Python Figure.set_figwidth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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [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_figwidth [as 别名]
def general_graph(polarity,name):
    
    # Create a figure and a canvas to draw in
    fig = Figure()
    fig.set_figwidth(12)
    canvas = FigureCanvas(fig)
    
    # Set the legend and the colors for the plot
    legend=["P+",     "P",      "NEU",    "N",      "N+",     "NONE"]
    colors=["#A7DB40","#D8E067","#FFB81F","#FF743D","#C4213D","#707070"]
    
    # Set the figure configuration and parameters
    ax = fig.add_subplot(1,1,1, axisbg='white')
    ax.set_ylabel('Polarity value')
    ax.set_xlabel('Date')
    ax.set_title('Polarity evolution for the query: '+ name)
    
    # Set the x axis indices for every plotting
    N = len(polarity[6])
    ind = np.arange(N)# creates an numpy.array from 0 to N-1
    
    # This is used in order to skip the dates where there is no information
    def format_date(x, pos=None):
        thisind = np.clip(int(x+0.5), 0, N-1)
        return polarity[6][thisind].strftime('%h,%d %Hh.')
    
    ax.autoscale(tight=True)
    ax.grid(True)
    
    i=0
    # Plot all the polarity evolution lines
    while i < 6: 
        ax.plot(ind,polarity[i],colors[i],label=legend[i],linewidth=3)
        i+=1
    # Plot the legend in the graphic
    ax.legend()
    
    # As indices are being used instead of dates, each index has to be
    # asociated with the correspondig date using the funcion defined
    # above
    ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
    fig.autofmt_xdate()
    
    #Save the graphic as an image
    canvas.print_figure('tweetclass/static/tweetclass/histogram_generic_'+name+'.png',facecolor="#EBE8E9",bbox_inches='tight')

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figwidth [as 别名]
 def _draw_figure(self, title, filename, x_values, y_values, x_label, y_label):
     figure = Figure()
     canvas = FigureCanvas(figure)
     axes = figure.add_axes([0.15, 0.1, 0.7, 0.7])
     axes.plot(x_values, y_values)
     axes.grid(True)
     axes.set_xlabel(x_label)
     axes.set_ylabel(y_label)
     axes.set_title(title)
     figure.set_figheight(8)
     figure.set_figwidth(15)
     try:
         figure.savefig(filename)
         #canvas.print_png(filename)
     except Exception, e:
         logger.error(title)
         logger.error(filename)
         logger.error(str(e))

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figwidth [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')

# 需要导入模块: from matplotlib.figure import Figure [as 别名]
# 或者: from matplotlib.figure.Figure import set_figwidth [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