我们从Python开源项目中，提取了以下9个代码示例，用于说明如何使用matplotlib.colors.hsv_to_rgb()。
def main(imgsize): y, x = np.ogrid[6: -6: imgsize*2j, -6: 6: imgsize*2j] z = x + y*1j z = RiemannSphere(Klein(Mobius(Klein(z)))) # define colors in hsv space H = np.sin(z[0]*np.pi)**2 S = np.cos(z[1]*np.pi)**2 V = abs(np.sin(z[2]*np.pi) * np.cos(z[2]*np.pi))**0.2 HSV = np.dstack((H, S, V)) # transform to rgb space img = hsv_to_rgb(HSV) fig = plt.figure(figsize=(imgsize/100.0, imgsize/100.0), dpi=100) ax = fig.add_axes([0, 0, 1, 1], aspect=1) ax.axis('off') ax.imshow(img) fig.savefig('kaleidoscope.png')
def plot_candidates(self): """Plot a representation of candidate periodicity Size gives the periodicity strength, color the order of preference """ fig, ax = pl.subplots(2, sharex=True) hues = np.arange(self.ncand)/float(self.ncand) hsv = np.swapaxes(np.atleast_3d([[hues, np.ones(len(hues)), np.ones(len(hues))]]), 1, 2) cols = hsv_to_rgb(hsv).squeeze() for per in self.periods: nc = len(per.cand_period) ax[0].scatter(per.time*np.ones(nc), per.cand_period, s=per.cand_strength*100, c=cols[0:nc], alpha=.5) ax[0].plot(*zip(*[[per.time, float(per.get_preferred_period())] for per in self.periods]), color='k') ax[1].plot(self.get_times(), self.get_strength())
def update_fig(self, data): self.series[0].set_data(0, data) hue = self.hue_transfer_function(data) color = hsv_to_rgb([hue, 1, 0.75]) self.series[0].set_color(color) return self.series
def get_gamma_colors(nr_colors): hsv_colors = np.ones((nr_colors, 3)) hsv_colors[:, 0] = (np.linspace(0, 1, nr_colors, endpoint=False) + 2/3) % 1.0 color_conv = hsv_to_rgb(hsv_colors) return color_conv
def hue_map(self, value): ''' :param value: number 0 to 1, map to hue 0.6 - 0 (blue to red, like heatmap) more highter the value, more warm the color :return: hex of rgb ''' HUE_MAX = 0.6 hue = pow(1 - value, 2) * HUE_MAX rgb = colors.hsv_to_rgb((hue, 1, 1)) hex = colors.to_hex(rgb) return hex
def visualize_flow(flow, mode='Y'): """ this function visualize the input flow :param flow: input flow in array :param mode: choose which color mode to visualize the flow (Y: Ccbcr, RGB: RGB color) :return: None """ if mode == 'Y': # Ccbcr color wheel img = flow_to_image(flow) plt.imshow(img) plt.show() elif mode == 'RGB': (h, w) = flow.shape[0:2] du = flow[:, :, 0] dv = flow[:, :, 1] valid = flow[:, :, 2] max_flow = max(np.max(du), np.max(dv)) img = np.zeros((h, w, 3), dtype=np.float64) # angle layer img[:, :, 0] = np.arctan2(dv, du) / (2 * np.pi) # magnitude layer, normalized to 1 img[:, :, 1] = np.sqrt(du * du + dv * dv) * 8 / max_flow # phase layer img[:, :, 2] = 8 - img[:, :, 1] # clip to [0,1] small_idx = img[:, :, 0:3] < 0 large_idx = img[:, :, 0:3] > 1 img[small_idx] = 0 img[large_idx] = 1 # convert to rgb img = cl.hsv_to_rgb(img) # remove invalid point img[:, :, 0] = img[:, :, 0] * valid img[:, :, 1] = img[:, :, 1] * valid img[:, :, 2] = img[:, :, 2] * valid # show plt.imshow(img) plt.show() return None
def plot_candidates(self): """Plot a representation of candidate periodicity Size gives the periodicity strength, color the order of preference """ hues = np.arange(self.ncand)/float(self.ncand) hsv = np.swapaxes(np.atleast_3d([[hues,np.ones(len(hues)),np.ones(len(hues))]]),1,2) cols = hsv_to_rgb(hsv).squeeze() for per in self.periods: nc = len(per.cand_period) pl.scatter(per.time*np.ones(nc),per.cand_period,s=per.cand_strength*100,c=cols[0:nc],alpha=.5)
def render_jump_range(params=None): if not putil.has_any(params): raise CommandException('Specify an origin system to render the jump range from') origin_fragment = putil.single_str(params) destination_fragment = putil.retrieve_value(params, '-d', None) hashes = database.get_star_log_hashes() origin_hash = putil.natural_match(origin_fragment, hashes) if origin_hash is None: raise CommandException('Unable to find an origin system containing %s' % origin_fragment) destination_hash = None highest = None if destination_fragment is not None: destination_hash = putil.natural_match(destination_fragment, hashes) if destination_hash is None: raise CommandException('Unable to find a destination system containing %s' % destination_fragment) if not database.get_star_logs_share_chain([origin_hash, destination_hash]): raise CommandException('Systems %s and %s exist on different chains' % (util.get_system_name(origin_hash), util.get_system_name(destination_hash))) highest = database.get_star_log_highest(database.get_star_log_highest_from_list([origin_hash, destination_hash]))['hash'] figure = pyplot.figure() axes = figure.add_subplot(111, projection='3d') hue_start = 0.327 hue_end = 0.0 hue_delta = hue_end - hue_start for current_system in database.get_star_log_hashes(highest): cost = util.get_jump_cost(origin_hash, current_system) cost_hue = hue_start + (cost * hue_delta) cost_value = 0.0 if cost == 1.0 else 1.0 color = pycolors.hsv_to_rgb([cost_hue, 0.7, cost_value]) current_position = util.get_cartesian(current_system) xs = [current_position[0], current_position[0]] ys = [current_position[1], current_position[1]] zs = [0, current_position[2]] axes.plot(xs, ys, zs, c=color) marker = '^' if current_system == origin_hash else 'o' axes.scatter(current_position[0], current_position[1], current_position[2], label=util.get_system_name(current_system), c=color, marker=marker) if destination_hash is not None: origin_position = util.get_cartesian(origin_hash) destination_position = util.get_cartesian(destination_hash) xs = [origin_position[0], destination_position[0]] ys = [origin_position[1], destination_position[1]] zs = [origin_position[2], destination_position[2]] axes.plot(xs, ys, zs, linestyle=':') axes.legend() axes.set_title('Jump Range %s' % util.get_system_name(origin_hash)) axes.set_xlabel('X') axes.set_ylabel('Y') axes.set_zlabel('Z') pyplot.show()
