Python matplotlib.lines方法代碼示例

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def show(self):
        'populate the combo box'
        self._updateson = False
        # flush the old
        cbox = self.cbox_lineprops
        for i in range(self._lastcnt-1,-1,-1):
            cbox.remove_text(i)

        # add the new
        for line in self.lines:
            cbox.append_text(line.get_label())
        cbox.set_active(0)

        self._updateson = True
        self._lastcnt = len(self.lines)
        self.dlg.show() 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def streamplot(x, y, u, v, density=1, linewidth=None, color=None, cmap=None,
               norm=None, arrowsize=1, arrowstyle='-|>', minlength=0.1,
               transform=None, hold=None):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.streamplot(x, y, u, v, density=density, linewidth=linewidth,
                            color=color, cmap=cmap, norm=norm,
                            arrowsize=arrowsize, arrowstyle=arrowstyle,
                            minlength=minlength, transform=transform)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret.lines)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def reset(self, event):

        if not self.click_id:
            self.click_id = fig.canvas.mpl_connect('button_press_event', self.onclick)
        #print (len(self.lines))
        #print (len(self.circles))
        if len(self.points)>5:
            for line in self.lines:
                line.pop(0).remove()
            for circle in self.circles:
                circle.remove()
            self.lines, self.circles = [], []
            self.p.remove()
            self.prev = self.p = None
            self.points = []
        #print (len(self.lines))
        #print (len(self.circles)) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def submit(self, event):

        if not self.right_click:
            print ('Right click before submit is a must!!')
        else:

            self.text+=self.radio.value_selected+'\n'+'%.2f'%self.find_poly_area()+'\n'+self.print_points()+'\n\n'
            self.right_click = False
            #print (self.points)

            self.lines, self.circles = [], []
            self.click_id = fig.canvas.mpl_connect('button_press_event', self.onclick)

            self.polys.append(Polygon(self.points_to_polygon(), closed=True, color=np.random.rand(3), alpha=0.4, fill=True))
            if self.submit_p:
                self.submit_p.remove()
            self.submit_p = PatchCollection(self.polys, cmap=matplotlib.cm.jet, alpha=0.4)
            self.ax.add_collection(self.submit_p)
            self.points = [] 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def _color_config(self):
        self.plot_style = {
            'experiment': {'color': 'blue', 'linestyle': '',
                           'marker': '.', 'label': self.exp_data_label},
            'background': {'color': 'indigo', 'marker': '+',
                           'markersize': 1, 'label': 'background'},
            'emission_line': {'color': 'black', 'linewidth': 2},
            'roi_line': {'color': 'red', 'linewidth': 2},
            'k_line': {'color': 'green', 'label': 'k lines'},
            'l_line': {'color': 'magenta', 'label': 'l lines'},
            'm_line': {'color': 'brown', 'label': 'm lines'},
            'compton': {'color': 'darkcyan', 'linewidth': 1.5, 'label': 'compton'},
            'elastic': {'color': 'purple', 'label': 'elastic'},
            'escape': {'color': 'darkblue', 'label': 'escape'},
            'pileup': {'color': 'darkgoldenrod', 'label': 'pileup'},
            'userpeak': {'color': 'orange', 'label': 'userpeak'},
            # 'auto_fit': {'color': 'black', 'label': 'auto fitted', 'linewidth': 2.5},
            'fit': {'color': 'red', 'label': 'fit', 'linewidth': 2.5},
            'residual': {'color': 'black', 'label': 'residual', 'linewidth': 2.0}
        } 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def plot_emission_line(self):
        """
        Plot emission line and escape peaks associated with given lines.
        The value of self.max_v is needed in this function in order to plot
        the relative height of each emission line.
        """
        while(len(self.eline_obj)):
            self.eline_obj.pop().remove()

        escape_e = self.escape_e

        if len(self.elist):
            for i in range(len(self.elist)):
                eline, = self._ax.plot([self.elist[i][0], self.elist[i][0]],
                                       [0, self.elist[i][1]*self.max_v],
                                       color=self.plot_style['emission_line']['color'],
                                       linewidth=self.plot_style['emission_line']['linewidth'])
                self.eline_obj.append(eline)
                if self.plot_escape_line and self.elist[i][0] > escape_e:
                    eline, = self._ax.plot([self.elist[i][0]-escape_e,
                                            self.elist[i][0]-escape_e],
                                           [0, self.elist[i][1]*self.max_v],
                                           color=self.plot_style['escape']['color'],
                                           linewidth=self.plot_style['emission_line']['linewidth'])
                    self.eline_obj.append(eline) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def save(self):
        """ save the changes to the .py file """
        header = [getReference(self.figure) + ".ax_dict = {ax.get_label(): ax for ax in " + getReference(
            self.figure) + ".axes}", "import matplotlib as mpl"]

        # block = getTextFromFile(header[0], self.stack_position)
        output = ["#% start: automatic generated code from pylustrator"]
        # add the lines from the header
        for line in header:
            output.append(line)
        # add all lines from the changes
        for line in self.sorted_changes():
            output.append(line)
            if line.startswith("fig.add_axes"):
                output.append(header[1])
        output.append("#% end: automatic generated code from pylustrator")
        # print("\n".join(output))

        block_id = getReference(self.figure)
        block = getTextFromFile(block_id, stack_position)
        if not block:
            block_id = getReference(self.figure, allow_using_variable_names=False)
            block = getTextFromFile(block_id, stack_position)
        insertTextToFile(output, stack_position, block_id)
        self.saved = True 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def add_line(self, line):
        """
        Add a :class:`~matplotlib.lines.Line2D` to the list of plot
        lines

        Returns the line.
        """
        self._set_artist_props(line)
        if line.get_clip_path() is None:
            line.set_clip_path(self.patch)

        self._update_line_limits(line)
        if not line.get_label():
            line.set_label('_line%d' % len(self.lines))
        self.lines.append(line)
        line._remove_method = lambda h: self.lines.remove(h)
        return line 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def relim(self, visible_only=False):
        """
        Recompute the data limits based on current artists. If you want to
        exclude invisible artists from the calculation, set
        ``visible_only=True``

        At present, :class:`~matplotlib.collections.Collection`
        instances are not supported.
        """
        # Collections are deliberately not supported (yet); see
        # the TODO note in artists.py.
        self.dataLim.ignore(True)
        self.dataLim.set_points(mtransforms.Bbox.null().get_points())
        self.ignore_existing_data_limits = True

        for line in self.lines:
            if not visible_only or line.get_visible():
                self._update_line_limits(line)

        for p in self.patches:
            if not visible_only or p.get_visible():
                self._update_patch_limits(p) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def streamplot(x, y, u, v, density=1, linewidth=None, color=None, cmap=None,
               norm=None, arrowsize=1, arrowstyle='-|>', minlength=0.1,
               transform=None, zorder=1, hold=None):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.streamplot(x, y, u, v, density=density, linewidth=linewidth,
                            color=color, cmap=cmap, norm=norm,
                            arrowsize=arrowsize, arrowstyle=arrowstyle,
                            minlength=minlength, transform=transform,
                            zorder=zorder)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret.lines)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def add_line(self, line):
        """
        Add a :class:`~matplotlib.lines.Line2D` to the list of plot
        lines

        Returns the line.
        """
        self._set_artist_props(line)
        if line.get_clip_path() is None:
            line.set_clip_path(self.patch)

        self._update_line_limits(line)
        if not line.get_label():
            line.set_label('_line%d' % len(self.lines))
        self.lines.append(line)
        line._remove_method = self.lines.remove
        self.stale = True
        return line 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def get_children(self):
        """return a list of child artists"""
        children = []
        children.extend(self.collections)
        children.extend(self.patches)
        children.extend(self.lines)
        children.extend(self.texts)
        children.extend(self.artists)
        children.extend(self.spines.values())
        children.append(self.xaxis)
        children.append(self.yaxis)
        children.append(self.title)
        children.append(self._left_title)
        children.append(self._right_title)
        children.extend(self.tables)
        children.extend(self.images)
        children.extend(self.child_axes)

        if self.legend_ is not None:
            children.append(self.legend_)
        children.append(self.patch)

        return children 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def streamplot(
        x, y, u, v, density=1, linewidth=None, color=None, cmap=None,
        norm=None, arrowsize=1, arrowstyle='-|>', minlength=0.1,
        transform=None, zorder=None, start_points=None, maxlength=4.0,
        integration_direction='both', *, data=None):
    __ret = gca().streamplot(
        x=x, y=y, u=u, v=v, density=density, linewidth=linewidth,
        color=color, cmap=cmap, norm=norm, arrowsize=arrowsize,
        arrowstyle=arrowstyle, minlength=minlength,
        transform=transform, zorder=zorder, start_points=start_points,
        maxlength=maxlength,
        integration_direction=integration_direction, data=data)
    sci(__ret.lines)
    return __ret

# Autogenerated by boilerplate.py.  Do not edit as changes will be lost. 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def plot_costs(case, number_of_segments=1, ax=None, legend=True):
    if ax is None:
        fig, axs = plt.subplots(1, 1, figsize=(16, 10))
        ax = axs

    color_scale = make_interpolater(0, len(case.gen_name), 0, 1)

    color = {g: plt.cm.jet(color_scale(i)) for i, g in enumerate(case.gen_name)}

    for s in calculate_segments(case, number_of_segments=number_of_segments):
        pmin, pmax = s['segment']
        x = np.linspace(pmin, pmax)
        y = x * s['slope']
        ax.plot(x, y, color=color[s['name']])

    ax = ax.twinx()
    for s in calculate_segments(case, number_of_segments=number_of_segments):
        pmin, pmax = s['segment']
        x = np.linspace(pmin, pmax)
        y = [s['slope'] for _ in x]
        ax.plot(x, y, color=color[s['name']])

    ax.set_ylim(0, 1.2*y[-1])

    if legend:
        lines = list()
        for g in case.gen_name:
            lines.append(mlines.Line2D([], [], color=color[g], label=g))
            ax.legend(handles=lines, loc='upper left')

    return ax 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import lines [as 別名]
def __init__(self, lines):
        import gtk.glade

        datadir = matplotlib.get_data_path()
        gladefile = os.path.join(datadir, 'lineprops.glade')
        if not os.path.exists(gladefile):
            raise IOError('Could not find gladefile lineprops.glade in %s'%datadir)

        self._inited = False
        self._updateson = True # suppress updates when setting widgets manually
        self.wtree = gtk.glade.XML(gladefile, 'dialog_lineprops')
        self.wtree.signal_autoconnect(dict([(s, getattr(self, s)) for s in self.signals]))

        self.dlg = self.wtree.get_widget('dialog_lineprops')

        self.lines = lines

        cbox = self.wtree.get_widget('combobox_lineprops')
        cbox.set_active(0)
        self.cbox_lineprops = cbox

        cbox = self.wtree.get_widget('combobox_linestyles')
        for ls in self.linestyles:
            cbox.append_text(ls)
        cbox.set_active(0)
        self.cbox_linestyles = cbox

        cbox = self.wtree.get_widget('combobox_markers')
        for m in self.markers:
            cbox.append_text(m)
        cbox.set_active(0)
        self.cbox_markers = cbox
        self._lastcnt = 0
        self._inited = True