Python Figure.set_figheight方法代码示例

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def reports_pie(request,scope):

    month, year, late , dates_gc = current_reporting_period()
 
    period = (dates_gc[0],dates_gc[1])
 
    completed = len(scope.current_entries())
    incomplete = len(scope.health_posts()) - len(scope.current_entries())
 

    fig = Figure()
    ax=fig.add_subplot(111, axisbg='r')
    fig.set_figheight(2)
    fig.set_figwidth(2)
    fig.set_facecolor('w')
  
    labels = 'Completed', 'Incomlete'
    fracs = [completed,incomplete]
    explode=(0,0.01)
    pie(fracs, explode=explode, labels=None,colors=('g','r'), autopct='%1.1f%%', shadow=True)
    title('Reports..', bbox={'facecolor':'0.5', 'pad':5})
    ax.pie(fracs, explode=explode, labels=None,colors=('#52E060','#F7976E'),  shadow=True)
   
    canvas=FigureCanvas(fig)
    response=HttpResponse(content_type='image/png')
    canvas.print_png(response)
    return response

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def tricontouring_response(tri_subset, data, request, dpi=None):
    """
    triang_subset is a matplotlib.Tri object in lat/lon units (will be converted to projected coordinates)
    xmin, ymin, xmax, ymax is the bounding pox of the plot in PROJETED COORDINATES!!!
    request is the original getMap request object
    """

    dpi = dpi or 80.

    bbox = request.GET['bbox']
    width = request.GET['width']
    height = request.GET['height']
    colormap = request.GET['colormap']
    colorscalerange = request.GET['colorscalerange']
    cmin = colorscalerange.min
    cmax = colorscalerange.max
    crs = request.GET['crs']
    nlvls = request.GET['numcontours']

    EPSG4326 = pyproj.Proj(init='EPSG:4326')
    tri_subset.x, tri_subset.y = pyproj.transform(EPSG4326, crs, tri_subset.x, tri_subset.y)

    fig = Figure(dpi=dpi, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    fig.set_figheight(height/dpi)
    fig.set_figwidth(width/dpi)

    ax = fig.add_axes([0., 0., 1., 1.], xticks=[], yticks=[])
    ax.set_axis_off()

    if request.GET['logscale'] is True:
        norm_func = mpl.colors.LogNorm
    else:
        norm_func = mpl.colors.Normalize

    # Set out of bound data to NaN so it shows transparent?
    # Set to black like ncWMS?
    # Configurable by user?
    if cmin is not None and cmax is not None:
        lvls = np.linspace(cmin, cmax, nlvls)
        norm = norm_func(vmin=cmin, vmax=cmax, clip=True)
    else:
        lvls = nlvls
        norm = norm_func()

    if request.GET['image_type'] == 'filledcontours':
        ax.tricontourf(tri_subset, data, lvls, norm=norm, cmap=colormap, extend='both')
    elif request.GET['image_type'] == 'contours':
        ax.tricontour(tri_subset, data, lvls, norm=norm, cmap=colormap, extend='both')

    ax.set_xlim(bbox.minx, bbox.maxx)
    ax.set_ylim(bbox.miny, bbox.maxy)
    ax.set_frame_on(False)
    ax.set_clip_on(False)
    ax.set_position([0., 0., 1., 1.])

    canvas = FigureCanvasAgg(fig)
    response = HttpResponse(content_type='image/png')
    canvas.print_png(response)
    return response

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
    def buildMetadataImage(self, layerInfoList, width):
        """
        Creates the metadata caption for figures in styles that display a title only.
        """
        # Find first non-outline layer.
        nonOutlineLayers = [l for l in layerInfoList if l.id != outline_layer.OUTLINE_LAYER_ID]
        layerInfo = nonOutlineLayers[0] if len(nonOutlineLayers) > 0 else None

        # Get the title of the first set of keyword data, i.e., that for the layer rather than one
        # of its antecedent layers or datasets.
        titleText = ''
        if layerInfo and (len(layerInfo.keywordData) > 0):
            titleText = layerInfo.keywordData[0].get('title', '')

        height = 500
        dpi = 100
        transparent = False

        figsize = (width / float(dpi), height / float(dpi))
        fig = Figure(figsize=figsize, dpi=dpi, facecolor='w', frameon=(not transparent))
        renderer = Renderer(fig.dpi)

        text = fig.text(0.5, 0.98, titleText,
                        fontdict=titleFont,
                        horizontalalignment='center',
                        verticalalignment='top')

        # Trim the height of the text image.
        extent = text.get_window_extent(renderer)
        textHeight = (extent.y1 - extent.y0 + 8)
        fig.set_figheight(textHeight / float(dpi))
        
        return image_util.figureToImage(fig)

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def quiver_response(lon, lat, dx, dy, request, dpi=None):

    dpi = dpi or 80.

    bbox = request.GET['bbox']
    width = request.GET['width']
    height = request.GET['height']
    colormap = request.GET['colormap']
    colorscalerange = request.GET['colorscalerange']
    vectorscale = request.GET['vectorscale']
    cmin = colorscalerange.min
    cmax = colorscalerange.max
    crs = request.GET['crs']
    unit_vectors = None  # We don't support requesting these yet, but wouldn't be hard

    EPSG4326 = pyproj.Proj(init='EPSG:4326')
    x, y = pyproj.transform(EPSG4326, crs, lon, lat)  # TODO order for non-inverse?

    fig = Figure(dpi=dpi, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    fig.set_figheight(height/dpi)
    fig.set_figwidth(width/dpi)

    ax = fig.add_axes([0., 0., 1., 1.], xticks=[], yticks=[])
    ax.set_axis_off()
    mags = np.sqrt(dx**2 + dy**2)

    cmap = mpl.cm.get_cmap(colormap)

    if request.GET['logscale'] is True:
        norm_func = mpl.colors.LogNorm
    else:
        norm_func = mpl.colors.Normalize

    # Set out of bound data to NaN so it shows transparent?
    # Set to black like ncWMS?
    # Configurable by user?
    if cmin is not None and cmax is not None:
        mags[mags > cmax] = cmax
        mags[mags < cmin] = cmin
        norm = norm_func(vmin=cmin, vmax=cmax)
    else:
        norm = norm_func()

    # plot unit vectors
    if unit_vectors:
        ax.quiver(x, y, dx/mags, dy/mags, mags, cmap=cmap, norm=norm, scale=vectorscale)
    else:
        ax.quiver(x, y, dx, dy, mags, cmap=cmap, norm=norm, scale=vectorscale)

    ax.set_xlim(bbox.minx, bbox.maxx)
    ax.set_ylim(bbox.miny, bbox.maxy)
    ax.set_frame_on(False)
    ax.set_clip_on(False)
    ax.set_position([0., 0., 1., 1.])

    canvas = FigureCanvasAgg(fig)
    response = HttpResponse(content_type='image/png')
    canvas.print_png(response)
    return response

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
    def buildMetadataImage(self, layerInfoList, width):
        """
        Creates the metadata caption for figures in the style used by WMSViz.
        """
        self.metadataItems = self._buildMetadataItems(layerInfoList)
        self.width = width
        
        width=self.width;height=1600;dpi=100;transparent=False
        figsize=(width / float(dpi), height / float(dpi))
        fig = Figure(figsize=figsize, dpi=dpi, facecolor='w', frameon=(not transparent))
        axes = fig.add_axes([0.04, 0.04, 0.92, 0.92],  frameon=True,xticks=[], yticks=[])
        renderer = Renderer(fig.dpi)


        title, titleHeight = self._drawTitleToAxes(axes, renderer)
        
        txt, textHeight = self._drawMetadataTextToAxes(axes, renderer, self.metadataItems)

        # fit the axis round the text

        pos = axes.get_position()
        newpos = Bbox( [[pos.x0,  pos.y1 - (titleHeight + textHeight) / height], [pos.x1, pos.y1]] )
        axes.set_position(newpos )

        # position the text below the title

        newAxisHeight = (newpos.y1 - newpos.y0) * height
        txt.set_position( (0.02, 0.98 - (titleHeight/newAxisHeight) ))

        for loc, spine in axes.spines.iteritems():
            spine.set_edgecolor(borderColor)
        
        # Draw heading box
        
        headingBoxHeight = titleHeight - 1
        
        axes.add_patch(Rectangle((0, 1.0 - (headingBoxHeight/newAxisHeight)), 1, (headingBoxHeight/newAxisHeight),
                       facecolor=borderColor,
                      fill = True,
                      linewidth=0))

        # reduce the figure height
        
        originalHeight = fig.get_figheight()
        pos = axes.get_position()
        topBound = 20 / float(dpi)
        
        textHeight = (pos.y1 - pos.y0) * originalHeight
        
        newHeight = topBound * 2 + textHeight
        
        # work out the new proportions for the figure
        
        border = topBound / float(newHeight)
        newpos = Bbox( [[pos.x0,  border], [pos.x1, 1 - border]] )
        axes.set_position(newpos )
        
        fig.set_figheight(newHeight)
        
        return image_util.figureToImage(fig)

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def save_plot(fname, plot_name, plot):
    from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
    from matplotlib.figure import Figure
    from matplotlib.dates import DateFormatter

    fig = Figure()
    ax = fig.add_subplot(111)
    ax.xaxis.set_major_formatter(DateFormatter('%H:%M'))
    ax.set_xlabel("Time")
    ax.set_ylabel(plot_name)
    fig.set_figheight(20)
    fig.set_figwidth(30)
    fig.autofmt_xdate()

    handles = []
    labels = []
    for graph in plot:
        x, y = plot[graph]
        handles.append(ax.plot(x, y))
        labels.append(graph)

    fig.legend(handles, labels, 1, shadow=True)

    canvas = FigureCanvas(fig)
    canvas.print_figure(fname, dpi=80)

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
    def getImage(self):
    
        figure = Figure()
        axes = figure.add_subplot(111)
        
        yAxes = self.signal_read()
        xAxes = [1]
                
        aux = 1
        for x in range (0, len(yAxes)-1):
            aux += 1.0/self.sampleRate
            xAxes.append(aux)
            
        
        axes.plot(xAxes, yAxes)
                 
        canvas = FigureCanvas(figure)
        
        figure.set_figwidth(6)
        figure.set_figheight(2)

        figure.savefig(self.fileImage)
        
        fig = QLabel()
        fig.setPixmap(QPixmap(self.fileImage))
        fig.setFixedSize(600, 200)
        
        return fig

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def quiver_response(lon,
                    lat,
                    dx,
                    dy,
                    request,
                    vectorscale,
                    unit_vectors=False,
                    dpi=80):

    bbox = request.GET['bbox']
    width = request.GET['width']
    height = request.GET['height']
    colormap = request.GET['colormap']
    colorscalerange = request.GET['colorscalerange']
    cmin = colorscalerange.min
    cmax = colorscalerange.max
    crs = request.GET['crs']

    EPSG4326 = pyproj.Proj(init='EPSG:4326')
    x, y = pyproj.transform(EPSG4326, crs, lon, lat)  # TODO order for non-inverse?

    fig = Figure(dpi=dpi, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    fig.set_figheight(height/dpi)
    fig.set_figwidth(width/dpi)

    ax = fig.add_axes([0., 0., 1., 1.], xticks=[], yticks=[])
    ax.set_axis_off()
    mags = np.sqrt(dx**2 + dy**2)

    cmap = mpl.cm.get_cmap(colormap)
    # Set out of bound data to NaN so it shows transparent?
    # Set to black like ncWMS?
    # Configurable by user?
    norm = None
    if cmin is not None and cmax is not None:
        mags[mags > cmax] = cmax
        mags[mags < cmin] = cmin
        bounds = np.linspace(cmin, cmax, 15)
        norm = mpl.colors.BoundaryNorm(bounds, cmap.N)

    # plot unit vectors
    if unit_vectors:
        ax.quiver(x, y, dx/mags, dy/mags, mags, cmap=cmap, scale=vectorscale)
    else:
        ax.quiver(x, y, dx, dy, mags, cmap=cmap, norm=norm, scale=vectorscale)

    ax.set_xlim(bbox.minx, bbox.maxx)
    ax.set_ylim(bbox.miny, bbox.maxy)
    ax.set_frame_on(False)
    ax.set_clip_on(False)
    ax.set_position([0., 0., 1., 1.])

    canvas = FigureCanvasAgg(fig)
    response = HttpResponse(content_type='image/png')
    canvas.print_png(response)
    return response

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def contouring_response(lon, lat, data, request, dpi=None):

    dpi = dpi or 80.

    bbox, width, height, colormap, cmin, cmax, crs = _get_common_params(request)
    nlvls = request.GET['numcontours']

    EPSG4326 = pyproj.Proj(init='EPSG:4326')
    x, y = pyproj.transform(EPSG4326, crs, lon, lat)

    fig = Figure(dpi=dpi, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    fig.set_figheight(height/dpi)
    fig.set_figwidth(width/dpi)

    ax = fig.add_axes([0., 0., 1., 1.], xticks=[], yticks=[])
    ax.set_axis_off()

    if request.GET['logscale'] is True:
        norm_func = mpl.colors.LogNorm
    else:
        norm_func = mpl.colors.Normalize

    if cmin is not None and cmax is not None:
        data[data > cmax] = cmax
        data[data < cmin] = cmin
        lvls = np.linspace(cmin, cmax, nlvls)
        norm = norm_func(vmin=cmin, vmax=cmax)
    else:
        lvls = nlvls
        norm = norm_func()

    if request.GET['image_type'] == 'filledcontours':
        ax.contourf(x, y, data, lvls, norm=norm, cmap=colormap)
    elif request.GET['image_type'] == 'contours':
        ax.contour(x, y, data, lvls, norm=norm, cmap=colormap)
    elif request.GET['image_type'] == 'filledhatches':
        hatches = DEFAULT_HATCHES[:lvls]
        ax.contourf(x, y, data, lvls, norm=norm, cmap=colormap, hatches=hatches)
    elif request.GET['image_type'] == 'hatches':
        hatches = DEFAULT_HATCHES[:lvls]
        ax.contourf(x, y, data, lvls, norm=norm, colors='none', hatches=hatches)

    ax.set_xlim(bbox.minx, bbox.maxx)
    ax.set_ylim(bbox.miny, bbox.maxy)
    ax.set_frame_on(False)
    ax.set_clip_on(False)
    ax.set_position([0., 0., 1., 1.])

    canvas = FigureCanvasAgg(fig)
    response = HttpResponse(content_type='image/png')
    canvas.print_png(response)
    return response

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def tricontourf_response(tri_subset,
                         data,
                         request,
                         dpi=80.0,
                         nlvls=15):
    """
    triang_subset is a matplotlib.Tri object in lat/lon units (will be converted to projected coordinates)
    xmin, ymin, xmax, ymax is the bounding pox of the plot in PROJETED COORDINATES!!!
    request is the original getMap request object
    """
    bbox = request.GET['bbox']
    width = request.GET['width']
    height = request.GET['height']
    colormap = request.GET['colormap']
    colorscalerange = request.GET['colorscalerange']
    cmin = colorscalerange.min
    cmax = colorscalerange.max
    crs = request.GET['crs']

    EPSG4326 = pyproj.Proj(init='EPSG:4326')
    tri_subset.x, tri_subset.y = pyproj.transform(EPSG4326, crs, tri_subset.x, tri_subset.y)

    fig = Figure(dpi=dpi, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    fig.set_figheight(height/dpi)
    fig.set_figwidth(width/dpi)

    ax = fig.add_axes([0., 0., 1., 1.], xticks=[], yticks=[])
    ax.set_axis_off()

    # Set out of bound data to NaN so it shows transparent?
    # Set to black like ncWMS?
    # Configurable by user?
    if cmin and cmax:
        data[data > cmax] = cmax
        data[data < cmin] = cmin
        lvls = np.linspace(float(cmin), float(cmax), int(nlvls))
        ax.tricontourf(tri_subset, data, levels=lvls, cmap=colormap)
    else:
        ax.tricontourf(tri_subset, data, cmap=colormap)

    ax.set_xlim(bbox.minx, bbox.maxx)
    ax.set_ylim(bbox.miny, bbox.maxy)
    ax.set_frame_on(False)
    ax.set_clip_on(False)
    ax.set_position([0., 0., 1., 1.])

    canvas = FigureCanvasAgg(fig)
    response = HttpResponse(content_type='image/png')
    canvas.print_png(response)
    return response

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def create_projected_fig(lonmin, latmin, lonmax, latmax, projection, height, width):
    from mpl_toolkits.basemap import Basemap
    from matplotlib.figure import Figure
    fig = Figure(dpi=80, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    fig.set_figheight(height)
    fig.set_figwidth(width)
    m = Basemap(llcrnrlon=lonmin, llcrnrlat=latmin,
            urcrnrlon=lonmax, urcrnrlat=latmax, projection=projection,
            resolution=None,
            lat_ts = 0.0,
            suppress_ticks=True)
    m.ax = fig.add_axes([0, 0, 1, 1], xticks=[], yticks=[])
    return fig, m

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def contourf_response(lon,
                      lat,
                      data,
                      request,
                      dpi=80,
                      nlvls = 15):

    xmin, ymin, xmax, ymax = wms_handler.get_bbox(request)

    width, height = wms_handler.get_width_height(request)

    colormap = wms_handler.get_colormap(request)

    cmin, cmax = wms_handler.get_climits(request)

    #proj = get_pyproj(request)
    #xcrs, ycrs = proj(lon.flatten(),lat.flatten())
    CRS = get_pyproj(request)
    xcrs, ycrs = pyproj.transform(EPSG4326, CRS, lon.flatten(),lat.flatten()) #TODO order for non-inverse?
    #logger.info("xcrs, ycrs: {0} {1}".format(xcrs, ycrs))

    xcrs = xcrs.reshape(data.shape)
    ycrs = ycrs.reshape(data.shape)

    sxcrs = np.argsort(xcrs[1,:])
    sycrs = np.argsort(ycrs[:,1])

    fig = Figure(dpi=dpi, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    fig.set_figheight(height/dpi)
    fig.set_figwidth(width/dpi)

    ax = fig.add_axes([0., 0., 1., 1.], xticks=[], yticks=[])
    lvls = np.linspace(cmin, cmax, nlvls)

    #ax.contourf(xcrs, ycrs, data, levels=lvls, cmap=colormap)
    ax.contourf(xcrs[sycrs,:][:,sxcrs], ycrs[sycrs,:][:,sxcrs], data[sycrs,:][:,sxcrs], levels=lvls, cmap=colormap)

    ax.set_xlim(xmin, xmax)
    ax.set_ylim(ymin, ymax)
    ax.set_frame_on(False)
    ax.set_clip_on(False)
    ax.set_position([0, 0, 1, 1])
    
    canvas = FigureCanvasAgg(fig)
    
    response = HttpResponse(content_type='image/png')
    canvas.print_png(response)

    return response

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def blank_canvas(width, height, dpi=5):
    """
    return a transparent (blank) response
    used for tiles with no intersection with the current view or for some other error.
    """
    fig = Figure(dpi=dpi, facecolor='none', edgecolor='none')
    fig.set_alpha(0)
    ax = fig.add_axes([0, 0, 1, 1])
    fig.set_figheight(height/dpi)
    fig.set_figwidth(width/dpi)
    ax.set_frame_on(False)
    ax.set_clip_on(False)
    ax.set_position([0, 0, 1, 1])
    canvas = FigureCanvasAgg(fig)
    return canvas

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
    def getImage(self):
    
        figure = Figure()
        axes = figure.add_subplot(111)
        axes.plot(self.signal_read())
                 
        canvas = FigureCanvas(figure)
        
        figure.set_figwidth(6)
        figure.set_figheight(2)

        figure.savefig(self.fileImage)
        
        fig = QLabel()
        fig.setPixmap(QPixmap(self.fileImage))
        fig.setFixedSize(600, 200)
        
        return fig

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figheight [as 别名]
def radial_summary(values,name):
    # Set the colors for the plot
    colors=["#A7DB40","#D8E067","#FFB81F","#FF743D","#C4213D","#707070"]
    
    # Create a figure and a canvas to draw in
    fig = Figure()
    canvas = FigureCanvas(fig)
    fig.set_figwidth(1)
    fig.set_figheight(1)
    
    # Set the figure configuration and parameters
    ax = fig.add_subplot(1,1,1)

    # Plot the pie with the diferent values and colors
    ax.pie(values,colors=colors, shadow=True, startangle=90)
    
    #Save the graphic as an image
    canvas.print_figure('tweetclass/static/tweetclass/summary_pie_'+name+'.png',bbox_inches='tight')