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: 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.tricontourf(tri_subset, data, lvls, norm=norm, cmap=colormap) elif request.GET['image_type'] == 'contours': ax.tricontour(tri_subset, data, lvls, norm=norm, 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.]) return figure_response(fig, request)
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
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
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
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
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
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
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
def blank_figure(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]) return fig
class canvas(FigureCanvas): def __init__(self, parent, double=False): # Se instancia el objeto figure self.fig = Figure() self.fig.set_alpha(0) self.fig.patch.set_facecolor('None') self.fig.patch.set_alpha(0.0) # Se define la grafica en coordenadas polares self.axes = self.fig.add_subplot(111) self.axes.set_facecolor('None') self.axes.set_alpha(0.0) # Se define una grilla self.axes.grid(color='xkcd:mint green', linestyle='-', linewidth=0.5, visible=True) # se inicializa FigureCanvas super(canvas, self).__init__(self.fig) # se define el widget padre self.axes.tick_params(axis='x', colors='xkcd:mint green') self.axes.tick_params(axis='y', colors='xkcd:mint green') if double: self.ax2 = self.axes.twinx() self.ax2.tick_params('y', colors='xkcd:mint green') self.setParent(parent) self.fig.canvas.draw() def reload(self, double=False): self.axes.cla() # Se define una grilla self.axes.grid(True) def plot(self, x, y, y2=None, color1='r', color2='b', double=False): # Dibujar Curva self.reload() if double: self.axes.plot(x, y, color1) self.ax2.plot(x, y2, color2) else: if y2: self.axes.plot(x, y, y2, color1) else: self.axes.plot(x, y, color1) self.fig.canvas.draw()
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
def pcolormesh_response(lon, lat, data, request, dpi=80): bbox, width, height, colormap, cmin, cmax, crs = _get_common_params(request) 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 and cmax: data[data > cmax] = cmax data[data < cmin] = cmin norm = norm = norm_func(vmin=cmin, vmax=cmax) else: norm = norm_func() masked = np.ma.masked_invalid(data) ax.pcolormesh(x, y, masked, norm=norm, 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
def pcolormesh_response(lon, lat, data, request, dpi=None): dpi = dpi or 80. bbox, width, height, colormap, cmin, cmax, crs = _get_common_params( request) 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 and cmax: data[data > cmax] = cmax data[data < cmin] = cmin norm = norm = norm_func(vmin=cmin, vmax=cmax) else: norm = norm_func() masked = np.ma.masked_invalid(data) ax.pcolormesh(x, y, masked, norm=norm, 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
def pcolormesh_response(lon, lat, data, request, dpi=80): params = _get_common_params(request) bbox, width, height, colormap, cmin, cmax, crs = params 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() cmap = mpl.cm.get_cmap(colormap) if cmin and cmax: data[data > cmax] = cmax data[data < cmin] = cmin bounds = np.linspace(cmin, cmax, 15) norm = mpl.colors.BoundaryNorm(bounds, cmap.N) bounds = np.linspace(cmin, cmax, 15) else: norm = None masked = np.ma.masked_invalid(data) ax.pcolormesh(x, y, masked, vmin=5, vmax=30, norm=norm) 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
def quiver_response(lon, lat, dx, dy, height, width, # request, 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 colormap = 'spectral' cmin = 1 cmax = 9 # 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 and cmax: 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(lon, lat, dx/mags, dy/mags, mags, cmap=cmap) else: ax.quiver(lon, lat, dx, dy, mags, cmap=cmap, norm=norm) x_min = np.min(lon) x_max = np.max(lon) y_min = np.min(lat) y_max = np.max(lat) ax.set_xlim(x_min, x_max) ax.set_ylim(y_min, y_min) 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') png_path = 'C:\\Users\\ayan\\Desktop\\tmp\\blah.png' canvas.print_png(png_path) return mags
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 and cmax: 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
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
def getLegendGraphic(request, dataset): """ Parse parameters from request that looks like this: http://webserver.smast.umassd.edu:8000/wms/NecofsWave? ELEVATION=1 &LAYERS=hs &TRANSPARENT=TRUE &STYLES=facets_average_jet_0_0.5_node_False &SERVICE=WMS &VERSION=1.1.1 &REQUEST=GetLegendGraphic &FORMAT=image%2Fpng &TIME=2012-06-20T18%3A00%3A00 &SRS=EPSG%3A3857 &LAYER=hs """ styles = request.GET["styles"].split("_") try: climits = (float(styles[3]), float(styles[4])) except: climits = (None, None) variables = request.GET["layer"].split(",") plot_type = styles[0] colormap = styles[2].replace('-', '_') # direct the service to the dataset # make changes to server_local_config.py if settings.LOCALDATASET: url = settings.LOCALDATASETPATH[dataset] else: url = Dataset.objects.get(name=dataset).path() nc = netCDF4.Dataset(url) """ Create figure and axes for small legend image """ #from matplotlib.figure import Figure from matplotlib.pylab import get_cmap fig = Figure(dpi=100., facecolor='none', edgecolor='none') fig.set_alpha(0) fig.set_figwidth(1*1.3) fig.set_figheight(1.5*1.3) """ Create the colorbar or legend and add to axis """ v = cf.get_by_standard_name(nc, variables[0]) try: units = v.units except: units = '' # vertical level label if v.ndim > 3: units = units + '\nvertical level: %s' % _get_vertical_level(nc, v) if climits[0] is None or climits[1] is None: # TODO: NOT SUPPORTED RESPONSE #going to have to get the data here to figure out bounds #need elevation, bbox, time, magnitudebool CNorm = None ax = fig.add_axes([0, 0, 1, 1]) ax.grid(False) ax.text(.5, .5, 'Error: No Legend\navailable for\nautoscaled\ncolor styles!', ha='center', va='center', transform=ax.transAxes, fontsize=8) elif plot_type not in ["contours", "filledcontours"]: #use limits described by the style ax = fig.add_axes([.01, .05, .2, .8]) # xticks=[], yticks=[]) CNorm = matplotlib.colors.Normalize(vmin=climits[0], vmax=climits[1], clip=False, ) cb = matplotlib.colorbar.ColorbarBase(ax, cmap=get_cmap(colormap), norm=CNorm, orientation='vertical', ) cb.set_label(units, size=8) else: # plot type somekind of contour if plot_type == "contours": #this should perhaps be a legend... #ax = fig.add_axes([0,0,1,1]) fig_proxy = Figure(frameon=False, facecolor='none', edgecolor='none') ax_proxy = fig_proxy.add_axes([0, 0, 1, 1]) CNorm = matplotlib.colors.Normalize(vmin=climits[0], vmax=climits[1], clip=True) #levs = numpy.arange(0, 12)*(climits[1]-climits[0])/10 levs = numpy.linspace(climits[0], climits[1], 11) x, y = numpy.meshgrid(numpy.arange(10), numpy.arange(10)) cs = ax_proxy.contourf(x, y, x, levels=levs, norm=CNorm, cmap=get_cmap(colormap)) proxy = [plt.Rectangle((0, 0), 0, 0, fc=pc.get_facecolor()[0]) for pc in cs.collections] fig.legend(proxy, levs, #bbox_to_anchor = (0, 0, 1, 1), #bbox_transform = fig.transFigure, loc = 6, title = units, prop = { 'size' : 8 }, frameon = False, ) elif plot_type == "filledcontours": #this should perhaps be a legend... #ax = fig.add_axes([0,0,1,1]) fig_proxy = Figure(frameon=False, facecolor='none', edgecolor='none') ax_proxy = fig_proxy.add_axes([0, 0, 1, 1]) CNorm = matplotlib.colors.Normalize(vmin=climits[0], vmax=climits[1], clip=False,) #levs = numpy.arange(1, 12)*(climits[1]-(climits[0]))/10 levs = numpy.linspace(climits[0], climits[1], 10) levs = numpy.hstack(([-99999], levs, [99999])) x, y = numpy.meshgrid(numpy.arange(10), numpy.arange(10)) cs = ax_proxy.contourf(x, y, x, levels=levs, norm=CNorm, cmap=get_cmap(colormap)) proxy = [plt.Rectangle((0, 0), 0, 0, fc=pc.get_facecolor()[0]) for pc in cs.collections] levels = [] for i, value in enumerate(levs): #if i == 0: # levels[i] = "<" + str(value) if i == len(levs)-2 or i == len(levs)-1: levels.append("> " + str(value)) elif i == 0: levels.append("< " + str(levs[i+1])) else: #levels.append(str(value) + "-" + str(levs[i+1])) text = '%.2f-%.2f' % (value, levs[i+1]) levels.append(text) fig.legend(proxy, levels, #bbox_to_anchor = (0, 0, 1, 1), #bbox_transform = fig.transFigure, loc = 6, title = units, prop = { 'size' : 6 }, frameon = False, ) canvas = FigureCanvasAgg(fig) response = HttpResponse(content_type='image/png') canvas.print_png(response) nc.close() return response
class StylistTkinter(ttk.Frame): _WINDOW_TITLE = "Generic Title" opts = {} mplparams = {} """ Present tool sytlization choices for a matplotlib plot. 1. Create the plot required to build this up 2. Create all of the appropriate widgets """ def styleChange(self, name1, name2, op): """ :param name1: http://www.tcl.tk/man/tcl8.4/TclCmd/trace.htm#M14 :param name2: http://www.tcl.tk/man/tcl8.4/TclCmd/trace.htm#M14 :param op: http://www.tcl.tk/man/tcl8.4/TclCmd/trace.htm#M14 """ logging.debug("styleChange detected with arguments (%s, %s, %s)" % (name1, name2, op)) logging.debug("styleChange executing a change from to %s", self.mpl_global_style.get()) plt.style.use( self.mpl_global_style.get() ) # TODO can you set this up to use name1 ? Yes, tk.StringVar() contains _name # clean up the existing stuff, deleting all of the components within the canvas self.canvas.get_tk_widget().delete("all") for child in self.mplframe.winfo_children(): child.destroy() self.figure.clear() self.axes.clear() del self.line, self.axes, self.figure # recretae the plot, the frame it resides in is already created and useful self.createPlot() logging.debug("styleChange completed with new style changed to %s" % self.mpl_global_style.get()) def loadOptions(self): logging.debug("loadOptions invocation") self.opts["mpl_style_idx"] = 0 self.mplparams["styles"] = plt.style.available logging.debug('loadOptions set self.mplparams["styles"] = %s' % repr(self.mplparams["styles"])) optpath = os.path.join(os.getcwd(), "res", "stylist.opt") logging.debug("loading options: loading option file from %s" % (optpath)) self.master.option_readfile(optpath) # fixme having some trouble with the namespaces of the options database def applyOptions(self): logging.debug("applyOptions invocation") plt.style.use(self.mplparams["styles"][self.opts["mpl_style_idx"]]) for s in self.mplparams["styles"]: if self.opts["mpl_style_idx"] == s: self.mplparams["style_default"] = self.mplparams["styles"].index[s] def createPlot(self): logging.debug("createPlot invocation") self.figure = Figure(figsize=(5, 4), dpi=100) self.axes = self.figure.add_subplot(111) self.line, = self.axes.plot(self.x, self.y) self.canvas = FigureCanvasTkAgg(self.figure, master=self.mplframe) self.canvas.show() # add the mpl toolbar to the toolbar self.toolbar = NavigationToolbar2TkAgg(self.canvas, self.mplframe) self.toolbar.update() self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1) def scaleFigAlpha(self, value): logging.debug("scaleFigAlpha called with alpha = %s" % value) self.figure.set_alpha(value) def createWidgets(self): logging.debug("createWidgets invocation") # todo add a menu region # a tk.DrawingArea containing the appropriate toolbars logging.debug("createWidgets building Matplotlib components for Tkinter integration") self.mplframe = ttk.Frame(class_="matplotstylist", name="mplframe") self.createPlot() self.mplframe.pack(side=tk.LEFT, fill=tk.BOTH, expand=1) # The following contains the right hand style configuration area self.styleframe = ttk.Frame(class_="matplotstylist", name="styleframe") self.styleframe.pack(side=tk.RIGHT, anchor=tk.NE, fill=tk.X, expand=1, ipadx=2, ipady=2, padx=2, pady=2) # todo evaluation if you should Add a listbox describing the potentially available styles, permits compositing # self.lbx_styles = tk.Listbox(self, activestyle='dotbox', # listvariable=tk.StringVar(value=" ".join(self.mplparams["styles"]) # , name="mplparams.styles"), # selectmode=tk.SINGLE) # self.lbx_styles.activate(self.opts['mpl_style_idx']) # self.lbx_styles.pack(side=tk.LEFT, fill=tk.BOTH, expand=1) # Add an OptionsMenu describing the potentially available styles self.mpl_global_style = tk.StringVar() self.mpl_global_style.set(self.mplparams["styles"][self.opts["mpl_style_idx"]]) self.omu_styles = tk.OptionMenu(self.styleframe, self.mpl_global_style, *self.mplparams["styles"]) self.omu_styles.pack(side=tk.TOP, fill=tk.X, expand=1) logging.debug("createWidgets creating and populating styleframe artist's notebook") self.artist_notebook = ArtistStyleBook(self.styleframe) # add one tab for each type of artist in the plot """ populate the artists notebook with the controls to set/get each and every setable property of the artists used by the figure and its children. Each artist may be inspected interactively using matplotlib.artist.getp(object), which lists each property and their values. These same properties may be identified using "artists" """ self.styletab_figure = FigureParametrics(self.artist_notebook, self.figure) self.styletab_axes = AxesParametrics(self.artist_notebook, self.axes) self.styletab_primitives = PrimitiveParametrics(self.artist_notebook, self.figure) self.artist_notebook.add(self.styletab_figure, sticky=tk.N + tk.E + tk.S + tk.W, text="Figure") self.artist_notebook.add(self.styletab_axes, sticky=tk.N + tk.E + tk.S + tk.W, text="Axes") self.artist_notebook.add(self.styletab_primitives, sticky=tk.N + tk.E + tk.S + tk.W, text="Primitives") # Lay it out self.artist_notebook.pack(side=tk.TOP, fill=tk.BOTH, expand=1) logging.debug("createWidgets creating options for master window") self.master.wm_title(self._WINDOW_TITLE) self.master.wm_minsize(width=1024, height=640) self.master.wm_iconbitmap() self.pack() def bindWidgetVariables(self): self.mpl_global_style.trace("w", self.styleChange) def bindWidgetEvents(self): pass def __init__(self, master=None): ttk.Frame.__init__(self, master, class_="matplotstylist") plt.ion() self.loadOptions() self.applyOptions() StylistTheme.configure() self.x = arange(0.0, pi, 0.01) self.y = sin(2 * pi * self.x) self.createWidgets() self.bindWidgetVariables() self.bindWidgetEvents() # TODO: can we change any master level features such as title and author for this frame @staticmethod def launch(style=None): logging.debug("%s launch invoked with style %s" % (repr(StylistTkinter), repr(style))) global app ttk.Style().theme_use(style) app = StylistTkinter() app.mainloop() try: app.destroy() except tk.TclError as terr: if not terr.message == 'can\'t invoke "destroy" command: application has been destroyed': logging.error(repr(terr)) else: logging.debug(terr.message)
class Plotter(IOTABasePanel): ''' Class with function to plot various PRIME charts (includes Table 1) ''' def __init__(self, parent, info, output_dir=None, anomalous_flag=False, *args, **kwargs): IOTABasePanel.__init__(self, parent=parent, *args, **kwargs) self.target_anomalous_flag = anomalous_flag self.info = info self.output_dir = output_dir def initialize_figure(self, figsize=(8, 8)): self.figure = Figure(figsize=figsize) self.canvas = FigureCanvas(self, -1, self.figure) self.main_sizer.Add(self.canvas, 1, flag=wx.EXPAND) def table_one(self): ''' Constructs Table 1 for GUI or logging ''' A = u'\N{ANGSTROM SIGN}' d = u'\N{DEGREE SIGN}' a = u'\N{GREEK SMALL LETTER ALPHA}' b = u'\N{GREEK SMALL LETTER BETA}' g = u'\N{GREEK SMALL LETTER GAMMA}' s = u'\N{GREEK SMALL LETTER SIGMA}' h = u'\u00BD' uc_edges = '{:4.2f}, {:4.2f}, {:4.2f}'.format(self.info['mean_a'][-1], self.info['mean_b'][-1], self.info['mean_c'][-1]) uc_angles = '{:4.2f}, {:4.2f}, {:4.2f}'.format( self.info['mean_alpha'][-1], self.info['mean_beta'][-1], self.info['mean_gamma'][-1]) res_total = '{:4.2f} - {:4.2f}'.format(self.info['total_res_max'][-1], self.info['total_res_min'][-1]) res_last_shell = '{:4.2f} - {:4.2f}' \ ''.format(self.info['binned_resolution'][-1][-2], self.info['binned_resolution'][-1][-1]) t1_rlabels = [ u.to_unicode(u'No. of accepted images'), u.to_unicode(u'No. of rejected images'), u.to_unicode(u'Space Group'), u.to_unicode(u'Cell dimensions'), u.to_unicode(u' a, b, c ({}) '.format(A)), u.to_unicode(u' {}, {}, {} ({}) '.format(a, b, g, d)), u.to_unicode(u'Resolution ({}) '.format(A)), u.to_unicode(u'Completeness (%)'), u.to_unicode(u'Multiplicity'), u.to_unicode(u'I / {}(I) '.format(s)), u.to_unicode(u'CC{} '.format(h)), u.to_unicode(u'R_merge') ] n_frames_bad = self.info['n_frames_bad_cc'][-1] + \ self.info['n_frames_bad_G'][-1] + \ self.info['n_frames_bad_uc'][-1] + \ self.info['n_frames_bad_gamma_e'][-1] + \ self.info['n_frames_bad_SE'][-1] t1_data = [ ['{}'.format(self.info['n_frames_good'][-1])], ['{}'.format(n_frames_bad)], ['{}'.format(self.info['space_group_info'][-1])], [''], ['{}'.format(uc_edges)], ['{}'.format(uc_angles)], ['{} ({})'.format(res_total, res_last_shell)], [ '{:4.2f} ({:4.2f})'.format( self.info['total_completeness'][-1], self.info['binned_completeness'][-1][-1]) ], [ '{:4.2f} ({:4.2f})'.format(self.info['total_n_obs'][-1], self.info['binned_n_obs'][-1][-1]) ], [ '{:4.2f} ({:4.2f})'.format( self.info['total_i_o_sigi'][-1], self.info['binned_i_o_sigi'][-1][-1]) ], [ '{:4.2f} ({:4.2f})'.format( self.info['total_cc12'][-1], self.info['binned_cc12'][-1][-1] * 100) ], [ '{:4.2f} ({:4.2f})'.format(self.info['total_rmerge'][-1], self.info['binned_rmerge'][-1][-1]) ] ] return t1_rlabels, t1_data def stat_charts(self): ''' Displays charts of CC1/2, Completeness, Multiplicity and I / sig(I) per resolution bin after the final cycle of post-refinement ''' gsp = gridspec.GridSpec(2, 2) self.figure.set_alpha(0) rc('font', family='sans-serif', size=12) rc('mathtext', default='regular') x = self.info['binned_resolution'][-1] bins = np.arange(len(x)) xlabels = ["{:.2f}".format(i) for i in x] sel_bins = bins[0::len(bins) // 6] sel_xlabels = [xlabels[t] for t in sel_bins] # Plot CC1/2 vs. resolution ax_cc12 = self.figure.add_subplot(gsp[0]) reslabel = 'Resolution ({})'.format(r'$\AA$') ax_cc12.set_xlabel(reslabel, fontsize=15) ax_cc12.ticklabel_format(axis='y', style='plain') ax_cc12.set_ylim(0, 100) if self.target_anomalous_flag: ax_cc12.set_ylabel(r'$CC_{1/2}$ anom (%)', fontsize=15) else: ax_cc12.set_ylabel(r'$CC_{1/2}$ (%)', fontsize=15) ax_cc12.set_xticks(sel_bins) ax_cc12.set_xticklabels(sel_xlabels) ax_cc12.grid(True) cc12_start_percent = [c * 100 for c in self.info['binned_cc12'][0]] cc12_end_percent = [c * 100 for c in self.info['binned_cc12'][-1]] start, = ax_cc12.plot(bins, cc12_start_percent, c='#7fcdbb', lw=2) end, = ax_cc12.plot(bins, cc12_end_percent, c='#2c7fb8', lw=3) labels = ['Initial', 'Final'] ax_cc12.legend([start, end], labels, loc='lower left', fontsize=9, fancybox=True) # Plot Completeness vs. resolution ax_comp = self.figure.add_subplot(gsp[1]) ax_comp.set_xlabel(reslabel, fontsize=15) ax_comp.ticklabel_format(axis='y', style='plain') ax_comp.set_ylabel('Completeness (%)', fontsize=15) ax_comp.set_xticks(sel_bins) ax_comp.set_xticklabels(sel_xlabels) ax_comp.set_ylim(0, 100) ax_comp.grid(True) start, = ax_comp.plot(bins, self.info['binned_completeness'][0], c='#7fcdbb', lw=2) end, = ax_comp.plot(bins, self.info['binned_completeness'][-1], c='#2c7fb8', lw=3) labels = ['Initial', 'Final'] ax_comp.legend([start, end], labels, loc='lower left', fontsize=9, fancybox=True) # Plot Multiplicity (no. of observations) vs. resolution ax_mult = self.figure.add_subplot(gsp[2]) ax_mult.set_xlabel(reslabel, fontsize=15) ax_mult.ticklabel_format(axis='y', style='plain') ax_mult.set_ylabel('# of Observations', fontsize=15) ax_mult.set_xticks(sel_bins) ax_mult.set_xticklabels(sel_xlabels) ax_mult.grid(True) start, = ax_mult.plot(bins, self.info['binned_n_obs'][0], c='#7fcdbb', lw=2) end, = ax_mult.plot(bins, self.info['binned_n_obs'][-1], c='#2c7fb8', lw=3) labels = ['Initial', 'Final'] ax_mult.legend([start, end], labels, loc='lower left', fontsize=9, fancybox=True) # Plot I / sig(I) vs. resolution ax_i_sigi = self.figure.add_subplot(gsp[3]) ax_i_sigi.set_xlabel(reslabel, fontsize=15) ax_i_sigi.ticklabel_format(axis='y', style='plain') ax_i_sigi.set_ylabel(r'I / $\sigma$(I)', fontsize=15) ax_i_sigi.set_xticks(sel_bins) ax_i_sigi.set_xticklabels(sel_xlabels) ax_i_sigi.grid(True) start, = ax_i_sigi.plot(bins, self.info['binned_i_o_sigi'][0], c='#7fcdbb', lw=2) end, = ax_i_sigi.plot(bins, self.info['binned_i_o_sigi'][-1], c='#2c7fb8', lw=3) labels = ['Initial', 'Final'] ax_i_sigi.legend([start, end], labels, loc='lower left', fontsize=9, fancybox=True) self.figure.set_tight_layout(True)
class ResidualPlot(FigureCanvas): __instance = None def __init__(self): Global.event.task_selected.connect(self._on_task_selected) Global.event.plot_x_limit_changed.connect(self._on_x_limit_changed) Global.event.task_deleted.connect(self._on_task_deleted) Global.event.tasks_list_updated.connect(self._on_tasks_list_updated) self.task = None self.axes = None self.last_x_limit = [] self.chi2s = [] bg_color = str(QPalette().color(QPalette.Active, QPalette.Window).name()) rcParams.update({'font.size': 10}) self.figure = Figure(facecolor=bg_color, edgecolor=bg_color) self.figure.hold(False) super(ResidualPlot, self).__init__(self.figure) self.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding) self.updateGeometry() self.hide() def _on_task_selected(self, task): self.set_task(task) self.redraw() def _on_task_deleted(self, task): if self.task == task: self.set_task(None) self.clear() def _on_tasks_list_updated(self): if not len(Global.tasks()): self.set_task(None) self.clear() def set_task(self, task): self.task = task def clear(self): self.figure.clf() self.figure.clear() self.draw() self.parent().chi2_label.hide() self.parent().chi2_value.hide() self.hide() gc.collect() def redraw(self): self.clear() if self.task.result.chi2 is None: self.parent().chi2_label.hide() self.parent().chi2_value.hide() self.hide() return self.chi2s.append(self.task.result.chi2) self.show() self.parent().chi2_label.show() self.parent().chi2_value.show() self.axes = self.figure.add_subplot(1, 1, 1) self.axes.grid(False) self.figure.set_alpha(0) self.axes.set_xlabel('Phase') self.axes.set_ylabel('Residual') phases = [] delta_values = [] keys = sorted(self.task.result.data().keys()) for key in keys: if self.task.result.data()[key]['delta_value'] is not None: phases.append(key) delta_values.append(self.task.result.data()[key]['delta_value']) y_max = max(abs(min(delta_values)), abs(max(delta_values))) y_pad = (y_max / 100) * 10 self.axes.set_autoscaley_on(False) self.axes.set_ylim([-(y_max + y_pad), y_max + y_pad]) self.axes.set_autoscalex_on(False) self.axes.set_xlim(self.last_x_limit) color = QColor(0,0,0) min_chi2 = min(self.chi2s) if len(self.chi2s) == 1 : color = QColor(0,0,0) elif self.task.result.chi2 <= min_chi2 : color = QColor(0,139,0) else: color = QColor(255,0,0) self.axes.axhline(y=0, ls='--', linewidth=0.5, color='black') self.axes.scatter(phases, delta_values, s=0.5, color='r') palette = self.parent().chi2_value.palette() palette.setColor(QPalette.Active, QPalette.Text, color) self.parent().chi2_value.setPalette(palette) self.parent().chi2_value.setText(str(self.task.result.chi2)) self.draw() def _on_x_limit_changed(self, limit): self.last_x_limit = limit
def quiver_response(lon, lat, dx, dy, request, unit_vectors=False, dpi=80): from django.http import HttpResponse xmin, ymin, xmax, ymax = wms_handler.get_bbox(request) width, height = wms_handler.get_width_height(request) colormap = wms_handler.get_colormap(request) climits = wms_handler.get_climits(request) cmax = 1. cmin = 0. if len(climits) == 2: cmin, cmax = climits else: logger.debug("No climits, default cmax to 1.0") # cmax = 10. #proj = get_pyproj(request) #x, y = proj(lon, lat) CRS = get_pyproj(request) x, y = pyproj.transform(EPSG4326, CRS, lon, lat) #TODO order for non-inverse? #logger.info("x, y: {0} {1}".format(x, 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() #scale to cmin - cmax # dx = cmin + dx*(cmax-cmin) # dy = cmin + dy*(cmax-cmin) mags = np.sqrt(dx**2 + dy**2) # mags[mags>cmax] = cmax mags[mags>cmax] = cmax mags[mags<cmin] = cmin import matplotlib as mpl cmap = mpl.cm.get_cmap(colormap) 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=colormap) else: ax.quiver(x, y, dx, dy, mags, cmap=cmap, norm=norm) #ax.quiver(x, y, dx/mags, dy/mags, mags, cmap=colormap,norm=norm) 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
def tricontourf_response(triang_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 """ from django.http import HttpResponse 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) #logger.info('cmin/cmax: {0} {1}'.format(cmin, cmax)) # TODO: check this? try: data[data>cmax] = cmax data[data<cmin] = cmin except: exc_type, exc_value, exc_traceback = sys.exc_info() logger.warning("tricontourf_response error: " + repr(traceback.format_exception(exc_type, exc_value, exc_traceback))) clvls = wms_handler.get_clvls(request) #proj = get_pyproj(request) #triang_subset.x, triang_subset.y = proj(triang_subset.x, triang_subset.y) CRS = get_pyproj(request) triang_subset.x, triang_subset.y = pyproj.transform(EPSG4326, CRS, triang_subset.x, triang_subset.y) #TODO order for non-inverse? #logger.info('TRANSFORMED triang_subset.x: {0}'.format(triang_subset.x)) #logger.info('TRANSFORMED triang_subset.y: {0}'.format(triang_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() lvls = np.linspace(float(cmin), float(cmax), int(clvls)) #logger.info('trang.shape: {0}'.format(triang_subset.x.shape)) #logger.info('data.shape: {0}'.format(data.shape)) ax.tricontourf(triang_subset, data, 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.]) #plt.axis('off') canvas = FigureCanvasAgg(fig) response = HttpResponse(content_type='image/png') canvas.print_png(response) return response