, colormap=None, linestyle=0, linestyles=None):
        if colormap:
            if isinstance(colormap,list):
                self.colormap = colormap
            elif isinstance(colormap,str):
                self.colormap = colormap.split()
        if 0 <= color < len(self.colormap):
            self.color = color
        if linestyles:
            self.linestyles = []
            if isinstance(linestyles,list):
                styles = linestyles
            elif isinstance(linestyles,str):
                styles = linestyles.split()
            for ls in styles:
                if self.lsalias.has_key(ls):
                    self.linestyles.append(self.lsalias.get(ls))
                else:
                    self.linestyles.append(self.lsalias.get('line'))
        if 0 <= linestyle < len(self.linestyles):
            self.linestyle = linestyle

    def delete(self, numbers=None):
        """
        Delete the 0-relative line number, default is to delete the last.
        The remaining lines are NOT renumbered.
        """

        if numbers is None: numbers = [len(self.lines)-1]

        if not hasattr(numbers, '__iter__'):
            numbers = [numbers]

        for number in numbers:
            if 0 <= number < len(self.lines):
                if self.lines[number] is not None:
                    for line in self.lines[number]:
                        line.set_linestyle('None')
                        self.lines[number] = None
        self.show()

    def get_line(self):
        """
        Get the current default line attributes.
        """
        return self.attributes


    def hist(self, x=None, y=None, fmt=None, add=None):
        """
        Plot a histogram.  N.B. the x values refer to the start of the
        histogram bin.

        fmt is the line style as in plot().
        """
        from matplotlib.numerix import array
        from matplotlib.numerix.ma import MaskedArray
        if x is None:
            if y is None: return
            x = range(len(y))

        if len(x) != len(y):
            return
        l2 = 2*len(x)
        x2 = range(l2)
        y2 = range(12)
        y2 = range(l2)
        m2 = range(l2)
        ymsk = y.raw_mask()
        ydat = y.raw_data()
        for i in range(l2):
            x2[i] = x[i/2]
            m2[i] = ymsk[i/2]

        y2[0] = 0.0
        for i in range(1,l2):
            y2[i] = ydat[(i-1)/2]

        self.plot(x2, MaskedArray(y2,mask=m2,copy=0), fmt, add)


    def hold(self, hold=True):
        """
        Buffer graphics until subsequently released.
        """
        self.buffering = hold


    def legend(self, loc=None):
        """
        Add a legend to the plot.

        Any other value for loc else disables the legend:
             1: upper right
             2: upper left
             3: lower left
             4: lower right
             5: right
             6: center left
             7: center right
             8: lower center
             9: upper center
            10: center

        """
        if isinstance(loc, int):
            self.loc = None
            if 0 <= loc <= 10: self.loc = loc
        else:
            self.loc = None
        #self.show()


    def plot(self, x=None, y=None, fmt=None, add=None):
        """
        Plot the next line in the current frame using the current line
        attributes.  The ASAPlot graphics window will be mapped and raised.

        The argument list works a bit like the matlab plot() function.
        """
        if x is None:
            if y is None: return
            x = range(len(y))

        elif y is None:
            y = x
            x = range(len(y))
        if fmt is None:
            line = self.axes.plot(x, y)
        else:
            line = self.axes.plot(x, y, fmt)

        # Add to an existing line?
        i = None
        if add is None or len(self.lines) < add < 0:
            # Don't add.
            self.lines.append(line)
            i = len(self.lines) - 1
        else:
            if add == 0: add = len(self.lines)
            i = add - 1
            self.lines[i].extend(line)

        # Set/reset attributes for the line.
        gotcolour = False
        for k, v in self.attributes.iteritems():
            if k == 'color': gotcolour = True
            for segment in self.lines[i]:
                getattr(segment, "set_%s"%k)(v)

        if not gotcolour and len(self.colormap):
            for segment in self.lines[i]:
                getattr(segment, "set_color")(self.colormap[self.color])
                if len(self.colormap)  == 1:
                    getattr(segment, "set_dashes")(self.linestyles[self.linestyle])

            self.color += 1
            if self.color >= len(self.colormap):
                self.color = 0

            if len(self.colormap) == 1:
                self.linestyle += 1
            if self.linestyle >= len(self.linestyles):
                self.linestyle = 0

        self.show()


    def position(self):
        """
        Use the mouse to get a position from a graph.
        """

        def position_disable(event):
            self.register('button_press', None)
            print '%.4f, %.4f' % (event.xdata, event.ydata)

        print 'Press any mouse button...'
        self.register('button_press', position_disable)


    def region(self):
        """
        Use the mouse to get a rectangular region from a plot.

        The return value is [x0, y0, x1, y1] in world coordinates.
        """

        def region_start(event):
            height = self.canvas.figure.bbox.height()
            self.rect = {'fig': None, 'height': height,
                         'x': event.x, 'y': height - event.y,
                         'world': [event.xdata, event.ydata,
                                   event.xdata, event.ydata]}
            self.register('button_press', None)
            self.register('motion_notify', region_draw)
            self.register('button_release', region_disable)

        def region_draw(event):
            self.canvas._tkcanvas.delete(self.rect['fig'])
            self.rect['fig'] = self.canvas._tkcanvas.create_rectangle(
                                self.rect['x'], self.rect['y'],
                                event.x, self.rect['height'] - event.y)

        def region_disable(event):
            self.register('motion_notify', None)
            self.register('button_release', None)

            self.canvas._tkcanvas.delete(self.rect['fig'])

            self.rect['world'][2:4] = [event.xdata, event.ydata]
            print '(%.2f, %.2f)  (%.2f, %.2f)' % (self.rect['world'][0],
                self.rect['world'][1], self.rect['world'][2],
                self.rect['world'][3])

        self.register('button_press', region_start)

        # This has to be modified to block and return the result (currently
        # printed by region_disable) when that becomes possible in matplotlib.

        return [0.0, 0.0, 0.0, 0.0]


    def register(self, type=None, func=None):
        """
        Register, reregister, or deregister events of type 'button_press',
        'button_release', or 'motion_notify'.

        The specified callback function should have the following signature:

            def func(event)

        where event is an MplEvent instance containing the following data:

            name                # Event name.
            canvas              # FigureCanvas instance generating the event.
            x      = None       # x position - pixels from left of canvas.
            y      = None       # y position - pixels from bottom of canvas.
            button = None       # Button pressed: None, 1, 2, 3.
            key    = None       # Key pressed: None, chr(range(255)), shift,
                                  win, or control
            inaxes = None       # Axes instance if cursor within axes.
            xdata  = None       # x world coordinate.
            ydata  = None       # y world coordinate.

        For example:

            def mouse_move(event):
                print event.xdata, event.ydata

            a = asaplot()
            a.register('motion_notify', mouse_move)

        If func is None, the event is deregistered.

        Note that in TkAgg keyboard button presses don't generate an event.
        """

        if not self.events.has_key(type): return

        if func is None:
            if self.events[type] is not None:
                # It's not clear that this does anything.
                self.canvas.mpl_disconnect(self.events[type])
                self.events[type] = None

                # It seems to be necessary to return events to the toolbar.
                if type == 'motion_notify':
                    self.canvas.mpl_connect(type + '_event',
                        self.figmgr.toolbar.mouse_move)
                elif type == 'button_press':
                    self.canvas.mpl_connect(type + '_event',
                        self.figmgr.toolbar.press)
                elif type == 'button_release':
                    self.canvas.mpl_connect(type + '_event',
                        self.figmgr.toolbar.release)

        else:
            self.events[type] = self.canvas.mpl_connect(type + '_event', func)


    def release(self):
        """
        Release buffered graphics.
        """
        self.buffering = False
        self.show()


    def save(self, fname=None, orientation=None, dpi=None, papertype=None):
        """
        Save the plot to a file.

        fname is the name of the output file.  The image format is determined
        from the file suffix; 'png', 'ps', and 'eps' are recognized.  If no
        file name is specified 'yyyymmdd_hhmmss.png' is created in the current
        directory.
        """
        from asap import rcParams
        if papertype is None:
            papertype = rcParams['plotter.papertype']
        if fname is None:
            from datetime import datetime
            dstr = datetime.now().strftime('%Y%m%d_%H%M%S')
            fname = 'asap'+dstr+'.png'

        d = ['png','.ps','eps']

        from os.path import expandvars
        fname = expandvars(fname)

        if fname[-3:].lower() in d:
            try:
                if fname[-3:].lower() == ".ps":
                    from matplotlib import __version__ as mv
                    w = self.figure.figwidth.get()
                    h = self.figure.figheight.get()

                    if orientation is None:
                        # oriented
                        if w > h:
                            orientation = 'landscape'
                        else:
                            orientation = 'portrait'
                    from matplotlib.backends.backend_ps import papersize
                    pw,ph = papersize[papertype.lower()]
                    ds = None
                    if orientation == 'landscape':
                        ds = min(ph/w, pw/h)
                    else:
                        ds = min(pw/w, ph/h)
                    ow = ds * w
                    oh = ds * h
                    self.figure.set_figsize_inches((ow, oh))
                    self.figure.savefig(fname, orientation=orientation,
                                        papertype=papertype.lower())
                    self.figure.set_figsize_inches((w, h))
                    print 'Written file %s' % (fname)
                else:
                    if dpi is None:
                        dpi =150
                    self.figure.savefig(fname,dpi=dpi)
                    print 'Written file %s' % (fname)
            except IOError, msg:
                print 'Failed to save %s: Error msg was\n\n%s' % (fname, err)
                return
        else:
            print "Invalid image type. Valid types are:"
            print "'ps', 'eps', 'png'"


    def set_axes(self, what=None, *args, **kwargs):
        """
        Set attributes for the axes by calling the relevant Axes.set_*()
        method.  Colour translation is done as described in the doctext
        for palette().
        """

        if what is None: return
        if what[-6:] == 'colour': what = what[:-6] + 'color'

        key = "colour"
        if kwargs.has_key(key):
            val = kwargs.pop(key)
            kwargs["color"] = val

        getattr(self.axes, "set_%s"%what)(*args, **kwargs)

        self.show(hardrefresh=False)


    def set_figure(self, what=None, *args, **kwargs):
        """
        Set attributes for the figure by calling the relevant Figure.set_*()
        method.  Colour translation is done as described in the doctext
        for palette().
        """

        if what is None: return
        if what[-6:] == 'colour': what = what[:-6] + 'color'
        #if what[-5:] == 'color' and len(args):
        #    args = (get_colour(args[0]),)

        newargs = {}
        for k, v in kwargs.iteritems():
            k = k.lower()
            if k == 'colour': k = 'color'
            newargs[k] = v

        getattr(self.figure, "set_%s"%what)(*args, **newargs)
        self.show(hardrefresh=False)


    def set_limits(self, xlim=None, ylim=None):
        """
        Set x-, and y-limits for each subplot.

        xlim = [xmin, xmax] as in axes.set_xlim().
        ylim = [ymin, ymax] as in axes.set_ylim().
        """
        for s in self.subplots:
            self.axes  = s['axes']
            self.lines = s['lines']
            oldxlim =  list(self.axes.get_xlim())
            oldylim =  list(self.axes.get_ylim())
            if xlim is not None:
                for i in range(len(xlim)):
                    if xlim[i] is not None:
                        oldxlim[i] = xlim[i]
            if ylim is not None:
                for i in range(len(ylim)):
                    if ylim[i] is not None:
                        oldylim[i] = ylim[i]
            self.axes.set_xlim(oldxlim)
            self.axes.set_ylim(oldylim)
        return


    def set_line(self, number=None, **kwargs):
        """
        Set attributes for the specified line, or else the next line(s)
        to be plotted.

        number is the 0-relative number of a line that has already been
        plotted.  If no such line exists, attributes are recorded and used
        for the next line(s) to be plotted.

        Keyword arguments specify Line2D attributes, e.g. color='r'.  Do

            import matplotlib
            help(matplotlib.lines)

        The set_* methods of class Line2D define the attribute names and
        values.  For non-US usage, "colour" is recognized as synonymous with
        "color".

        Set the value to None to delete an attribute.

        Colour translation is done as described in the doctext for palette().
        """

        redraw = False
        for k, v in kwargs.iteritems():
            k = k.lower()
            if k == 'colour': k = 'color'

            if 0 <= number < len(self.lines):
                if self.lines[number] is not None:
                    for line in self.lines[number]:
                        getattr(line, "set_%s"%k)(v)
                    redraw = True
            else:
                if v is None:
                    del self.attributes[k]
                else:
                    self.attributes[k] = v

        if redraw: self.show(hardrefresh=False)


    def set_panels(self, rows=1, cols=0, n=-1, nplots=-1, ganged=True):
        """
        Set the panel layout.

        rows and cols, if cols != 0, specify the number of rows and columns in
        a regular layout.   (Indexing of these panels in matplotlib is row-
        major, i.e. column varies fastest.)

        cols == 0 is interpreted as a retangular layout that accomodates
        'rows' panels, e.g. rows == 6, cols == 0 is equivalent to
        rows == 2, cols == 3.

        0 <= n < rows*cols is interpreted as the 0-relative panel number in
        the configuration specified by rows and cols to be added to the
        current figure as its next 0-relative panel number (i).  This allows
        non-regular panel layouts to be constructed via multiple calls.  Any
        other value of n clears the plot and produces a rectangular array of
        empty panels.  The number of these may be limited by nplots.
        """
        if n < 0 and len(self.subplots):
            self.figure.clear()
            self.set_title()

        if rows < 1: rows = 1

        if cols <= 0:
            i = int(sqrt(rows))
            if i*i < rows: i += 1
            cols = i

            if i*(i-1) >= rows: i -= 1
            rows = i

        if 0 <= n < rows*cols:
            i = len(self.subplots)
            self.subplots.append({})

            self.subplots[i]['axes']  = self.figure.add_subplot(rows,
                                            cols, n+1)
            self.subplots[i]['lines'] = []

            if i == 0: self.subplot(0)

            self.rows = 0
            self.cols = 0

        else:
            self.subplots = []

            if nplots < 1 or rows*cols < nplots:
                nplots = rows*cols
            if ganged:
                hsp,wsp = None,None
                if rows > 1: hsp = 0.0001
                if cols > 1: wsp = 0.0001
                self.figure.subplots_adjust(wspace=wsp,hspace=hsp)
            for i in range(nplots):
                self.subplots.append({})
                self.subplots[i]['lines'] = []
                if not ganged:
                    self.subplots[i]['axes'] = self.figure.add_subplot(rows,
                                                cols, i+1)
                    self.subplots[i]['axes'].xaxis.set_major_formatter(OldScalarFormatter())
                else:
                    if i == 0:
                        self.subplots[i]['axes'] = self.figure.add_subplot(rows,
                                                cols, i+1)
                        self.subplots[i]['axes'].xaxis.set_major_formatter(OldScalarFormatter())
                    else:
                        self.subplots[i]['axes'] = self.figure.add_subplot(rows,
                                                cols, i+1,
                                                sharex=self.subplots[0]['axes'],
                                                sharey=self.subplots[0]['axes'])

                    # Suppress tick labelling for interior subplots.
                    if i <= (rows-1)*cols - 1:
                        if i+cols < nplots:
                            # Suppress x-labels for frames width
                            # adjacent frames
                            for tick in self.subplots[i]['axes'].xaxis.majorTicks:
                                tick.label1On = False
                            self.subplots[i]['axes'].xaxis.label.set_visible(False)
                    if i%cols:
                        # Suppress y-labels for frames not in the left column.
                        for tick in self.subplots[i]['axes'].yaxis.majorTicks:
                            tick.label1On = False
                        self.subplots[i]['axes'].yaxis.label.set_visible(False)
                    # disable the first tick of [1:ncol-1] of the last row
                    #if i+1 < nplots:
                    #    self.subplots[i]['axes'].xaxis.majorTicks[0].label1On = False
                self.rows = rows
                self.cols = cols
            self.subplot(0)

    def tidy(self):
        # this needs to be exceuted after the first "refresh"
        nplots = len(self.subplots)
        if nplots == 1: return
        for i in xrange(nplots):
            ax = self.subplots[i]['axes']
            if i%self.cols:
                ax.xaxis.majorTicks[0].label1On = False
            else:
                if i != 0:
                    ax.yaxis.majorTicks[-1].label1On = False


    def set_title(self, title=None):
        """
        Set the title of the plot window.  Use the previous title if title is
        omitted.
        """
        if title is not None:
            self.title = title

        self.figure.text(0.5, 0.95, self.title, horizontalalignment='center')


    def show(self, hardrefresh=True):
        """
        Show graphics dependent on the current buffering state.
        """
        if not hardrefresh: return
        if not self.buffering:
            if self.loc is not None:
                for sp in self.subplots:
                    lines  = []
                    labels = []
                    i = 0
                    for line in sp['lines']:
                        i += 1
                        if line is not None:
                            lines.append(line[0])
                            lbl = line[0].get_label()
                            if lbl == '':
                                lbl = str(i)
                            labels.append(lbl)

                    if len(lines):
                        fp = FP(size=rcParams['legend.fontsize'])
                        fsz = fp.get_size_in_points() - len(lines)
                        fp.set_size(max(fsz,6))
                        sp['axes'].legend(tuple(lines), tuple(labels),
                                          self.loc, prop=fp)
                    else:
                        sp['axes'].legend((' '))

            from matplotlib.artist import setp
            fp = FP(size=rcParams['xtick.labelsize'])
            xts = fp.get_size_in_points()- (self.cols)/2
            fp = FP(size=rcParams['ytick.labelsize'])
            yts = fp.get_size_in_points() - (self.rows)/2
            for sp in self.subplots:
                ax = sp['axes']
                s = ax.title.get_size()
                tsize = s-(self.cols+self.rows)
                ax.title.set_size(tsize)
                fp = FP(size=rcParams['axes.labelsize'])
                setp(ax.get_xticklabels(), fontsize=xts)
                setp(ax.get_yticklabels(), fontsize=yts)
                origx =  fp.get_size_in_points()
                origy = origx
                off = 0
                if self.cols > 1: off = self.cols
                xfsize = origx-off
                ax.xaxis.label.set_size(xfsize)
                off = 0
                if self.rows > 1: off = self.rows
                yfsize = origy-off
                ax.yaxis.label.set_size(yfsize)

    def subplot(self, i=None, inc=None):
        """
        Set the subplot to the 0-relative panel number as defined by one or
        more invokations of set_panels().
        """
        l = len(self.subplots)
        if l:
            if i is not None:
                self.i = i

            if inc is not None:
                self.i += inc

            self.i %= l
            self.axes  = self.subplots[self.i]['axes']
            self.lines = self.subplots[self.i]['lines']

    def text(self, *args, **kwargs):
        """
        Add text to the figure.
        """
        self.figure.text(*args, **kwargs)
        self.show()

    def vline_with_label(self, x, y, label,
                         location='bottom', rotate=0.0, **kwargs):
        """
        Plot a vertical line with label.
        It takes "world" values fo x and y.
        """
        ax = self.axes
        # need this to suppress autoscaling during this function
        self.axes.set_autoscale_on(False)
        ymin = 0.0
        ymax = 1.0
        valign = 'center'
        if location.lower() == 'top':
            y = max(0.0, y)
        elif location.lower() == 'bottom':
            y = min(0.0, y)
        lbloffset = 0.06
        # a rough estimate for the bb of the text
        if rotate > 0.0: lbloffset = 0.03*len(label)
        peakoffset = 0.01
        xy0 = ax.transData.xy_tup((x,y))
        # get relative coords
        xy = ax.transAxes.inverse_xy_tup(xy0)
        if location.lower() == 'top':
            ymax = 1.0-lbloffset
            ymin = xy[1]+peakoffset
            valign = 'bottom'
            ylbl = ymax+0.01
        elif location.lower() == 'bottom':
            ymin = lbloffset
            ymax = xy[1]-peakoffset
            valign = 'top'
            ylbl = ymin-0.01
        trans = blend_xy_sep_transform(ax.transData, ax.transAxes)
        l = ax.axvline(x, ymin, ymax, color='black', **kwargs)
        t = ax.text(x, ylbl ,label, verticalalignment=valign,
                                    horizontalalignment='center',
                    rotation=rotate,transform = trans)
        self.axes.set_autoscale_on(True)