# Copyright (c) 2024-present, Yumeow. Licensed under the MIT License. import os import re import numpy as np import matplotlib.pyplot as plt import matplotlib.colors as mcolors from typing import List, Dict, Literal, Tuple def get_fig(RN, CN, FW=None, FH=None, AW=None, AH=None, A_ratio=1.0, LM=3, RM=3, TM=3, BM=3, HS=None, VS=None, dpi=300, fontsize=7, lw=0.5, gridspec=False, **kwargs): # 基础字体和尺寸 plt.rcParams['font.family'] = kwargs.get('font_family', 'Arial') plt.rcParams['font.size'] = fontsize # --- 字体大小设置 (Font Sizes) --- plt.rcParams['axes.labelsize'] = fontsize plt.rcParams['axes.titlesize'] = fontsize plt.rcParams['xtick.labelsize'] = fontsize * (5/7) plt.rcParams['ytick.labelsize'] = fontsize * (5/7) plt.rcParams['legend.fontsize'] = fontsize * (5/7) plt.rcParams['figure.titlesize'] = fontsize # --- 线条宽度设置 (Line Widths) --- plt.rcParams['lines.linewidth'] = lw plt.rcParams['axes.linewidth'] = lw plt.rcParams['xtick.major.width'] = lw plt.rcParams['ytick.major.width'] = lw plt.rcParams['xtick.minor.width'] = lw plt.rcParams['ytick.minor.width'] = lw plt.rcParams['grid.linewidth'] = lw plt.rcParams['patch.linewidth'] = lw # --- 导出设置 (Export Settings) --- plt.rcParams['pdf.fonttype'] = 42 plt.rcParams['svg.fonttype'] = 'none' LM = LM * fontsize / 72 RM = RM * fontsize / 72 TM = TM * fontsize / 72 BM = BM * fontsize / 72 HS = HS * fontsize / 72 if HS is not None else LM VS = VS * fontsize / 72 if VS is not None else TM if AW is not None: AW /= 2.54 FW = LM + CN * AW + (CN - 1) * HS + RM if AH is not None: AH /= 2.54 FH = TM + RN * AH + (RN - 1) * VS + BM A_ratio = AW / AH else: AH = AW / A_ratio FH = TM + RN * AH + (RN - 1) * VS + BM elif AH is not None: AH /= 2.54 AW = AH * A_ratio FH = TM + RN * AH + (RN - 1) * VS + BM FW = LM + CN * AW + (CN - 1) * HS + RM elif FW is not None: FW /= 2.54 AW = (FW - LM - RM - (CN - 1) * HS) / CN if FH is not None: FH /= 2.54 AH = (FH - TM - BM - (RN - 1) * VS) / RN A_ratio = AW / AH else: AH = AW / A_ratio FH = TM + RN * AH + (RN - 1) * VS + BM elif FH is not None: FH /= 2.54 AH = (FH - TM - BM - (RN - 1) * VS) / RN AW = AH * A_ratio FW = LM + CN * AW + (CN - 1) * HS + RM figinfo = dict(RN=RN, CN=CN, FW=FW, FH=FH, AW=AW, AH=AH, LM=LM, RM=RM, TM=TM, BM=BM, HS=HS, VS=VS, r_AW=AW/FW, r_AH=AH/FH, r_HS=HS/FW, r_VS=VS/FH, r_LM=LM/FW, r_RM=RM/FW, r_TM=TM/FH, r_BM=BM/FH, fontsize=fontsize, lw=lw, top_box=(LM/FW, 1-TM/FH, 1-(LM+RM)/FW, TM/FH), bottom_box=(LM/FW, 0, 1-(LM+RM)/FW, BM/FH), right_box=(1-RM/FW, BM/FH, RM/FW, 1-(TM+BM)/FH), left_box=(0, BM/FH, LM/FW, 1-(TM+BM)/FH), ) if gridspec: fig = plt.figure(figsize=(FW, FH), dpi=dpi, **kwargs) gs = fig.add_gridspec(RN, CN, wspace=HS/AW, hspace=VS/AH, left=LM/FW, right=1-RM/FW, top=1-TM/FH, bottom=BM/FH) return figinfo, fig, gs else: fig, axes = plt.subplots(RN, CN, figsize=(FW, FH), dpi=dpi, **kwargs) fig.subplots_adjust(left=LM/FW, right=1-RM/FW, top=1-TM/FH, bottom=BM/FH, wspace=HS/AW, hspace=VS/AH) axes = axes.ravel() if RN * CN > 1 else [axes] return figinfo, fig, axes def plot_resilience(f:callable, extent=(0, 1, 0, 1), gridnum=(1000, 1000), cmap=None, norm=None, ax=None, reset_xylim=True, lw=1): """ 绘制二维函数的韧性 - f: 二维函数，如 lambda x, y: y - 3*y**2 - y**3 + x*y**3 - extent: 函数定义域 (xmin, xmax, ymin, ymax) - gridnum: 网格数量 (xnum, ynum) --- Example: >>> f = lambda x, y: y - 3*y**2 - y**3 + x*y**3 >>> plot_resilience(f, ax=axes[0], extent=(0, 5, 0, 5)) >>> f = lambda x, y: np.sin(np.sqrt(x**2 + y ** 2)) >>> plot_resilience(f, ax=axes[1], extent=(-4*np.pi, 4*np.pi, -4*np.pi, 4*np.pi)) >>> f = lambda x, y: np.sin(np.sqrt(x ** 2 + y ** 2)) * x - y * np.cos(np.sqrt(x ** 2 + y ** 2)) >>> plot_resilience(f, ax=axes[2], extent=(-4*np.pi, 4*np.pi, -4*np.pi, 4*np.pi)) """ if cmap is None: cmap = mcolors.LinearSegmentedColormap.from_list('my_bwr', ['#74b9ff', 'white', '#ff7675']) if norm is None: norm = mcolors.SymLogNorm(linthresh=0.01, linscale=0.01, vmin=-1, vmax=1) if ax is None: ax = plt.gca() def plot1(x, y): ax.plot(x, y, 'black', linewidth=lw, linestyle='-', solid_capstyle='round') def plot2(x, y): ax.plot(x, y, 'gray', linewidth=lw, linestyle=(3, (3, 1)), solid_capstyle='round') xmin, xmax, ymin, ymax = extent xnum, ynum = gridnum x = np.linspace(xmin, xmax, xnum) y = np.linspace(ymin, ymax, ynum) x, y = np.meshgrid(x, y) z = f(x, y) ax.imshow(z, origin='lower', aspect='auto', cmap=cmap, norm=norm, zorder=0, extent=(xmin, xmax, ymin, ymax)) contours = ax.contour(x, y, z, levels=[0], linewidths=0) for coll in contours.collections: coll.remove() dzdy = np.gradient(z)[0] for coll in contours.collections: for path in coll.get_paths(): saved = [] sign = None for (x0, y0) in path.vertices: saved.append((x0, y0)) x_idx = int(np.floor((x0-xmin) / (xmax-xmin) * (xnum - 1))) y_idx = int(np.floor((y0-ymin) / (ymax-ymin) * (ynum - 1))) if sign is None: sign = np.sign(dzdy[y_idx, x_idx]) if np.sign(dzdy[y_idx, x_idx] * sign) < 0: if sign < 0: plot1(*np.array(saved).T) else: plot2(*np.array(saved).T) sign *= -1 saved = [] else: pass if saved: if sign < 0: plot1(*np.array(saved).T) else: plot2(*np.array(saved).T) if reset_xylim: scale = lambda min, max, ratio=0.1: (min - (max - min) * ratio / 2, max + (max - min) * ratio / 2) ax.set_xlim(*scale(xmin, xmax)) ax.set_ylim(*scale(ymin, ymax)) class EqualizeNormalize(mcolors.Normalize): """ 按分布而非值进行归一化 """ def __init__(self, samples, clip=False): super().__init__(vmin=samples.min(), vmax=samples.max(), clip=clip) hist, bin_edges = np.histogram(samples.flatten(), bins=256, range=(self.vmin, self.vmax), density=True) cdf = hist.cumsum() cdf = (cdf - cdf.min()) / (cdf.max() - cdf.min()) self.bin_edges = bin_edges self.cdf = cdf def __call__(self, value, clip=False): value = np.array(value) return np.ma.masked_array(np.interp(value.flatten(), self.bin_edges[:-1], self.cdf).reshape(value.shape)) def inverse(self, value): value = np.array(value) return np.ma.masked_array(np.interp(value.flatten(), self.cdf, self.bin_edges[:-1]).reshape(value.shape)) def plotOD(ax, source:List[str], destination:List[str], flow:List[float], location:Dict[str, Tuple[float, float]], linetype:Literal['straight', 'parabola', 'rotated_parabola', 'projected_parabola']='straight', N=100, zorder=10, **kwargs): """ 绘制OD流量 """ cmap = mcolors.LinearSegmentedColormap.from_list('cmap', ['#0308F8', '#FD0B1B', '#ffff00'], gamma=5.0) norm = EqualizeNormalize(flow.values) t = np.linspace(0, 1, N) ignored = set(list(source) + list(destination)) - set(location.keys()) if ignored: print(f'\033[33mWarning: {ignored} are not in location\033[0m') for (s, d, f) in zip(source, destination, flow): if s not in location or d not in location: continue p1 = np.array(location[s])[:, np.newaxis] # (2, 1) p2 = np.array(location[d])[:, np.newaxis] # (2, 1) if linetype == 'straight': ax.plot(*(p1 * (1 - t) + p2 * t), lw=0.05+0.1*norm(f), alpha=0.4+0.4*norm(f), color=cmap(norm(f)), zorder=zorder+norm(f), rasterized=kwargs.get('rasterized', False)) elif linetype == 'parabola': y_scale = locals().get('y_scale', np.diff(ax.get_ylim())[0]) xy = p1 * (1-t) + p2 * t + np.array([[0], [1]]) * 4 * t * (1-t) * norm(f) * y_scale * kwargs.get('scale', 0.1) ax.plot(*xy, lw=0.05+0.1*norm(f), alpha=0.4+0.4*norm(f), color=cmap(norm(f)), zorder=zorder+norm(f), rasterized=kwargs.get('rasterized', False)) elif linetype == 'rotated_parabola': height = 0.5 * norm(f) C, S = (p2 - p1)[:, 0] A = np.array([[C, -S], [S, C]]) / 2 if kwargs.get('adjust_up', None) and (C < 0): A = -A if kwargs.get('adjust_down', None) and (C > 0): A = -A xy = A @ np.array([2 * t - 1, height * 4 * t * (1 - t)]) + 0.5 * (p1 + p2) ax.plot(*xy, lw=0.05+0.1*norm(f), alpha=0.4+0.4*norm(f), color=cmap(norm(f)), zorder=zorder+norm(f), rasterized=kwargs.get('rasterized', False)) elif linetype == 'projected_parabola': p0 = locals().get('p0', np.array(kwargs.get('p0', [np.mean(ax.get_xlim()), np.mean(ax.get_ylim())]))[:, np.newaxis]) D = kwargs.get('D', 10) xy = p0 + D * (p1 * (1-t) + p2 * t - p0) / (D - 4*t*(1 - t)*(norm(f) + 1)) ax.plot(*xy, lw=0.05+0.1*norm(f), alpha=0.4+0.4*norm(f), color=cmap(norm(f)), zorder=zorder+norm(f), rasterized=kwargs.get('rasterized', False)) else: raise ValueError(f'Invalid linetype: {linetype}') return ax def clear_svg(path, debug=False): """ matplotlib 生成的 svg 中会使用 2020-02-02 的语法，而 Powerpoint 无法识别 font: 9.8px 'Arial'; 的简写记法，只能识别 font-family: 'Arial'; font-size: 9.8px; 的记法。因此需要进行转换。考虑的属性包括： - font-size - font-family - font-weight - font-style """ raise DeprecationWarning("现在好像不需要 clear 了，直接导入 PPT 即可") from lxml import etree tree = etree.parse(path) root = tree.getroot() for text in root.findall('.//{http://www.w3.org/2000/svg}tspan') + root.findall('.//{http://www.w3.org/2000/svg}text'): style = text.attrib.pop('style', '') font_size = re.search(r'font:[^;]*\s+(\d+\.?\d*px)(?:\s|$)', style) font_family = re.search(r'font:[^;]*\s+\'([^\']*)\'(?:\s|$)', style) font_style = re.search(r'font:[^;]*\s+(italic|oblique)(?:\s|$)', style) font_weight = re.search(r'font:[^;]*\s+(bold|normal|bolder|lighter)(?:\s|$)', style) line_height = re.search(r'line-height:\s+([\d\.]+(px|em|%)?)', style) font_variant = re.search(r'font-variant:\s+([\w-]+)', style) text_anchor = re.search(r'text-anchor:\s+([\w-]+)', style) if font_size: text.set('font-size', font_size.group(1)) if font_family: text.set('font-family', font_family.group(1)) if font_style: text.set('font-style', font_style.group(1)) if font_weight: text.set('font-weight', font_weight.group(1)) if line_height: text.set('line-height', line_height.group(1)) if font_variant: text.set('font-variant', font_variant.group(1)) if text_anchor: text.set('text-anchor', text_anchor.group(1)) if debug: print(f'"{style}" -> "{text.attrib}"') tree.write(path) def load_font(): """ - plt.title("示例图表：数字平方", fontproperties=font, size=15) - plt.xlabel("数字", fontproperties=font, size=12) - plt.ylabel("平方", fontproperties=font, size=12) """ import requests from matplotlib.font_manager import FontProperties url = "https://ghp.ci/https://github.com/notofonts/noto-cjk/blob/main/Sans/SubsetOTF/SC/NotoSansSC-Regular.otf" font_path = "/tmp/SimHei.otf" if not os.path.exists(font_path): response = requests.get(url) if response.status_code == 200: with open(font_path, "wb") as f: f.write(response.content) else: raise Exception("Failed to download the font.") font = FontProperties(fname=font_path) plt.rcParams["font.family"] = "sans-serif" plt.rcParams["font.sans-serif"] = [font_path] # 这里指定.otf文件路径 plt.rcParams["axes.unicode_minus"] = False # 正确显示负号 return font # 计算两个 box 的重叠面积 def _overlapping_area(bbox1, bbox2): x0 = max(bbox1.x0, bbox2.x0) x1 = min(bbox1.x1, bbox2.x1) y0 = max(bbox1.y0, bbox2.y0) y1 = min(bbox1.y1, bbox2.y1) return max(0, x1 - x0) * max(0, y1 - y0) # 计算 point 到 box 的最近距离 def _distance_to_box(point, box): x = max(box.x0, min(point[0], box.x1)) y = max(box.y0, min(point[1], box.y1)) return np.sqrt((point[0] - x) ** 2 + (point[1] - y) ** 2) # 调整文本位置的函数 def adjust_text(texts, ax, step=0.01, max_iterations=100, mode="xy"): raw_pos = np.array([text.get_position() for text in texts], dtype=float) cur_pos = raw_pos.copy() overlap = np.zeros((len(texts), len(texts))) def update(i, utri_only=False): bbox1 = texts[i].get_window_extent(renderer=ax.figure.canvas.get_renderer()) for j, text2 in enumerate(texts): if j == i: continue if utri_only and j <= i: continue bbox2 = text2.get_window_extent(renderer=ax.figure.canvas.get_renderer()) overlap[i, j] = overlap[j, i] = _overlapping_area(bbox1, bbox2) def normalize(v): return v / np.linalg.norm(v).clip(1e-6) # 初始化 for i in range(len(texts)): update(i, utri_only=True) for iteration in range(max_iterations): i, j = random.choice(list(np.stack(np.nonzero(overlap), axis=-1))) # i 对 j 的排斥 F1 = cur_pos[j] - cur_pos[i] # raw_pos[j] 对 j 的吸引 bbox = texts[j].get_window_extent(renderer=ax.figure.canvas.get_renderer()) F2 = ( normalize(raw_pos[j] - cur_pos[j]) * _distance_to_box(raw_pos[j], bbox) * 0.001 ) # F2 = 0.0 # 随机扰动 F3 = np.random.randn(2) # 合力 F = F1 + F2 + F3 if mode == "x": F[1] = 0 if mode == "y": F[0] = 0 # 更新位置 cur_pos[j] += F * step texts[j].set_position(cur_pos[j]) update(j) if (overlap == 0).all(): break def use_chinese_font(fontpath="/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc"): font_prop = FontProperties(fname=fontpath) rcParams["font.family"] = font_prop.get_name() rcParams["axes.unicode_minus"] = False def merge_axes(axes, fig=None): if fig is None: fig = axes[0].figure xmin = min(ax.get_position().bounds[0] for ax in axes) # axes[0, 2] 的左上角坐标 xmax = max(ax.get_position().bounds[0] + ax.get_position().bounds[2] for ax in axes) # axes[1, 3] 的右下角坐标 ymin = min(ax.get_position().bounds[1] for ax in axes) # axes[0, 2] 的左上角坐标 ymax = max(ax.get_position().bounds[1] + ax.get_position().bounds[3] for ax in axes) # axes[1, 3] 的右下角坐标 merged_ax = fig.figure.add_axes([xmin, ymin, xmax - xmin, ymax - ymin]) # 如果 axes[0] 被设置与其他的 ax 共享坐标轴，则需要设置 merged_ax 也共享坐标轴 # if axes[0].get_shared_x_axes() is not None: # merged_ax.get_shared_x_axes().join(merged_ax, *axes) # if axes[0].get_shared_y_axes() is not None: # merged_ax.get_shared_y_axes().join(merged_ax, *axes) for ax in axes: fig.delaxes(ax) return merged_ax