import os import joypy import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns def keep_txt_to_file(code, script_path): with open(script_path, 'w', encoding='utf-8') as f: f.write(code) def scatter_plot(file_path, chart_out_path, out_path, x_scale_font_angle, y_scale_font_angle, x_column_name, y_column_name, group_by_column='category', x_name="x", y_name="y", title="chart", dpi=100, width=10, height=6, title_font_size=12, ): midwest = pd.read_csv(file_path) # 导入文件 plt.figure(figsize=(int(width), int(height)), dpi=int(dpi), facecolor='w', edgecolor='k') categories = np.unique(midwest[group_by_column]) colors = [ plt.cm.Set1(i / float(len(categories) - 1)) for i in range(len(categories)) ] for i, category in enumerate(categories): plt.scatter(x_column_name, y_column_name, data=midwest.loc[midwest.category == category, :], s=20, color=colors[i], label=str(category)) plt.gca().set( xlim=(0.0, 0.1), ylim=(0, 90000), ) # xy轴的刻度 plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) # xy轴的名称 plt.xlabel(x_name, fontdict={'fontsize': 10}) plt.ylabel(y_name, fontdict={'fontsize': 10}) # 标题 plt.title(title, fontsize=int(title_font_size)) # 加上图例 plt.legend(fontsize=10) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Each_regression_line_in_its_own_column(file_path, chart_out_path, out_path, group_by_column, group_by_range, x_column_name, y_column_name, title, title_font_size, x_name, y_name, color): df = pd.read_csv(file_path) group_by_range = [group_by_range.split("-")[0], group_by_range.split("-")[1]] df_select = df.loc[df[group_by_column].isin(group_by_range), :] plt.figure(figsize=(5, 3), dpi=200) gridobj = sns.lmplot(x=x_column_name, y=y_column_name, data=df_select, robust=True, palette=color, col=group_by_column, scatter_kws=dict(s=60, linewidths=.7, edgecolors='black')) # Decorations sns.set(style="whitegrid", font_scale=1.5) gridobj.fig.set_size_inches(10, 6) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 # xy轴的名称 plt.xlabel(x_name, fontdict={'fontsize': 10}) plt.ylabel(y_name, fontdict={'fontsize': 10}) plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Jittering_with_stripplot(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, title_font_size, x_name, y_name, color): df = pd.read_csv(file_path) fig, ax = plt.subplots(figsize=(5, 3), dpi=180) print(fig, ax) sns.stripplot(df[x_column_name], df[y_column_name], jitter=0.25, size=8, ax=ax, linewidth=.5, palette=color) sns.set(style="whitegrid", font_scale=1.1) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.legend(fontsize=10) # xy轴的名称 plt.xlabel(x_name, fontdict={'fontsize': 10}) plt.ylabel(y_name, fontdict={'fontsize': 10}) plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Marginal_Histogram(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, x_name, y_name, chart_bar_x_color='#0078d4', chart_bar_y_color='#098154'): df = pd.read_csv(file_path) # Create Fig and gridspec fig = plt.figure(figsize=(9.4, 4.25), dpi=200) grid = plt.GridSpec(4, 4, hspace=0.5, wspace=0.2) # Define the axes ax_main = fig.add_subplot(grid[:-1, :-1]) ax_right = fig.add_subplot(grid[:-1, -1], xticklabels=[], yticklabels=[]) ax_bottom = fig.add_subplot(grid[-1, 0:-1], xticklabels=[], yticklabels=[]) # Scatterplot on main ax ax_main.scatter(x_column_name, y_column_name, c=df.manufacturer.astype('category').cat.codes, alpha=.9, data=df, cmap="Set1", edgecolors='gray', linewidths=.5) # histogram on the right ax_bottom.hist(df[x_column_name], 40, histtype='stepfilled', orientation='vertical', color=chart_bar_x_color) ax_bottom.invert_yaxis() # histogram in the bottom ax_right.hist(df[y_column_name], 40, histtype='stepfilled', orientation='horizontal', color=chart_bar_y_color) ax_main.set(title=title, xlabel=x_name, ylabel=y_name) for item in ([ax_main.xaxis.label, ax_main.yaxis.label] + ax_main.get_xticklabels() + ax_main.get_yticklabels()): item.set_fontsize(10) xlabels = ax_main.get_xticks().tolist() ax_main.set_xticklabels(xlabels) plt.savefig(chart_out_path) # 保存图片 plt.legend(fontsize=10) plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Correllogram(file_path, chart_out_path, out_path, title, title_font_size, font_size, font_color, weight): df = pd.read_csv(file_path) plt.figure(figsize=(9.4, 4.25), dpi=200) sns.heatmap( df.corr(), xticklabels=df.corr().columns, yticklabels=df.corr().columns, cmap='Set1', center=0, annot=True, annot_kws={ 'size': font_size, 'weight': weight, 'color': font_color }, ) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.legend(fontsize=10) plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Marginal_Boxplot(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name, color): # 边缘箱图（Marginal Boxplot） df = pd.read_csv(file_path) fig = plt.figure(figsize=(9.4, 4.25), dpi=100) grid = plt.GridSpec( 4, 4, hspace=0.5, wspace=0.2 ) # Define the axes ax_main = fig.add_subplot(grid[:-1, :-1]) ax_right = fig.add_subplot(grid[:-1, -1], xticklabels=[], yticklabels=[]) ax_bottom = fig.add_subplot(grid[-1, 0:-1], xticklabels=[], yticklabels=[]) # Scatterplot on main ax ax_main.scatter(x_column_name, y_column_name, c=df.manufacturer.astype('category').cat.codes, alpha=.9, data=df, cmap="Set1", edgecolors='black', linewidths=.5) # Add a graph in each part sns.boxplot(df[y_column_name], ax=ax_right, orient="v", linewidth=1, palette=color) sns.boxplot(df[x_column_name], ax=ax_bottom, orient="h", linewidth=1, palette=color) ax_bottom.set(xlabel='') ax_right.set(ylabel='') ax_main.title.set_fontsize(fontsize=int(title_font_size)) ax_main.set(title=title, xlabel=x_name, ylabel=y_name) for item in ([ax_main.xaxis.label, ax_main.yaxis.label] + ax_main.get_xticklabels() + ax_main.get_yticklabels()): item.set_fontsize(11) plt.savefig(f"{chart_out_path}") # 保存图片 plt.legend(fontsize=10) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) # xy轴的名称 plt.xlabel(x_name, fontdict={'fontsize': 10}) plt.ylabel(y_name, fontdict={'fontsize': 10}) plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Pairwise_Plot(file_path, chart_out_path, out_path, title, title_font_size, features_column, color): df = pd.read_csv(file_path) plt.figure(figsize=(9.4, 4.25), dpi=100) plt.title(title, fontsize=int(title_font_size)) sns.pairplot(df, hue=features_column, palette=color, plot_kws=dict(s=80, edgecolor="white", linewidth=2.5)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Diverging_Bars(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name): df = pd.read_csv(file_path) x = df.loc[:, [x_column_name]] df[x_column_name + "_z"] = (x - x.mean()) / x.std() df['colors'] = ['red' if x < 0 else 'green' for x in df[x_column_name + "_z"]] df.sort_values(x_column_name + "_z", inplace=True) df.reset_index(inplace=True) # Draw plot plt.figure(figsize=(9.4, 4.25), dpi=80) plt.hlines(y=df.index, xmin=0, xmax=df.mpg_z, color=df.colors, alpha=0.8, linewidth=5) # Decorations plt.gca().set(ylabel=y_name, xlabel=x_name) plt.yticks(df.index, df[y_column_name], fontsize=12) plt.xticks(fontsize=12) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.title(title, fontsize=int(title_font_size)) plt.grid(linestyle='--', alpha=0.5) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Diverging_Bars_vertical(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name): df = pd.read_csv(file_path) x = df.loc[:, [y_column_name]] df[y_column_name + 'z'] = (x - x.mean()) / x.std() df['colors'] = ['red' if x < 0 else 'green' for x in df[y_column_name + 'z']] df.sort_values(y_column_name + 'z', inplace=True) df.reset_index(inplace=True) # Draw plot plt.figure(figsize=(10, 6), dpi=80) plt.vlines(x=df.index, ymin=0, ymax=df[y_column_name + 'z'], color=df.colors, alpha=0.8, linewidth=5) plt.gca().set(ylabel=y_name, xlabel=x_name) for y, x, tex in zip(df[y_column_name + 'z'], df.index, df[y_column_name + 'z']): plt.text(x, y + 0.2, round(tex, 1), horizontalalignment='center', fontdict={ 'color': 'black' if x < 0 else 'black', 'size': 8 }) # Decorations plt.xticks(df.index, df[x_column_name], fontsize=12, rotation=90) plt.yticks(fontsize=12) plt.title(title, fontdict={'size': int(title_font_size)}) plt.grid(linestyle='--', alpha=0.5) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Ordered_Bar_Chart(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, title_font_size, y_scale_font_angle, x_name, y_name, color): df_raw = pd.read_csv(file_path) df = df_raw[[x_column_name, y_column_name]].groupby(y_column_name).apply(lambda x: x.mean()) df.sort_values(x_column_name, inplace=True) df.reset_index(inplace=True) import matplotlib.patches as patches plt.gca().set(ylabel=y_name, xlabel=x_name) fig, ax = plt.subplots(figsize=(9.4, 4.25), facecolor='white', dpi=80) ax.vlines(x=df.index, ymin=0, ymax=df.cty, color=color, alpha=0.7, linewidth=20) plt.yticks(rotation=y_scale_font_angle, fontsize=10) # Annotate Text for i, cty in enumerate(df.cty): ax.text(i, cty + 0.5, round(cty, 1), horizontalalignment='center') # Title, Label, Ticks and Ylim plt.xticks(df.index, df.manufacturer.str.upper(), rotation=60, horizontalalignment='right', fontsize=10) plt.yticks(fontsize=12) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.ylim = (0, 30) # 添加底纹 p1 = patches.Rectangle((.57, -0.005), width=.33, height=.13, alpha=.1, facecolor='green', transform=fig.transFigure) p2 = patches.Rectangle((.124, -0.005), width=.446, height=.13, alpha=.1, facecolor='red', transform=fig.transFigure) fig.add_artist(p1) fig.add_artist(p2) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 输出一个展示的png plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Lollipop_Chart(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name, color): df_raw = pd.read_csv(file_path) df = df_raw[[x_column_name, y_column_name]].groupby(y_column_name).apply(lambda x: x.mean()) df.sort_values(x_column_name, inplace=True) df.reset_index(inplace=True) # Draw plot fig, ax = plt.subplots(figsize=(9.4, 4.25), dpi=200) ax.vlines(x=df.index, ymin=0, ymax=df.cty, color=color, alpha=0.7, linewidth=4) ax.scatter(x=df.index, y=df[x_column_name], s=85, color=color, alpha=0.7) # Title, Label, Ticks and Ylim ax.set_xticks(df.index) ax.set_xticklabels(df.manufacturer.str.upper(), rotation=60, fontdict={ 'horizontalalignment': 'right', 'size': 11 }) ax.set_ylim(0, 30) plt.yticks(fontsize=12) # Annotate for row in df.itertuples(): ax.text(row.Index, row.cty + .5, s=round(row.cty, 2), horizontalalignment='center', verticalalignment='bottom', fontsize=12) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Dot_Plot(file_path, chart_out_path, out_path, x_column_name, y_column_name, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name, line_color, point_color): df_raw = pd.read_csv(file_path) df = df_raw[[x_column_name, y_column_name]].groupby(y_column_name).apply(lambda x: x.mean()) df.sort_values('cty', inplace=True) df.reset_index(inplace=True) # Draw plot fig, ax = plt.subplots(figsize=(10, 6), dpi=80) ax.hlines(y=df.index, xmin=11, xmax=26, color=line_color, alpha=0.7, linewidth=1, linestyles='dashdot') ax.scatter(y=df.index, x=df.cty, s=75, color=point_color, alpha=0.7) ax.set_yticks(df.index) ax.set_yticklabels(df.manufacturer.str.title(), fontdict={ 'horizontalalignment': 'right', 'fontsize': 12, }) ax.set_xlim(10, 27) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.xlabel(x_name, fontsize=12) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Slope_Chart(file_path, chart_out_path, out_path, column_name_1, column_name_2, column_name_3, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name): import matplotlib.lines as mlines df = pd.read_csv(file_path) def newline(p1, p2): ax = plt.gca() l = mlines.Line2D([p1[0], p2[0]], [p1[1], p2[1]], color='red' if p1[1] - p2[1] > 0 else 'green', marker='o', markersize=6) ax.add_line(l) return l fig, ax = plt.subplots(1, 1, figsize=(9.4, 4.25), dpi=80) # Vertical Lines ax.vlines(x=1, ymin=500, ymax=13000, color='black', alpha=0.7, linewidth=1, linestyles='dotted') ax.vlines(x=3, ymin=500, ymax=13000, color='black', alpha=0.7, linewidth=1, linestyles='dotted') ax.scatter(y=df[column_name_1], x=np.repeat(1, df.shape[0]), s=10, color='black', alpha=0.7) ax.scatter(y=df[column_name_2], x=np.repeat(3, df.shape[0]), s=10, color='black', alpha=0.7) # Line Segmentsand Annotation for p1, p2, c in zip(df[column_name_1], df[column_name_2], df[column_name_3]): newline([1, p1], [3, p2]) ax.text(1 - 0.05, p1, c + ', ' + str(round(p1)), horizontalalignment='right', verticalalignment='center', fontdict={'size': 14}) ax.text(3 + 0.05, p2, c + ', ' + str(round(p2)), horizontalalignment='left', verticalalignment='center', fontdict={'size': 14}) # 'Before' and 'After' Annotations ax.text(1 - 0.05, 13000, 'BEFORE', horizontalalignment='right', verticalalignment='center', fontdict={ 'size': 15, 'weight': 700 }) ax.text(3 + 0.05, 13000, 'AFTER', horizontalalignment='left', verticalalignment='center', fontdict={ 'size': 15, 'weight': 700 }) # Decoration ax.set(xlim=(0, 4), ylim=(0, 14000)) ax.set_xticks([1, 3]) ax.set_xticklabels([column_name_1, column_name_2], fontdict={'size': 15, 'weight': 700}) plt.yticks(np.arange(500, 13000, 2000), rotation=y_scale_font_angle, fontsize=10) # Lighten borders plt.gca().spines["top"].set_alpha(.0) plt.gca().spines["bottom"].set_alpha(.0) plt.gca().spines["right"].set_alpha(.0) plt.gca().spines["left"].set_alpha(.0) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Dumbbell_Plot(file_path, chart_out_path, out_path, column_name_1, column_name_2, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name): import matplotlib.lines as mlines # Import Data df = pd.read_csv(file_path) df.sort_values(column_name_1, inplace=True) df.reset_index(inplace=True) # Func to draw line segment def newline(p1, p2): ax = plt.gca() l = mlines.Line2D([p1[0], p2[0]], [p1[1], p2[1]], color='#d5695d') ax.add_line(l) return l # Figure and Axes fig, ax = plt.subplots(1, 1, figsize=(9.4, 4.25), facecolor='#f8f2e4', dpi=80) # Vertical Lines ax.vlines(x=.05, ymin=0, ymax=26, color='black', alpha=1, linewidth=1, linestyles='dotted') ax.vlines(x=.10, ymin=0, ymax=26, color='black', alpha=1, linewidth=1, linestyles='dotted') ax.vlines(x=.15, ymin=0, ymax=26, color='black', alpha=1, linewidth=1, linestyles='dotted') ax.vlines(x=.20, ymin=0, ymax=26, color='black', alpha=1, linewidth=1, linestyles='dotted') # Points ax.scatter(y=df['index'], x=df[column_name_1], s=50, color='#dc2624') ax.scatter(y=df['index'], x=df[column_name_2], s=50, color='#e87a59') # Line Segments for i, p1, p2 in zip(df['index'], df[column_name_1], df[column_name_2]): newline([p1, i], [p2, i]) # Decoration ax.set_facecolor('#f8f2e4') ax.set(xlim=(0, .25), ylim=(-1, 27)) plt.yticks(fontsize=15) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") def Stacked_Histogram_for_Continuous_Variable(file_path, chart_out_path, out_path, x_column_name, group_by_column, title, title_font_size, x_scale_font_angle, y_scale_font_angle, x_name, y_name): df = pd.read_csv(file_path) # Prepare data x_var = x_column_name groupby_var = group_by_column df_agg = df.loc[:, [x_var, groupby_var]].groupby(groupby_var) vals = [df[x_var].values.tolist() for i, df in df_agg] # Draw plt.figure(figsize=(9.4, 4.25), dpi=180) colors = [plt.cm.Set1(i / float(len(vals) - 1)) for i in range(len(vals))] n, bins, patches = plt.hist(vals, 30, stacked=True, density=False, color=colors[:len(vals)]) # Decoration plt.legend({ group: col for group, col in zip( np.unique(df[groupby_var]).tolist(), colors[:len(vals)]) }) plt.xlabel(x_var) # plt.ylim(0, 25) plt.xticks(ticks=bins[::3], labels=[round(b, 1) for b in bins[::3]]) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.title(title, fontsize=int(title_font_size)) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 23、密度图(Density_Plot) # 测试文件 mpg.csv # 基础参数 图片的长/宽/分辨率/字号/x轴字号/标题的字号、xy轴限制/颜色 def Density_Plot(file_path, chart_out_path, x_scale_font_angle, y_scale_font_angle, y_name, x_name, y_font_size, x_font_size, out_path, scale_font_size, title, title_font_size, column_name): df = pd.read_csv(file_path) # Draw Plot plt.figure(figsize=(9.4, 4.25), dpi=180) sns.kdeplot(df.loc[df[column_name] == 4, column_name], shade=True, color="#01a2d9", label=f"{column_name}=4", alpha=.7) sns.kdeplot(df.loc[df[column_name] == 5, column_name], shade=True, color="#dc2624", label=f"{column_name}=5", alpha=.7) sns.kdeplot(df.loc[df[column_name] == 6, column_name], shade=True, color="#C89F91", label=f"{column_name}=6", alpha=.7) sns.kdeplot(df.loc[df[column_name] == 8, column_name], shade=True, color="#649E7D", label=f"{column_name}=8", alpha=.7) # Decoration sns.set(style="whitegrid", font_scale=scale_font_size) plt.title(title, fontsize=title_font_size) plt.legend() plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=y_font_size) plt.ylabel(x_name, fontsize=x_font_size) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 25、山峰叠峦图(Joy_Plot) # 测试文件 mpg.csv # 基础参数 图片的长/宽/分辨率/字号/x轴字号/标题的字号、xy轴限制/颜色 def Joy_Plot(file_path, chart_out_path, out_path, title, title_font_size, x_scale_font_angle, y_scale_font_angle, y_name, x_name, column_name_1, column_name_2, group_by_column, y_scale_limit): mpg = pd.read_csv(file_path) # Draw Plot plt.figure(figsize=(9.4, 4.25), dpi=180) fig, axes = joypy.joyplot(mpg, column=[column_name_1, column_name_2], by=group_by_column, ylim=y_scale_limit, colormap=plt.cm.Set1, figsize=(10, 6)) # Decoration plt.title(title, fontsize=title_font_size) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 27、箱图（boxplot） # 测试文件 mpg.csv # 基础参数 图片的长/宽/分辨率/字号/x轴字号/标题的字号、xy轴限制/颜色 def boxplot(file_path, chart_out_path, out_path, scale_font_size, title, title_font_size, font_size, font_color, y_scale_min, y_scale_max, x_column_name, y_column_name, x_scale_font_angle, y_scale_font_angle, y_name, x_name, color): df = pd.read_csv(file_path) # Draw Plot plt.figure(figsize=(9.4, 4.25), dpi=180) sns.boxplot( x=x_column_name, y=y_column_name, data=df, notch=False, palette=color, ) # Add N Obs inside boxplot (optional) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) def add_n_obs(df, group_col, y): medians_dict = { grp[0]: grp[1][y].median() for grp in df.groupby(group_col) } xticklabels = [x.get_text() for x in plt.gca().get_xticklabels()] n_obs = df.groupby(group_col)[y].size().values for (x, xticklabel), n_ob in zip(enumerate(xticklabels), n_obs): plt.text(x, medians_dict[xticklabel] * 1.01, "#obs : " + str(n_ob), horizontalalignment='center', fontdict={'size': font_size}, color=font_color) add_n_obs(df, group_col=x_column_name, y=y_column_name) # Decoration sns.set(style="whitegrid", font_scale=scale_font_size) plt.title(title, fontsize=title_font_size) plt.ylim(y_scale_min, y_scale_max) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 28、箱图结合点图（Dot_Box_Plot） # 测试文件 mpg.csv def Dot_Box_Plot(file_path, chart_out_path, out_path, title, title_font_size, point_size, line_color, x_scale_font_angle, y_scale_font_angle, y_name, x_name, x_column_name, y_column_name, group_by_column, legend_name, color): df = pd.read_csv(file_path) plt.figure(figsize=(9.4, 4.25), dpi=180) sns.boxplot( x=x_column_name, y=y_column_name, data=df, hue=legend_name, palette=color, ) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.legend(loc=9) sns.stripplot(x=x_column_name, y=y_column_name, data=df, color='#dc2624', size=point_size, jitter=1) for i in range(len(df[group_by_column].unique()) - 1): plt.vlines(i + .5, 10, 45, linestyles='solid', colors=line_color, alpha=0.2) # Decoration plt.title(title, fontsize=title_font_size) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 28、箱图结合点图（Dot_Box_Plot） # 测试文件 mpg.csv def Violin_Plot(file_path, chart_out_path, out_path, title, title_font_size, x_column_name, y_column_name, x_scale_font_angle, y_scale_font_angle, y_name, x_name, color): df = pd.read_csv(file_path) # Draw Plot plt.figure(figsize=(9.4, 4.25), dpi=180) sns.violinplot(x=x_column_name, y=y_column_name, data=df, scale='width', palette=color, inner='quartile') # Decoration plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.title(title, fontsize=title_font_size) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 30、金字塔图(Population_Pyramid) # 测试文件 email_campaign_funnel.csv def Population_Pyramid(file_path, chart_out_path, out_path, title, title_font_size, x_name, y_name, group_by_column, x_scale_font_angle, y_scale_font_angle, y_column_name, x_column_name): df = pd.read_csv(file_path) # Draw Plot plt.figure(figsize=(9.4, 4.25), dpi=180) group_col = group_by_column order_of_bars = df.Stage.unique()[::-1] colors = [ plt.cm.Set1(i / float(len(df[group_col].unique()) - 1)) for i in range(len(df[group_col].unique())) ] for c, group in zip(colors, df[group_col].unique()): sns.barplot(x=x_column_name, y=y_column_name, data=df.loc[df[group_col] == group, :], order=order_of_bars, color=c, label=group) # Decorations plt.title(title, fontsize=title_font_size) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.legend() plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 32、华夫饼图（Waffle_Chart） # 测试文件 mpg.csv def Waffle_Chart(file_path, chart_out_path, out_path, rows_number, group_by_column, x_scale_font_angle, y_scale_font_angle, y_name, x_name, title_font_size, title): df_raw = pd.read_csv(file_path) from pywaffle import Waffle # Prepare Data df = df_raw.groupby(group_by_column).size().reset_index(name='counts') n_categories = df.shape[0] colors = [plt.cm.Set1(i / float(n_categories)) for i in range(n_categories)] # Draw Plot and Decorate plt.figure(FigureClass=Waffle, plots={ '111': { 'values': df['counts'], 'labels': [ "{0} ({1})".format(n[0], n[1]) for n in df[[group_by_column, 'counts']].itertuples() ], 'legend': { 'loc': 'upper left', 'bbox_to_anchor': (1.05, 1), 'fontsize': 12 }, }, }, rows=rows_number, colors=colors, dpi=180, figsize=(9.4, 4.25)) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.title(title, fontsize=title_font_size) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 33、饼图（Pie_Chart） # 测试文件 mpg.csv def Pie_Chart(file_path, chart_out_path, out_path, y_name, title, group_by_column, title_font_size, y_scale_font_angle): df_raw = pd.read_csv(file_path) plt.figure(figsize=(9.4, 4.25), dpi=180) # Prepare Data df = df_raw.groupby(group_by_column).size() # Make the plot with pandas df.plot(kind='pie', subplots=True) plt.title(title, fontsize=title_font_size) plt.ylabel(y_name) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 34、树状图（Treemap） # 测试文件 mpg.csv def Treemap(file_path, chart_out_path, out_path, title, group_by_column, title_font_size): import squarify df_raw = pd.read_csv(file_path) # Prepare Data df = df_raw.groupby(group_by_column).size().reset_index(name='counts') labels = df.apply(lambda x: str(x[0]) + "\n (" + str(x[1]) + ")", axis=1) sizes = df['counts'].values.tolist() colors = [plt.cm.Set2(i / float(len(labels))) for i in range(len(labels))] # Draw Plot plt.figure(figsize=(9.4, 4.25), dpi=180) squarify.plot(sizes=sizes, label=labels, color=colors, alpha=.8) # Decorate plt.title(title, fontsize=title_font_size) plt.axis('off') plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 35、柱状图（Bar_Chart # 测试文件 mpg.csv def Bar_Chart(file_path, chart_out_path, out_path, title, title_font_size, font_size, y_scale_min, y_scale_max, width, group_by_column, x_scale_font_angle, y_scale_font_angle, y_name, x_name): import random df_raw = pd.read_csv(file_path) df = df_raw.groupby(group_by_column).size().reset_index(name='counts') n = df[group_by_column].unique().__len__() + 1 all_colors = list(plt.cm.colors.cnames.keys()) random.seed(100) c = random.choices(all_colors, k=n) # Plot Bars plt.figure(figsize=(9.4, 4.25), dpi=180) plt.bar(df[group_by_column], df['counts'], color=c, width=width) for i, val in enumerate(df['counts'].values): plt.text(i, val, float(val), horizontalalignment='center', verticalalignment='bottom', fontdict={ 'fontweight': 500, 'size': font_size }) # Decoration plt.gca().set_xticklabels(df[group_by_column], rotation=60, horizontalalignment='right') plt.title(title, fontsize=title_font_size) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.ylim(y_scale_min, y_scale_max) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 36、时间序列图（Time_Series_Plot） # 测试文件 AirPassengers.csv def Time_Series_Plot(file_path, chart_out_path, out_path, polt_color, title, title_font_size, x_column, y_column, x_font_size, y_font_size, y_scale_min, y_scale_max, x_scale_font_angle, y_scale_font_angle, y_name, x_name): df = pd.read_csv(file_path) # Draw Plot plt.figure(figsize=(9.4, 4.25), dpi=180) plt.plot(df[x_column], df[y_column], color=polt_color) # plt.plot(df['date'], df['value'], color='#365770') # print(file_path) # Decoration plt.ylim(y_scale_min, y_scale_max) xtick_location = df.index.tolist()[::12] xtick_labels = [x[-4:] for x in df.date.tolist()[::12]] plt.xticks(ticks=xtick_location, labels=xtick_labels, rotation=0, fontsize=x_font_size, horizontalalignment='center', alpha=.7) plt.yticks(fontsize=y_font_size, alpha=.7) plt.title(title, fontsize=title_font_size) plt.grid(axis='both', alpha=.3) plt.show() plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) # Remove borders plt.gca().spines["top"].set_alpha(0.0) plt.gca().spines["bottom"].set_alpha(0.3) plt.gca().spines["right"].set_alpha(0.0) plt.gca().spines["left"].set_alpha(0.3) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 41、多重时间序列图（Multiple_Time_Series）!!! # 测试文件 mortality.csv def Multiple_Time_Series(file_path, chart_out_path, out_path, font_size, title, title_font_size, x_font_size, y_font_size, x_scale_min, x_scale_max, x_scale_font_angle, y_scale_font_angle, y_name, x_name): df = pd.read_csv(file_path) y_LL = 100 y_UL = int(df.iloc[:, 1:].max().max() * 1.1) y_interval = 400 mycolors = ['tab:red', 'tab:blue', 'tab:green', 'tab:orange'] fig, ax = plt.subplots(1, 1, figsize=(9.4, 4.25), dpi=180) columns = df.columns[1:] for i, column in enumerate(columns): plt.plot(df.date.values, df[column].values, lw=1.5, color=mycolors[i]) plt.text(df.shape[0] + 1, df[column].values[-1], column, fontsize=font_size, color=mycolors[i]) for y in range(y_LL, y_UL, y_interval): plt.hlines(y, xmin=0, xmax=71, colors='black', alpha=0.3, linestyles="--", lw=0.5) # Decorations plt.tick_params(axis="both", which="both", bottom=False, top=False, labelbottom=True, left=False, right=False, labelleft=True) # Lighten borders plt.gca().spines["top"].set_alpha(.3) plt.gca().spines["bottom"].set_alpha(.3) plt.gca().spines["right"].set_alpha(.3) plt.gca().spines["left"].set_alpha(.3) plt.title(title, fontsize=title_font_size) plt.yticks(range(y_LL, y_UL, y_interval), [str(y) for y in range(y_LL, y_UL, y_interval)], fontsize=y_font_size) plt.xticks(range(0, df.shape[0], 12), df.date.values[::12], horizontalalignment='left', rotation=45, fontsize=x_font_size) plt.ylim(y_LL, y_UL) plt.xlim(x_scale_min, x_scale_max) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 42、双坐标系时间序列图（Plotting_with_different_scales_using_secondary_Y_axis） # 测试文件 economics.csv def Plotting_with_different_scales_using_secondary_Y_axis(file_path, chart_out_path, out_path, x_name, x_font_size, y_name_1, y_font_size_1, y_font_color_1, y_name_2, y_font_size_2, y_font_color_2, title, title_font_size, x_column, y_column_1, y_column_2, x_scale_font_angle, y_scale_font_angle): df = pd.read_csv(file_path) x = df[x_column] y1 = df[y_column_1] y2 = df[y_column_2] # Plot Line1 (Left Y Axis) fig, ax1 = plt.subplots(1, 1, figsize=(9.4, 4.25), dpi=180) ax1.plot(x, y1, color='tab:red') # Plot Line2 (Right Y Axis) ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis ax2.plot(x, y2, color='tab:blue') # Decorations # ax1 (left Y axis) ax1.set_xlabel(x_name, fontsize=x_font_size) ax1.tick_params(axis='x', rotation=70, labelsize=12) ax1.set_ylabel(y_name_1, color=y_font_color_1, fontsize=y_font_size_1) ax1.tick_params(axis='y', rotation=0, labelcolor='#dc2624') ax1.grid(alpha=.4) # ax2 (right Y axis) ax2.set_ylabel(y_name_2, color=y_font_color_2, fontsize=y_font_size_2) ax2.tick_params(axis='y', labelcolor='#01a2d9') ax2.set_xticks(np.arange(0, len(x), 60)) ax2.set_xticklabels(x[::60], rotation=90, fontdict={'fontsize': 10}) ax2.set_title( title, fontsize=title_font_size) fig.tight_layout() plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name_1, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 44、堆积面积图（Stacked_Area_Chart） # 测试文件 nightvisitors.csv def Stacked_Area_Chart(file_path, chart_out_path, out_path, y_scale_min, y_scale_max, title, title_font_size, data_column, x_scale_font_angle, y_scale_font_angle, y_name, x_name): df = pd.read_csv(file_path) # Decide Colors mycolors = ['#dc2624', '#2b4750', '#45a0a2', '#e87a59', '#7dcaa9', '#649E7D', '#dc8018', '#C89F91'] # Draw Plot and Annotate fig, ax = plt.subplots(1, 1, figsize=(9.4, 4.25), dpi=180) columns = df.columns[1:] labs = columns.values.tolist() # Prepare data x = df[data_column].values.tolist() y0 = df[columns[0]].values.tolist() y1 = df[columns[1]].values.tolist() y2 = df[columns[2]].values.tolist() y3 = df[columns[3]].values.tolist() y4 = df[columns[4]].values.tolist() y5 = df[columns[5]].values.tolist() y6 = df[columns[6]].values.tolist() y7 = df[columns[7]].values.tolist() y = np.vstack([y0, y2, y4, y6, y7, y5, y1, y3]) # Plot for each column labs = columns.values.tolist() ax = plt.gca() ax.stackplot(x, y, labels=labs, colors=mycolors, alpha=0.8) ax.tick_params(axis='x', rotation=45, labelsize=12) # Decorations ax.set_title(title, fontsize=title_font_size) ax.set(ylim=[y_scale_min, y_scale_max]) ax.legend(fontsize=10, ncol=4) plt.xticks(x[::5], fontsize=10, horizontalalignment='center') plt.yticks(np.arange(10000, 100000, 20000)) plt.xlim(x[0], x[-1]) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) # Lighten borders plt.gca().spines["top"].set_alpha(0) plt.gca().spines["bottom"].set_alpha(.3) plt.gca().spines["right"].set_alpha(0) plt.gca().spines["left"].set_alpha(.3) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 45、非堆积面积图（Area_Chart_UnStacked） # 测试文件 economics.csv def Area_Chart_UnStacked(file_path, chart_out_path, out_path, y_scale_min, y_scale_max, title, title_font_size, x_column, y_column_1, y_column_2, x_scale_font_angle, y_scale_font_angle, y_name, x_name): df = pd.read_csv(file_path) # Prepare Data x = df[x_column].values.tolist() y1 = df[y_column_1].values.tolist() y2 = df[y_column_2].values.tolist() columns = [y_column_1, y_column_2] # Draw Plot fig, ax = plt.subplots(1, 1, figsize=(9.4, 4.25), dpi=180) ax.fill_between(x, y1=y1, y2=0, label=columns[1], alpha=0.5, color='#dc2624', linewidth=2) ax.fill_between(x, y1=y2, y2=0, label=columns[0], alpha=0.5, color='#649E7D', linewidth=2) # Decorations ax.set_title(title, fontsize=title_font_size) ax.set(ylim=[y_scale_min, y_scale_max]) ax.legend(loc='best', fontsize=12) plt.xticks(x[::50], fontsize=10, horizontalalignment='center') plt.yticks(np.arange(2.5, 30.0, 2.5)) plt.xlim(-10, x[-1]) plt.tick_params(axis='x', rotation=45, labelsize=12) # Draw Tick lines for y in np.arange(2.5, 30.0, 2.5): plt.hlines(y, xmin=0, xmax=len(x), colors='black', alpha=0.3, linestyles="--", lw=0.5) # Lighten borders plt.gca().spines["top"].set_alpha(0) plt.gca().spines["bottom"].set_alpha(.3) plt.gca().spines["right"].set_alpha(0) plt.gca().spines["left"].set_alpha(.3) plt.xticks(rotation=x_scale_font_angle, fontsize=10) plt.yticks(rotation=y_scale_font_angle, fontsize=10) plt.ylabel(y_name, fontsize=12) plt.ylabel(x_name, fontsize=12) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 48、聚类树形图（Dendrogram） !!! # 测试文件 USArrests.csv # def Dendrogram(file_path, chart_out_path, out_path, x_font_size, y_font_size, title, title_font_size): import scipy.cluster.hierarchy as shc df = pd.read_csv(file_path) # Plot plt.figure(figsize=(9.4, 4.25), dpi=180) plt.title(title, fontsize=title_font_size) dend = shc.dendrogram(shc.linkage(df[['Murder', 'Assault', 'UrbanPop', 'Rape']], method='ward'), labels=df.State.values, color_threshold=200) plt.xticks(fontsize=x_font_size) plt.yticks(fontsize=y_font_size) plt.savefig(f"{chart_out_path}") # 保存图片 plt.savefig(f"{out_path}.png") plt.savefig(f"{out_path}.svg") plt.savefig(f"{out_path}.pdf") # 冯洋 # 基础参数 file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Composition_Bar.csv def Composition_Bar(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): code = f""" datas <- read.csv("{file_path}") freqtable <- table(datas[,1]) df <- as.data.frame.table(freqtable) library(ggplot2) theme_set(theme_classic()) x <- df[,1] y <- df[,2] # Plot g <- ggplot(df, aes(x, y)) gg <- g + geom_bar(stat="identity", width = 0.5, fill="tomato2") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") def Composition_BarOfColorsDataByGroup(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") library(ggplot2) theme_set(theme_classic()) x <- datas[,1] y <- datas[,2] # Plot g <- ggplot(datas, aes(x)) gg <- g + geom_bar(aes(fill=y), width = 0.5) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position # 实例文件 Composition_Pie.csv def Composition_Pie(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") library(ggplot2) theme_set(theme_classic()) # Source: Frequency table df <- as.data.frame(table(datas)) colnames(df) <- c("class", "freq") pie <- ggplot(df, aes(x = "", y=freq, fill = factor(class))) + geom_bar(width = 1, stat = "identity") + theme(axis.line = element_blank(), plot.title = element_text(hjust=0.5)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- pie + coord_polar(theta = "y", start=0) gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position # 实例文件 Composition_Pie.csv def Composition_Waffles(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") library("ggplot2") var <- datas[,1] # the categorical data nrows <- 10 df <- expand.grid(y = 1:nrows, x = 1:nrows) categ_table <- round(table(var) * ((nrows*nrows)/(length(var)))) df$category <- factor(rep(names(categ_table), categ_table)) ## Plot gg <- ggplot(df, aes(x = x, y = y, fill = category)) + geom_tile(color = "black", size = 0.5) + scale_x_continuous(expand = c(0, 0)) + scale_y_continuous(expand = c(0, 0), trans = 'reverse') + scale_fill_brewer(palette = "{color}") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, model2, model3, model4, model5 # 实例文件 Correlation_Box.csv def Correlation_Box(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, model1, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, model2, model3, model4, model5): code_1 = """ggMarginal(gg, type = "histogram", fill="transparent")""" code_2 = """ggMarginal(gg, type = "density", fill="transparent")""" code_3 = """ggMarginal(gg, type = "boxplot", fill="transparent")""" code_4 = """ggMarginal(gg, type = "violin", fill="transparent")""" code_5 = """ggMarginal(gg, type = "densigram", fill="transparent")""" code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] # load package and data library(ggplot2) library(ggExtra) # Scatterplot theme_set(theme_bw()) # pre-set the bw theme. gg <- ggplot(datas, aes(x, y)) + geom_count(show.legend={legend}) + geom_smooth(method="lm", se=F) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) if({model1}) {code_1} if({model2}) {code_2} if({model3}) {code_3} if({model4}) {code_4} if({model5}) {code_5} dev.off() png("{out_path}.png") if({model1}) {code_1} if({model2}) {code_2} if({model3}) {code_3} if({model4}) {code_4} if({model5}) {code_5} dev.off() pdf("{out_path}.pdf") if({model1}) {code_1} if({model2}) {code_2} if({model3}) {code_3} if({model4}) {code_4} if({model5}) {code_5} dev.off() svg("{out_path}.svg") if({model1}) {code_1} if({model2}) {code_2} if({model3}) {code_3} if({model4}) {code_4} if({model5}) {code_5} dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Correlation_Bubble.csv def Correlation_Bubble(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, size_legend_name, legend_name, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] z <- datas[,3] w <- datas[,4] library(ggplot2) # Scatterplot theme_set(theme_bw()) # pre-set the bw theme. g <- ggplot(datas, aes(y, z)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", col="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) gg <- g + geom_jitter(aes(col=x, size=w)) + geom_smooth(aes(col=x), method="lm", se=F) + labs(size="{size_legend_name}") png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Correlation_Correlation.csv def Correlation_Correlation(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): code = f""" datas <- read.csv("{file_path}") library(ggplot2) library(ggcorrplot) # Correlation matrix corr <- round(cor(datas), 1) # Plot gg <- ggcorrplot(corr, hc.order = TRUE, type = "lower", lab = TRUE, lab_size = 3, method="circle", colors = c("tomato2", "white", "springgreen3"), title="{title}", ggtheme=theme_bw) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Correlation_Count.csv def Correlation_Count(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] # load package and data library(ggplot2) # Scatterplot theme_set(theme_bw()) # pre-set the bw theme. gg <- ggplot(datas, aes(x, y)) + geom_count(col="tomato3", show.legend={legend}) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Correlation_Jitter.csv def Correlation_Jitter(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, legend_name, legend_position, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] # load package and data library(ggplot2) # Scatterplot theme_set(theme_bw()) # pre-set the bw theme. g <- ggplot(datas, aes(x, y, fill=x)) gg <- g + geom_jitter(width = .5, size=1) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Correlation_Scatter.csv def Correlation_Scatter(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, size_legend_name, legend_name, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] z <- datas[,3] w <- datas[,4] library(ggplot2) options(scipen=999) library(ggplot2) theme_set(theme_bw()) # Scatterplot gg <- ggplot(datas, aes(x=y, y=z)) + geom_point(aes(col=x, size=w)) + geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", col="{legend_name}", size="{size_legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Deviation_Area.csv def Deviation_Area(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) library(lubridate) # Compute % Returns datas$returns_perc <- c(0, diff(y)/y[-length(y)]) x <- as.Date(x) # Create break points and labels for axis ticks brks <- x[seq(1, length(x), 12)] lbls <- lubridate::year(x[seq(1, length(x), 12)]) # Plot gg <- ggplot(datas, aes(x, returns_perc)) + geom_area() + scale_x_date(breaks=brks, labels=lbls) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Deviation_Bar.csv def Deviation_Bar(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, type_1, type_2, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}", row.name = 1) y <- datas[,1] library(ggplot2) theme_set(theme_bw()) # Data Prep x <- rownames(datas) z <- round((y - mean(y))/sd(y), 2) w <- ifelse(z < 0, "{type_2}", "{type_1}") datas <- datas[order(z), ] # sort x <- factor(x,levels = x) #Diverging Barcharts gg <- ggplot(datas, aes(x, z, label=z)) + geom_bar(stat='identity', aes(fill=w), width=.5) + scale_fill_manual( labels = c("{type_1}", "{type_2}"), values = c("{type_1}"="#00ba38", "{type_2}"="#f8766d")) + coord_flip() + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Deviation_Dots.csv def Deviation_Dots(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, type_1, type_2, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] z <- datas[,3] library(ggplot2) theme_set(theme_bw()) # Plot gg <- ggplot(datas, aes(x, y, label=y)) + geom_point(stat='identity', aes(col=z), size=6) + scale_color_manual( labels = c("{type_1}", "{type_2}"), values = c("{type_1}"="#00ba38", "{type_2}"="#f8766d")) + geom_text(color="white", size=2) + ylim(-2.5, 2.5) + coord_flip() + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Deviation_Lollipop.csv def Deviation_Lollipop(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_bw()) gg <- ggplot(datas, aes(x, y, label=y)) + geom_point(stat='identity', fill="black", size=6) + geom_segment(aes(y = 0, x = x, yend = y, xend = x), color = "black") + geom_text(color="white", size=2) + ylim(-2.5, 2.5) + coord_flip() + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}), axis.title.x=element_text(size={y_font_size}, color="{y_font_color}"), axis.title.y=element_text(size={x_font_size}, color="{x_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color, point_color # 实例文件 Distribution_BoxWithDots.csv def Distribution_BoxWithDots(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color, point_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_bw()) # plot g <- ggplot(datas, aes(x, y, fill=x)) gg <- g + geom_boxplot(color="{line_color}") + geom_dotplot(binaxis='y', stackdir='center', dotsize = .5, fill="{point_color}", binwidth=0.5) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, line_color # 实例文件 Distribution_Box_1.csv def Distribution_Box_1(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, line_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_classic()) g <- ggplot(datas, aes(x, y)) gg <- g + geom_boxplot(varwidth=T, fill="plum", color="{line_color}") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color # 实例文件 Distribution_Box_2.csv def Distribution_Box_2(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] z <- datas[,3] library(ggthemes) library(ggplot2) g <- ggplot(datas, aes(x, y)) gg <- g + geom_boxplot(aes(fill=factor(z)), color="{line_color}") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color # 实例文件 Distribution_DensityFunction.csv def Distribution_DensityFunction(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_classic()) g <- ggplot(datas, aes(x)) gg <- g + geom_density(aes(fill=factor(y)), alpha=0.8, color="{line_color}") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, model # 实例文件 Distribution_Histogram.csv def Distribution_Histogram(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, model, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_classic()) # Histogram on a Continuous (Numeric) Variable g <- ggplot(mpg, aes(x)) + scale_fill_brewer(palette = "{color}") g1 <- g + geom_histogram(aes(fill=y), binwidth = .1, col="black", size=.1) # change binwidth g2 <- g + geom_histogram(aes(fill=y), bins=5, col="black", size=.1) # change number of bins gg <- if({model}) g2 else g1 gg <- gg + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position # 实例文件 Distribution_HistogramOfClassificationVariables.csv def Distribution_HistogramOfClassificationVariables(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_classic()) # Histogram on a Categorical variable g <- ggplot(datas, aes(x)) gg <- g + geom_bar(aes(fill=y), width = 0.5) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, color # 实例文件 Distribution_PopulationPyramid.csv def Distribution_PopulationPyramid(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, legend, legend_name, color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] legend <- datas[,3] library(ggplot2) library(ggthemes) options(scipen = 999) # turns of scientific notations like 1e+40 # X Axis Breaks and Labels brks <- seq(-15000000, 15000000, 5000000) lbls = paste0(as.character(c(seq(15, 0, -5), seq(5, 15, 5))), "m") # Plot g <- ggplot(datas, aes(x = x, y = y, fill = legend)) # Fill column gg <- g + geom_bar(stat = "identity", width = .6) + # draw the bars scale_y_continuous(breaks = brks, # Breaks labels = lbls) + # Labels coord_flip() + # Flip axes labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}")+ theme_tufte() + # Tufte theme from ggfortify theme(plot.title = element_text(hjust = .5), axis.ticks = element_blank()) + # Centre plot title scale_fill_brewer(palette = "{color}") # Color palette gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, color # 实例文件 Distribution_TufteBox.csv def Distribution_TufteBox(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggthemes) library(ggplot2) theme_set(theme_tufte()) # from ggthemes # plot g <- ggplot(datas, aes(x, y, fill=x)) gg <- g + geom_tufteboxplot(color="{color}") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color # 实例文件 Distribution_Violin.csv def Distribution_Violin(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position, line_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_bw()) g <- ggplot(datas, aes(x, y, fill=x)) gg <- g + geom_violin(color="{line_color}") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 基础参数 file_path, chart_out_path, out_path, title, caption, subtitle, title_font_size, # 高级参数 title_font_color # 实例文件 Group_HierarchicalTree.csv def Group_HierarchicalTree(file_path, chart_out_path, out_path, title, caption, subtitle, title_font_size, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}", row.names = 1) library(ggplot2) library(ggdendro) theme_set(theme_bw()) hc <- hclust(dist(datas), "ave") # hierarchical clustering # plot gg <- ggdendrogram(hc, rotate = TRUE, size = 2) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position # 实例文件 Sort_Dots.csv def Sort_Dots(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) library(scales) theme_set(theme_classic()) # Plot gg <- ggplot(datas, aes(x, y, fill=x)) + geom_point(col="tomato2", size=3) + # Draw points geom_segment(aes(x=x, xend=x, y=min(y), yend=max(y)), linetype="dashed", size=0.1) + # Draw dashed lines coord_flip() + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, species_1, species_2 # 实例文件 Sort_Lean.csv def Sort_Lean(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, time_1, time_2, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, species_1, species_2): file_path = file_path.replace("\\", "\\\\") code = f""" df <- read.csv("{file_path}") library(ggplot2) library(scales) theme_set(theme_classic()) # prep data colnames(df) <- c("continent", "{time_1}", "{time_2}") left_label <- paste(df$continent, round(df$`{time_1}`),sep=", ") right_label <- paste(df$continent, round(df$`{time_2}`),sep=", ") df$class <- ifelse((df$`{time_2}` - df$`{time_1}`) < 0, "red", "green") # Plot g <- ggplot(df) + geom_segment(aes(x=1, xend=2, y=`{time_1}`, yend=`{time_2}`, col=class), size=.75, show.legend=F) + geom_vline(xintercept=1, linetype="dashed", size=.1) + geom_vline(xintercept=2, linetype="dashed", size=.1) + scale_color_manual(labels = c("Up", "Down"), values = c("green"="#00ba38", "red"="#f8766d")) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) + xlim(.5, 2.5) + ylim(0,(1.1*(max(df$`{time_1}`, df$`{time_2}`)))) # Add texts g <- g + geom_text(label=left_label, y=df$`{time_1}`, x=rep(1, NROW(df)), hjust=1.1, size=3.5) g <- g + geom_text(label=right_label, y=df$`{time_2}`, x=rep(2, NROW(df)), hjust=-0.1, size=3.5) g <- g + geom_text(label="{species_1}", x=1, y=1.1*(max(df$`{time_1}`, df$`{time_2}`)), hjust=1.2, size=5) g <- g + geom_text(label="{species_2}", x=2, y=1.1*(max(df$`{time_1}`, df$`{time_2}`)), hjust=-0.1, size=5) # Minify theme gg <- g + theme(panel.grid = element_blank(), axis.ticks = element_blank(), axis.text.x = element_blank(), panel.border = element_blank(), plot.margin = unit(c(1,2,1,2), "cm")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position # 实例文件 Sort_Lollipop.csv def Sort_Lollipop(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) theme_set(theme_bw()) # Plot gg <- ggplot(datas, aes(x, y, fill=x)) + geom_point(size=3) + geom_segment(aes(x=x, xend=x, y=0, yend=y)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 Sort_OrderedBar.csv def Sort_OrderedBar(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") x_name = x_name.replace(' ', '_') y_name = y_name.replace(' ', '_') code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] df <- aggregate(y, by=list(x), FUN=mean) colnames(df) <- c("{x_name}", "{y_name}") df <- df[order(df${y_name}), ] df${x_name} <- factor(df${x_name}, levels = df${x_name}) library(ggplot2) theme_set(theme_bw()) # Draw plot gg <- ggplot(df, aes(x={x_name}, y={y_name}, fill={x_name})) + geom_bar(stat="identity", width=.5, fill="tomato3") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 TemporalChanges_Accumulation.csv def TemporalChanges_Accumulation(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, type_1, type_2, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] z <- datas[,3] library(ggplot2) library(lubridate) theme_set(theme_bw()) x <- as.Date(x) # labels and breaks for X axis text brks <- x[seq(1, length(x), 12)] lbls <- lubridate::year(brks) # plot gg <- ggplot(datas, aes(x)) + geom_area(aes(y=y+z, fill="{type_1}")) + geom_area(aes(y=z, fill="{type_2}")) + scale_x_date(labels = lbls, breaks = brks) + scale_fill_manual( values = c("{type_1}"="#00ba38", "{type_2}"="#f8766d")) + theme(panel.grid.minor = element_blank()) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position # 实例文件 TemporalChanges_CalendarHeat.csv def TemporalChanges_CalendarHeat(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, legend, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color, legend_name, legend_position): file_path = file_path.replace("\\", "\\\\") code = f""" df <- read.csv("{file_path}") x <- df[,1] y <- df[,2] z <- df[,3] w <- df[,4] v <- df[,5] u <- df[,6] library(ggplot2) library(plyr) library(scales) library(zoo) x <- as.Date(x) # format date names(df) <- c("x", "y", "z", "w", "v", "u") # Create Month Week df$yearmonth <- as.yearmon(x) df$yearmonthf <- factor(df$yearmonth) df <- ddply(df,.(yearmonthf), transform, monthweek=1+u-min(u)) # Plot gg <- ggplot(df, aes(monthweek, v, fill = y)) + geom_tile(colour = "white") + facet_grid(z~w) + scale_fill_gradient(low="red", high="green") + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", fill="{legend_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}"), legend.position="{legend_position}") gg <- if(!{legend}) gg+guides(fill="none") else gg png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 TemporalChanges_DataframeTimeSeries.csv def TemporalChanges_DataframeTimeSeries(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] x <- as.Date(x) library(ggplot2) theme_set(theme_classic()) # Allow Default X Axis Labels gg <- ggplot(datas, aes(x)) + geom_line(aes(y=y)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 TemporalChanges_SeasonalTimeSeries.csv def TemporalChanges_SeasonalTimeSeries(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, time, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): time = time.split("-") time = (int(time[0]), int(time[1])) file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") datas <- ts(datas, frequency = 12, start = c({time[0]},{time[1]})) library(ggplot2) library(forecast) theme_set(theme_classic()) # Plot gg <-ggseasonplot(datas) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 TemporalChanges_ShowMultipleTimeSeriesSimultaneously.csv def TemporalChanges_ShowMultipleTimeSeriesSimultaneously(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, type_1, type_2, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] z <- datas[,3] library(ggplot2) library(lubridate) theme_set(theme_bw()) x <- as.Date(x) # labels and breaks for X axis text brks <- x[seq(1, length(x), 12)] lbls <- lubridate::year(brks) # plot gg <- ggplot(datas, aes(x)) + geom_line(aes(y=y, col=z)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}", color=NULL) + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) + # title and caption scale_x_date(labels = lbls, breaks = brks) + scale_color_manual(labels = c("{type_1}", "{type_2}"), values = c("{type_1}"="#00ba38", "{type_2}"="#f8766d")) + theme(panel.grid.minor = element_blank()) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 TemporalChanges_TimeSeries.csv def TemporalChanges_TimeSeries(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, time, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): time = time.split("-") time = (int(time[0]), int(time[1])) file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") datas <- ts(datas, frequency = 12, start = c({time[0]},{time[1]})) library(ggplot2) library(ggfortify) theme_set(theme_classic()) # Plot gg <- autoplot(datas) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 TemporalChanges_TimeSeriesOfAnnualData.csv def TemporalChanges_TimeSeriesOfAnnualData(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) library(lubridate) theme_set(theme_bw()) x <- as.Date(x) # labels and breaks for X axis text brks <- x[seq(1, length(x), 12)] lbls <- lubridate::year(brks) # plot gg <- ggplot(datas, aes(x)) + geom_line(aes(y=y)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) + # title and caption scale_x_date(labels = lbls, breaks = brks) + theme(panel.grid.minor = element_blank()) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 高级参数 x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color # 实例文件 TemporalChanges_TimeSeriesOfMonthlyData.csv def TemporalChanges_TimeSeriesOfMonthlyData(file_path, chart_out_path, out_path, title, caption, subtitle, x_name, y_name, title_font_size, x_font_size, y_font_size, x_scale_font_size, y_scale_font_size, x_scale_font_angle, y_scale_font_angle, x_font_color, y_font_color, x_scale_font_color, y_scale_font_color, title_font_color): file_path = file_path.replace("\\", "\\\\") code = f""" datas <- read.csv("{file_path}") x <- datas[,1] y <- datas[,2] library(ggplot2) library(lubridate) theme_set(theme_bw()) x <- as.Date(x) # labels and breaks for X axis text lbls <- paste0(month.abb[month(x)], " ", lubridate::year(x)) brks <- x # plot gg <- ggplot(datas, aes(x)) + geom_line(aes(y=y)) + labs(title="{title}", subtitle="{subtitle}", caption="{caption}", x="{x_name}", y="{y_name}") + theme(title=element_text(size={title_font_size}, color="{title_font_color}"), axis.text.x=element_text(color="{x_scale_font_color}", size={x_scale_font_size}, angle={x_scale_font_angle}, vjust=0.6), axis.text.y=element_text(color="{y_scale_font_color}", size={y_scale_font_size}, angle={y_scale_font_angle}), axis.title.x=element_text(size={x_font_size}, color="{x_font_color}"), axis.title.y=element_text(size={y_font_size}, color="{y_font_color}")) + # title and caption scale_x_date(labels = lbls, breaks = brks) + theme(panel.grid.minor = element_blank()) png("{chart_out_path}",width=900,height=408) plot(gg) dev.off() png("{out_path}.png") plot(gg) dev.off() pdf("{out_path}.pdf") plot(gg) dev.off() svg("{out_path}.svg") plot(gg) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 最后一组 # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, scale_font_size, font_size, heading_1, heading_2, heading_font_size # 高级参数 title_font_color, scale_font_color, line_color, font_color, heading_font_color # 示例文件 Aggregated_Pyramids.xlsx def Aggregated_Pyramids(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, scale_font_size, font_size, heading_1, heading_2, heading_font_size, title_font_color, scale_font_color, line_color, font_color, heading_font_color): code = f""" library(gdata) x<-read.xls("{file_path}", encoding="latin1") names(x) <- c("","Group","M","F","des") pdf("{out_path}.pdf") par(mai=c(0.2,0.25,0.8,0.25),omi=c(0.75,0.2,0.85,0.2),cex=0.75,las=1) right<-t(as.matrix(data.frame(800,x$F))) left<--t(as.matrix(data.frame(800,x$M))) myColour_right<-c(par("bg"),rgb(255,0,210,150,maxColorValue=255)) myColour_left<-c(par("bg"),rgb(191,239,255,maxColorValue=255)) b1<-barplot(right,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_right,xlim=c(-8000,8000)) barplot(left,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_left,xlim=c(-7500,7500),add=T) abline(v=seq(0,6000,by=2000)+800,col="{line_color}",lty=3) abline(v=seq(-6000,0,by=2000)-800,col="{line_color}",lty=3) mtext(format(seq(0,6000,by=2000),big.mark="."),at=seq(0,6000,by=2000)+800,1,line=0,cex={scale_font_size},col="{scale_font_color}") mtext(format(abs(seq(-6000,0,by=2000)),big.mark="."),at=seq(-6000,0,by=2000)-800,1,line=0,cex={scale_font_size},col="{scale_font_color}") text(0,b1,x$des,cex={font_size},font=3,col="{font_color}") mtext("{heading_1}",3,line=1,adj=0.25,cex={heading_font_size},col="{heading_font_color}") mtext("{heading_2}",3,line=1,adj=0.75,cex={heading_font_size},col="{heading_font_color}") mtext("{title}",3,line=2,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.5,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("...",1,line=2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(mai=c(0.2,0.25,0.8,0.25),omi=c(0.75,0.2,0.85,0.2),cex=0.75,las=1) right<-t(as.matrix(data.frame(800,x$F))) left<--t(as.matrix(data.frame(800,x$M))) myColour_right<-c(par("bg"),rgb(255,0,210,150,maxColorValue=255)) myColour_left<-c(par("bg"),rgb(191,239,255,maxColorValue=255)) b1<-barplot(right,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_right,xlim=c(-8000,8000)) barplot(left,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_left,xlim=c(-7500,7500),add=T) abline(v=seq(0,6000,by=2000)+800,col="{line_color}",lty=3) abline(v=seq(-6000,0,by=2000)-800,col="{line_color}",lty=3) mtext(format(seq(0,6000,by=2000),big.mark="."),at=seq(0,6000,by=2000)+800,1,line=0,cex={scale_font_size},col="{scale_font_color}") mtext(format(abs(seq(-6000,0,by=2000)),big.mark="."),at=seq(-6000,0,by=2000)-800,1,line=0,cex={scale_font_size},col="{scale_font_color}") text(0,b1,x$des,cex={font_size},font=3,col="{font_color}") mtext("{heading_1}",3,line=1,adj=0.25,cex={heading_font_size},col="{heading_font_color}") mtext("{heading_2}",3,line=1,adj=0.75,cex={heading_font_size},col="{heading_font_color}") mtext("{title}",3,line=2,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.5,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("...",1,line=2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() png("{out_path}.png") par(mai=c(0.2,0.25,0.8,0.25),omi=c(0.75,0.2,0.85,0.2),cex=0.75,las=1) right<-t(as.matrix(data.frame(800,x$F))) left<--t(as.matrix(data.frame(800,x$M))) myColour_right<-c(par("bg"),rgb(255,0,210,150,maxColorValue=255)) myColour_left<-c(par("bg"),rgb(191,239,255,maxColorValue=255)) b1<-barplot(right,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_right,xlim=c(-8000,8000)) barplot(left,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_left,xlim=c(-7500,7500),add=T) abline(v=seq(0,6000,by=2000)+800,col="{line_color}",lty=3) abline(v=seq(-6000,0,by=2000)-800,col="{line_color}",lty=3) mtext(format(seq(0,6000,by=2000),big.mark="."),at=seq(0,6000,by=2000)+800,1,line=0,cex={scale_font_size},col="{scale_font_color}") mtext(format(abs(seq(-6000,0,by=2000)),big.mark="."),at=seq(-6000,0,by=2000)-800,1,line=0,cex={scale_font_size},col="{scale_font_color}") text(0,b1,x$des,cex={font_size},font=3,col="{font_color}") mtext("{heading_1}",3,line=1,adj=0.25,cex={heading_font_size},col="{heading_font_color}") mtext("{heading_2}",3,line=1,adj=0.75,cex={heading_font_size},col="{heading_font_color}") mtext("{title}",3,line=2,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.5,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("...",1,line=2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() svg("{out_path}.svg") par(mai=c(0.2,0.25,0.8,0.25),omi=c(0.75,0.2,0.85,0.2),cex=0.75,las=1) right<-t(as.matrix(data.frame(800,x$F))) left<--t(as.matrix(data.frame(800,x$M))) myColour_right<-c(par("bg"),rgb(255,0,210,150,maxColorValue=255)) myColour_left<-c(par("bg"),rgb(191,239,255,maxColorValue=255)) b1<-barplot(right,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_right,xlim=c(-8000,8000)) barplot(left,axes=F,horiz=T,axis.lty=0,border=NA,col=myColour_left,xlim=c(-7500,7500),add=T) abline(v=seq(0,6000,by=2000)+800,col="{line_color}",lty=3) abline(v=seq(-6000,0,by=2000)-800,col="{line_color}",lty=3) mtext(format(seq(0,6000,by=2000),big.mark="."),at=seq(0,6000,by=2000)+800,1,line=0,cex={scale_font_size},col="{scale_font_color}") mtext(format(abs(seq(-6000,0,by=2000)),big.mark="."),at=seq(-6000,0,by=2000)-800,1,line=0,cex={scale_font_size},col="{scale_font_color}") text(0,b1,x$des,cex={font_size},font=3,col="{font_color}") mtext("{heading_1}",3,line=1,adj=0.25,cex={heading_font_size},col="{heading_font_color}") mtext("{heading_2}",3,line=1,adj=0.75,cex={heading_font_size},col="{heading_font_color}") mtext("{title}",3,line=2,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.5,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("...",1,line=2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, event_1, event_2, event_3, font_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, font_color, line_color, color # 示例文件 Areas_Under_a_Time_Series.csv def Areas_Under_a_Time_Series(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, event_1, event_2, event_3, font_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, font_color, line_color, color): font_color = font_color[4:-1] color = color[4:-1] code = f""" library(gdata) colour<-rgb({font_color},150,maxColorValue=255) myShapeColour1<-rgb({color},50,maxColorValue=255) myShapeColour2<-rgb({color},80,maxColorValue=255) myData<-read.csv('{file_path}',encoding="latin1") names(myData) <- c("x","y") attach(myData) mySelection<-subset(myData,x >= 1879 & x <= 1884) pdf("{out_path}.pdf") par(cex.axis=1.1,mai=c(0.75,1.5,0.25,0.5),omi=c(0.5,0.5,1.1,0.5), mgp=c(6,1,0),las=1) plot(x,y,axes=F,type="n",xlab="",xlim=c(1800,2020),ylim=c(0,14000),xpd=T,ylab="{y_name}",cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,at=pretty(x),col="{x_scale_font_color}",cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,at=py<-pretty(y),col="{y_scale_font_color}",cex.lab=1.2,labels=format(py,big.mark=","),cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}") y<-ts(y,start=1800,frequency=1) points(window(y, end=1869),col="{line_color}") lines(window(y, start=1870),col="{line_color}") attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour2,border=NA) text(1860,2200,adj=0,col=colour,"{event_1}",cex={font_size}) mySelection<-subset(myData,x >= 1940 & x <= 1973) attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour1,border=NA) text(1930,5000,adj=0,col=colour,"{event_2}",cex={font_size}) mySelection<-subset(myData,x >= 1973 & x <= 1990) attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour2,border=NA) text(1960,6800,adj=0,col=colour,"{event_3}",cex={font_size}) mtext("{title}",3,line=2,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.5,adj=0,cex={title_font_size}*0.6,font=3, outer=T,col="{title_font_color}") mtext("{caption}",1,line=4.5,adj=1,cex={title_font_size}*0.4,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.57,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() myData<-read.csv('{file_path}',encoding="latin1") names(myData) <- c("x","y") attach(myData) mySelection<-subset(myData,x >= 1879 & x <= 1884) png("{char_out_path}",width=900,height=540) par(cex.axis=1.1,mai=c(0.75,1.5,0.25,0.5),omi=c(0.5,0.5,1.1,0.5), mgp=c(6,1,0),las=1) plot(x,y,axes=F,type="n",xlab="",xlim=c(1800,2020),ylim=c(0,14000),xpd=T,ylab="{y_name}",cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,at=pretty(x),col="{x_scale_font_color}",cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,at=py<-pretty(y),col="{y_scale_font_color}",cex.lab=1.2,labels=format(py,big.mark=","),cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}") y<-ts(y,start=1800,frequency=1) points(window(y, end=1869),col="{line_color}") lines(window(y, start=1870),col="{line_color}") attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour2,border=NA) text(1860,2200,adj=0,col=colour,"{event_1}",cex={font_size}) mySelection<-subset(myData,x >= 1940 & x <= 1973) attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour1,border=NA) text(1930,5000,adj=0,col=colour,"{event_2}",cex={font_size}) mySelection<-subset(myData,x >= 1973 & x <= 1990) attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour2,border=NA) text(1960,6800,adj=0,col=colour,"{event_3}",cex={font_size}) mtext("{title}",3,line=2,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.5,adj=0,cex={title_font_size}*0.6,font=3, outer=T,col="{title_font_color}") mtext("{caption}",1,line=4.5,adj=1,cex={title_font_size}*0.4,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.57,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() myData<-read.csv('{file_path}',encoding="latin1") names(myData) <- c("x","y") attach(myData) mySelection<-subset(myData,x >= 1879 & x <= 1884) png("{out_path}.png") par(cex.axis=1.1,mai=c(0.75,1.5,0.25,0.5),omi=c(0.5,0.5,1.1,0.5), mgp=c(6,1,0),las=1) plot(x,y,axes=F,type="n",xlab="",xlim=c(1800,2020),ylim=c(0,14000),xpd=T,ylab="{y_name}",cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,at=pretty(x),col="{x_scale_font_color}",cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,at=py<-pretty(y),col="{y_scale_font_color}",cex.lab=1.2,labels=format(py,big.mark=","),cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}") y<-ts(y,start=1800,frequency=1) points(window(y, end=1869),col="{line_color}") lines(window(y, start=1870),col="{line_color}") attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour2,border=NA) text(1860,2200,adj=0,col=colour,"{event_1}",cex={font_size}) mySelection<-subset(myData,x >= 1940 & x <= 1973) attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour1,border=NA) text(1930,5000,adj=0,col=colour,"{event_2}",cex={font_size}) mySelection<-subset(myData,x >= 1973 & x <= 1990) attach(mySelection) polygon(c(min(mySelection$x),mySelection$x,max(mySelection$x)),c(-500,mySelection$y,-500),col=myShapeColour2,border=NA) text(1960,6800,adj=0,col=colour,"{event_3}",cex={font_size}) mtext("{title}",3,line=2,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.5,adj=0,cex={title_font_size}*0.6,font=3, outer=T,col="{title_font_color}") mtext("{caption}",1,line=4.5,adj=1,cex={title_font_size}*0.4,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.57,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption_1, caption_2, subtitle, title_font_size, font_size # 高级参数 title_font_color, font_color, color_1, color_2 # 示例文件 Balloon_Plot.csv def Balloon_Plot(file_path, char_out_path, out_path, title, caption_1, caption_2, subtitle, title_font_size, font_size, title_font_color, font_color, color_1, color_2): code = f""" library(gplots) myData <- read.csv("{file_path}") attach(myData) myColours <- character(length(myData$Survived)) for(i in 1:length(myData$Survived)) myColours[i] <- if(myData$Survived[i] == "Yes") "{color_1}" else "{color_2}" pdf("{out_path}.pdf") par(omi=c(0.75,0.25,0.5,0.25),mai=c(0.25,0.55,0.25,0),cex={font_size}) balloonplot(x=list(Age,Sex),main="", y=list(Class=Class, Survived=gdata::reorder.factor(Survived,new.order=c(2,1))), z=Freq,dotsize=18, sort=T, dotcol=myColours, show.zeros=T, show.margins=T, text.color="{font_color}", label.color="{font_color}") mtext("{title}",3,line=0,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_1}",1,line=1,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_2}",1,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() png("{out_path}.png") par(omi=c(0.75,0.25,0.5,0.25),mai=c(0.25,0.55,0.25,0),cex={font_size}) balloonplot(x=list(Age,Sex),main="", y=list(Class=Class, Survived=gdata::reorder.factor(Survived,new.order=c(2,1))), z=Freq,dotsize=18, sort=T, dotcol=myColours, show.zeros=T, show.margins=T, text.color="{font_color}", label.color="{font_color}") mtext("{title}",3,line=0,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_1}",1,line=1,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_2}",1,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() svg("{out_path}.svg") par(omi=c(0.75,0.25,0.5,0.25),mai=c(0.25,0.55,0.25,0),cex={font_size}) balloonplot(x=list(Age,Sex),main="", y=list(Class=Class, Survived=gdata::reorder.factor(Survived,new.order=c(2,1))), z=Freq,dotsize=18, sort=T, dotcol=myColours, show.zeros=T, show.margins=T, text.color="{font_color}", label.color="{font_color}") mtext("{title}",3,line=0,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_1}",1,line=1,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_2}",1,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() png("{char_out_path}",width=900,height=408) par(omi=c(0.75,0.25,0.5,0.25),mai=c(0.25,0.55,0.25,0),cex={font_size}) balloonplot(x=list(Age,Sex),main="", y=list(Class=Class, Survived=gdata::reorder.factor(Survived,new.order=c(2,1))), z=Freq,dotsize=18, sort=T, dotcol=myColours, show.zeros=T, show.margins=T, text.color="{font_color}", label.color="{font_color}") mtext("{title}",3,line=0,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-2,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_1}",1,line=1,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption_2}",1,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, image_name_font_size, mark_country_1, mark_country_2, average_font_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, image_name_font_color, average_font_color, mark_color, color # 示例文件 Bar_Chart_Simple.xlsx def Bar_Chart_Simple(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, image_name_font_size, mark_country_1, mark_country_2, average_font_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, image_name_font_color, background_color, average_font_color, mark_color, color): y_name = "\n".join(y_name) background_color = background_color[4:-1] mark_color = mark_color[4:-1] code = f""" library(gdata) ipsos<-read.xls('{file_path}',encoding="latin1") names(ipsos) <- c("Country","Percent") sort.ipsos<-ipsos[order(ipsos$Percent) ,] attach(sort.ipsos) percent_max <- max(ipsos[,2])/2 myValue2 <- numeric(length(Country)) pdf("{out_path}.pdf") par(omi=c(0.65,0.25,0.75,0.75),mai=c(0.3,2,0.35,0),mgp=c(3,3,0),las=1) x<-barplot(Percent,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col="{color}", cex.names=0.85,axes=F) for (i in 1:length(Country)) {{ if (Country[i] %in% c("{mark_country_1}","{mark_country_2}")) {{ myValue2[i] <- Percent[i] text(-8,x[i],Country[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} text(-3.5,x[i],Percent[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} rect(0,-0.5,20,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(20,-0.5,40,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(40,-0.5,60,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(60,-0.5,80,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(80,-0.5,100,28,col=rgb({background_color},80,maxColorValue=255),border=NA) myColour2<-rgb({mark_color},maxColorValue=255) x2<-barplot(myValue2,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col=myColour2,cex.names=0.85,axes=F,add=T) arrows(percent_max,-0.5,percent_max,20.5,lwd=1.5,length=0,xpd=T,col="{average_font_color}") arrows(percent_max,-0.5,percent_max,-0.75,lwd=3,length=0,xpd=T) arrows(percent_max,20.5,percent_max,20.75,lwd=3,length=0,xpd=T) text(percent_max-5,20.5,"Average",adj=1,xpd=T,cex={average_font_size},font=3) text(percent_max-1,20.5,percent_max,adj=1,xpd=T,cex={average_font_size},font=4,col="{average_font_color}") text(100,20.5,"All values in percent",adj=1,xpd=T,cex={image_name_font_size},font=3,col="{image_name_font_color}") mtext(c(0,20,40,60,80,100),at=c(0,20,40,60,80,100),1,line=0,cex={x_scale_font_size},col="{x_scale_font_color}") mtext("{title}",3,line={title_font_size},adj=0,cex=1.2,outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.4,adj=0,cex={title_font_size}*0.6,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1.0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-0.2,adj=0.6,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",2,line=0.25,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() png("{out_path}.png") par(omi=c(0.65,0.25,0.75,0.75),mai=c(0.3,2,0.35,0),mgp=c(3,3,0),las=1) x<-barplot(Percent,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col="{color}", cex.names=0.85,axes=F) for (i in 1:length(Country)) {{ if (Country[i] %in% c("{mark_country_1}","{mark_country_2}")) {{ myValue2[i] <- Percent[i] text(-8,x[i],Country[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} text(-3.5,x[i],Percent[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} rect(0,-0.5,20,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(20,-0.5,40,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(40,-0.5,60,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(60,-0.5,80,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(80,-0.5,100,28,col=rgb({background_color},80,maxColorValue=255),border=NA) myColour2<-rgb({mark_color},maxColorValue=255) x2<-barplot(myValue2,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col=myColour2,cex.names=0.85,axes=F,add=T) arrows(percent_max,-0.5,percent_max,20.5,lwd=1.5,length=0,xpd=T,col="{average_font_color}") arrows(percent_max,-0.5,percent_max,-0.75,lwd=3,length=0,xpd=T) arrows(percent_max,20.5,percent_max,20.75,lwd=3,length=0,xpd=T) text(percent_max-5,20.5,"Average",adj=1,xpd=T,cex={average_font_size},font=3) text(percent_max-1,20.5,percent_max,adj=1,xpd=T,cex={average_font_size},font=4,col="{average_font_color}") text(100,20.5,"All values in percent",adj=1,xpd=T,cex={image_name_font_size},font=3,col="{image_name_font_color}") mtext(c(0,20,40,60,80,100),at=c(0,20,40,60,80,100),1,line=0,cex={x_scale_font_size},col="{x_scale_font_color}") mtext("{title}",3,line={title_font_size},adj=0,cex=1.2,outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.4,adj=0,cex={title_font_size}*0.6,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1.0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-0.2,adj=0.6,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",2,line=0.25,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() png("{char_out_path}",width=900,height=408) par(omi=c(0.65,0.25,0.75,0.75),mai=c(0.3,2,0.35,0),mgp=c(3,3,0),las=1) x<-barplot(Percent,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col="{color}", cex.names=0.85,axes=F) for (i in 1:length(Country)) {{ if (Country[i] %in% c("{mark_country_1}","{mark_country_2}")) {{ myValue2[i] <- Percent[i] text(-8,x[i],Country[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} text(-3.5,x[i],Percent[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} rect(0,-0.5,20,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(20,-0.5,40,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(40,-0.5,60,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(60,-0.5,80,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(80,-0.5,100,28,col=rgb({background_color},80,maxColorValue=255),border=NA) myColour2<-rgb({mark_color},maxColorValue=255) x2<-barplot(myValue2,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col=myColour2,cex.names=0.85,axes=F,add=T) arrows(percent_max,-0.5,percent_max,20.5,lwd=1.5,length=0,xpd=T,col="{average_font_color}") arrows(percent_max,-0.5,percent_max,-0.75,lwd=3,length=0,xpd=T) arrows(percent_max,20.5,percent_max,20.75,lwd=3,length=0,xpd=T) text(percent_max-5,20.5,"Average",adj=1,xpd=T,cex={average_font_size},font=3) text(percent_max-1,20.5,percent_max,adj=1,xpd=T,cex={average_font_size},font=4,col="{average_font_color}") text(100,20.5,"All values in percent",adj=1,xpd=T,cex={image_name_font_size},font=3,col="{image_name_font_color}") mtext(c(0,20,40,60,80,100),at=c(0,20,40,60,80,100),1,line=0,cex={x_scale_font_size},col="{x_scale_font_color}") mtext("{title}",3,line={title_font_size},adj=0,cex=1.2,outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.4,adj=0,cex={title_font_size}*0.6,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1.0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-0.2,adj=0.6,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",2,line=0.25,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() svg("{out_path}.svg") par(omi=c(0.65,0.25,0.75,0.75),mai=c(0.3,2,0.35,0),mgp=c(3,3,0),las=1) x<-barplot(Percent,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col="{color}", cex.names=0.85,axes=F) for (i in 1:length(Country)) {{ if (Country[i] %in% c("{mark_country_1}","{mark_country_2}")) {{ myValue2[i] <- Percent[i] text(-8,x[i],Country[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} text(-3.5,x[i],Percent[i],xpd=T,adj=1,cex={y_scale_font_size},col="{y_scale_font_color}") }} rect(0,-0.5,20,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(20,-0.5,40,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(40,-0.5,60,28,col=rgb({background_color},80,maxColorValue=255),border=NA) rect(60,-0.5,80,28,col=rgb({background_color},120,maxColorValue=255),border=NA) rect(80,-0.5,100,28,col=rgb({background_color},80,maxColorValue=255),border=NA) myColour2<-rgb({mark_color},maxColorValue=255) x2<-barplot(myValue2,names.arg=F,horiz=T,border=NA,xlim=c(0,100),col=myColour2,cex.names=0.85,axes=F,add=T) arrows(percent_max,-0.5,percent_max,20.5,lwd=1.5,length=0,xpd=T,col="{average_font_color}") arrows(percent_max,-0.5,percent_max,-0.75,lwd=3,length=0,xpd=T) arrows(percent_max,20.5,percent_max,20.75,lwd=3,length=0,xpd=T) text(percent_max-5,20.5,"Average",adj=1,xpd=T,cex={average_font_size},font=3) text(percent_max-1,20.5,percent_max,adj=1,xpd=T,cex={average_font_size},font=4,col="{average_font_color}") text(100,20.5,"All values in percent",adj=1,xpd=T,cex={image_name_font_size},font=3,col="{image_name_font_color}") mtext(c(0,20,40,60,80,100),at=c(0,20,40,60,80,100),1,line=0,cex={x_scale_font_size},col="{x_scale_font_color}") mtext("{title}",3,line={title_font_size},adj=0,cex=1.2,outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=-0.4,adj=0,cex={title_font_size}*0.6,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1.0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-0.2,adj=0.6,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",2,line=0.25,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, scale_font_size # 高级参数 title_font_color, scale_font_color, mark_scale_font_color, font_color # 示例文件 Bump_Chart.xlsx def Bump_Chart(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, scale_font_size, title_font_color, scale_font_color, mark_scale_font_color, font_color): code = f""" library(plotrix) library(gdata) z1<-read.xls('{file_path}', row.names = 1, encoding="latin1") myColours<-rep("{scale_font_color}",nrow(z1)); myLineWidth<-rep(1,nrow(z1)) myColours[5]<-"{mark_scale_font_color}"; myLineWidth[5]<-8 pdf("{out_path}.pdf") par(omi=c(0.5,0.5,0.9,0.5),mai=c(0,0.75,0.25,0.75),xpd=T,las=1,col="{font_color}") bumpchart(z1,rank=F,pch=18,top.labels=c("",""),col=myColours,lwd=myLineWidth,mar=c(2,12,1,12),cex=1.1) mtext("{title}",3,line=1.5,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{caption}",1,line=0,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2002), max(z1$r2002)),c(round(min(z1$r2002)/1000,digits=1), round(max(z1$r2002)/1000, digits=1)),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2011), max(z1$r2011)),c(round(min(z1$r2011)/1000,digits=1), round(max(z1$r2011)/1000, digits=1)),cex.axis={scale_font_size}) mtext("{subtitle}",3,font=3,adj=0,cex={title_font_size}*0.6,line=-0.5,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,1],round(z1[5,1]/1000, digits=1),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,2],round(z1[5,2]/1000, digits=1),cex.axis={scale_font_size}) dev.off() png("{out_path}.png") par(omi=c(0.5,0.5,0.9,0.5),mai=c(0,0.75,0.25,0.75),xpd=T,las=1,col="{font_color}") bumpchart(z1,rank=F,pch=18,top.labels=c("",""),col=myColours,lwd=myLineWidth,mar=c(2,12,1,12),cex=1.1) mtext("{title}",3,line=1.5,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{caption}",1,line=0,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2002), max(z1$r2002)),c(round(min(z1$r2002)/1000,digits=1), round(max(z1$r2002)/1000, digits=1)),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2011), max(z1$r2011)),c(round(min(z1$r2011)/1000,digits=1), round(max(z1$r2011)/1000, digits=1)),cex.axis={scale_font_size}) mtext("{subtitle}",3,font=3,adj=0,cex={title_font_size}*0.6,line=-0.5,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,1],round(z1[5,1]/1000, digits=1),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,2],round(z1[5,2]/1000, digits=1),cex.axis={scale_font_size}) dev.off() png("{char_out_path}",width=900,height=540) par(omi=c(0.5,0.5,0.9,0.5),mai=c(0,0.75,0.25,0.75),xpd=T,las=1,col="{font_color}") bumpchart(z1,rank=F,pch=18,top.labels=c("",""),col=myColours,lwd=myLineWidth,mar=c(2,12,1,12),cex=1.1) mtext("{title}",3,line=1.5,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{caption}",1,line=0,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2002), max(z1$r2002)),c(round(min(z1$r2002)/1000,digits=1), round(max(z1$r2002)/1000, digits=1)),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2011), max(z1$r2011)),c(round(min(z1$r2011)/1000,digits=1), round(max(z1$r2011)/1000, digits=1)),cex.axis={scale_font_size}) mtext("{subtitle}",3,font=3,adj=0,cex={title_font_size}*0.6,line=-0.5,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,1],round(z1[5,1]/1000, digits=1),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,2],round(z1[5,2]/1000, digits=1),cex.axis={scale_font_size}) dev.off() svg("{out_path}.svg") par(omi=c(0.5,0.5,0.9,0.5),mai=c(0,0.75,0.25,0.75),xpd=T,las=1,col="{font_color}") bumpchart(z1,rank=F,pch=18,top.labels=c("",""),col=myColours,lwd=myLineWidth,mar=c(2,12,1,12),cex=1.1) mtext("{title}",3,line=1.5,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{caption}",1,line=0,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2002), max(z1$r2002)),c(round(min(z1$r2002)/1000,digits=1), round(max(z1$r2002)/1000, digits=1)),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{scale_font_color}",col.axis="{scale_font_color}",lwd.ticks=0.5,tck=-0.025, at=c(min(z1$r2011), max(z1$r2011)),c(round(min(z1$r2011)/1000,digits=1), round(max(z1$r2011)/1000, digits=1)),cex.axis={scale_font_size}) mtext("{subtitle}",3,font=3,adj=0,cex={title_font_size}*0.6,line=-0.5,outer=T,col="{title_font_color}") axis(2,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,1],round(z1[5,1]/1000, digits=1),cex.axis={scale_font_size}) axis(4,col=par("bg"),col.ticks="{mark_scale_font_color}",col.axis="{mark_scale_font_color}",lwd.ticks=0.5,tck=-0.025,at=z1[5,2],round(z1[5,2]/1000, digits=1),cex.axis={scale_font_size}) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path,out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, high_color, low_color # 示例文件 Column_Chart_with_Percentages_for_Growth_Developments.csv def Column_Chart_for_Developments(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, high_color, low_color): y_name = "\n".join(y_name) code = f""" datas <- read.csv("{file_path}") myData <- datas[,2]/10000 myLabels <- datas[,1] myColours<-c(rep("{low_color}",length(myData)-1),"{high_color}") pdf("{out_path}.pdf") par(las=1,cex=0.9,omi=c(0.75,0.25,1.25,0.25),mai=c(0.5,0.25,0.5,0.75),las=1) barplot(myData,border=NA,col=myColours,names.arg=substr(myLabels,3,4),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) abline(h=c(10,20,30,40,50,60,70,80),col=par("bg"),lwd=1.5) axis(4,at=c(0,20,40,60),col="{y_scale_font_color}") text(11.5,myData[length(myData)]+0.025*myData[length(myData)],format(round(myData[length(myData)]),nsmall=1),adj=0.5,xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size}) # Titling mtext("{title}",3,line=4,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=0,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",4,line=0,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() png("{out_path}.png") par(las=1,cex=0.9,omi=c(0.75,0.25,1.25,0.25),mai=c(0.5,0.25,0.5,0.75),las=1) barplot(myData,border=NA,col=myColours,names.arg=substr(myLabels,3,4),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) abline(h=c(10,20,30,40,50,60,70,80),col=par("bg"),lwd=1.5) axis(4,at=c(0,20,40,60),col="{y_scale_font_color}") text(11.5,myData[length(myData)]+0.025*myData[length(myData)],format(round(myData[length(myData)]),nsmall=1),adj=0.5,xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size}) # Titling mtext("{title}",3,line=4,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=0,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",4,line=0,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(las=1,cex=0.9,omi=c(0.75,0.25,1.25,0.25),mai=c(0.5,0.25,0.5,0.75),las=1) barplot(myData,border=NA,col=myColours,names.arg=substr(myLabels,3,4),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) abline(h=c(10,20,30,40,50,60,70,80),col=par("bg"),lwd=1.5) axis(4,at=c(0,20,40,60),col="{y_scale_font_color}") text(11.5,myData[length(myData)]+0.025*myData[length(myData)],format(round(myData[length(myData)]),nsmall=1),adj=0.5,xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size}) # Titling mtext("{title}",3,line=4,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=0,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",4,line=0,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() svg("{out_path}.svg") par(las=1,cex=0.9,omi=c(0.75,0.25,1.25,0.25),mai=c(0.5,0.25,0.5,0.75),las=1) barplot(myData,border=NA,col=myColours,names.arg=substr(myLabels,3,4),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) abline(h=c(10,20,30,40,50,60,70,80),col=par("bg"),lwd=1.5) axis(4,at=c(0,20,40,60),col="{y_scale_font_color}") text(11.5,myData[length(myData)]+0.025*myData[length(myData)],format(round(myData[length(myData)]),nsmall=1),adj=0.5,xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size}) # Titling mtext("{title}",3,line=4,adj=0,outer=T,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,line=1,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1.0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=0,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") mtext("{y_name}",4,line=0,adj=0.5,cex={y_font_size},font=3,outer=T,col="{y_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path,out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, color, high_color, low_color # 示例文件 Column_Chart_with_Percentages_for_Growth_Developments.csv def Column_Chart_with_Percentages_for_Growth_Developments(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, color, high_color, low_color): code = f""" datas <- read.csv("{file_path}") myData <- datas[,2]/10000 myLabels <- datas[,1] pdf("{out_path}.pdf") par(las=1,cex=0.9,omi=c(0.75,0.5,1.25,0.5),mai=c(0.5,1,0,1),las=1) # Define data myGrowth<-0 for (i in 2:length(myData)) myGrowth<-c(myGrowth,myData[i]-myData[i-1]) myValueLeft<-myData-myGrowth x<-rbind(t(myData),t(myData)) y<-rbind(t(myValueLeft),rep(0,length(myData))) f1<-"{high_color}"; f2<-"{color}" myColours<-c(f1,f2) for (i in 1:length(myData)-1) myColours<-c(myColours,f1,f2) for (i in 1:length(myData)) {{ if (y[1,i]>x[1,i]) {{ tmp<-x[1,i]; x[1,i]<-y[1,i]; y[1,i]<-tmp myColours[(2*i)-1]<-"{low_color}" }} }} # Create chart and other elements barplot(x,beside=T,border=NA,col=myColours,space=c(0,2),axes=T,ylab="{y_name}",cex.lab={y_font_size},col.lab="{y_font_color}",col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size},fg="{y_scale_font_color}") barplot(y,beside=T,border=NA,col=rep("{color}",2*length(myData)),add=T,names.arg=myLabels,space=c(0,2),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) hoehe<-0.1*max(myData) j<-1 k<-j for (i in 1:length(myData)) {{ if (j > 1) k<-k+4 text(k+1.3,hoehe,format(round(x[2,i]),nsmall=0),cex=1.25,adj=0,xpd=T,col="white") j<-j+3 if (ix[1,i]) {{ tmp<-x[1,i]; x[1,i]<-y[1,i]; y[1,i]<-tmp myColours[(2*i)-1]<-"{low_color}" }} }} # Create chart and other elements barplot(x,beside=T,border=NA,col=myColours,space=c(0,2),axes=T,ylab="{y_name}",cex.lab={y_font_size},col.lab="{y_font_color}",col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size},fg="{y_scale_font_color}") barplot(y,beside=T,border=NA,col=rep("{color}",2*length(myData)),add=T,names.arg=myLabels,space=c(0,2),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) hoehe<-0.1*max(myData) j<-1 k<-j for (i in 1:length(myData)) {{ if (j > 1) k<-k+4 text(k+1.3,hoehe,format(round(x[2,i]),nsmall=0),cex=1.25,adj=0,xpd=T,col="white") j<-j+3 if (ix[1,i]) {{ tmp<-x[1,i]; x[1,i]<-y[1,i]; y[1,i]<-tmp myColours[(2*i)-1]<-"{low_color}" }} }} # Create chart and other elements barplot(x,beside=T,border=NA,col=myColours,space=c(0,2),axes=T,ylab="{y_name}",cex.lab={y_font_size},col.lab="{y_font_color}",col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size},fg="{y_scale_font_color}") barplot(y,beside=T,border=NA,col=rep("{color}",2*length(myData)),add=T,names.arg=myLabels,space=c(0,2),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) hoehe<-0.1*max(myData) j<-1 k<-j for (i in 1:length(myData)) {{ if (j > 1) k<-k+4 text(k+1.3,hoehe,format(round(x[2,i]),nsmall=0),cex=1.25,adj=0,xpd=T,col="white") j<-j+3 if (ix[1,i]) {{ tmp<-x[1,i]; x[1,i]<-y[1,i]; y[1,i]<-tmp myColours[(2*i)-1]<-"{low_color}" }} }} # Create chart and other elements barplot(x,beside=T,border=NA,col=myColours,space=c(0,2),axes=T,ylab="{y_name}",cex.lab={y_font_size},col.lab="{y_font_color}",col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size},fg="{y_scale_font_color}") barplot(y,beside=T,border=NA,col=rep("{color}",2*length(myData)),add=T,names.arg=myLabels,space=c(0,2),axes=F,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) hoehe<-0.1*max(myData) j<-1 k<-j for (i in 1:length(myData)) {{ if (j > 1) k<-k+4 text(k+1.3,hoehe,format(round(x[2,i]),nsmall=0),cex=1.25,adj=0,xpd=T,col="white") j<-j+3 if (i 2007) x<-ts(rev(gdp$jeworiginal),start=2008,frequency=4) pdf("{out_path}.pdf") par(omi=c(0.65,0.75,0.95,0.75),mai=c(0.9,0,0.25,0.02),fg="{x_scale_font_color}",bg="{background_color}",las=1) plot(x,type="n",axes=F,xlim=c(2008,2012),ylim=c(560,670),xlab="",ylab="") abline(v=c(2008:2012),col="{scale_line_color}",lty=1,lwd=1) lines(x,lwd=8,type="b",col=rgb({line_color},80,maxColorValue=255)) points(x,pch=19,cex=3,col=rgb({point_color},maxColorValue=255)) faktor<-rep(0.985,length(x)) for (i in 1:length(x)) {{ if (i>1 & ix[i-1] & x[i]>x[i+1]) {{ faktor[i]<-1.015 }} }} text((2008+i*0.25)-0.25,faktor[i]*x[i],x[i],col="{font_color}",cex={font_size}) }} axis(1,at=c(2008:2012),tck=0,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=NA,col.ticks="{y_scale_font_color}",lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.025,col.axis="{y_scale_font_color}") mtext("{title}",3,line=2.3,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=0,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{out_path}.png") par(omi=c(0.65,0.75,0.95,0.75),mai=c(0.9,0,0.25,0.02),fg="{x_scale_font_color}",bg="{background_color}",las=1) plot(x,type="n",axes=F,xlim=c(2008,2012),ylim=c(560,670),xlab="",ylab="") abline(v=c(2008:2012),col="{scale_line_color}",lty=1,lwd=1) lines(x,lwd=8,type="b",col=rgb({line_color},80,maxColorValue=255)) points(x,pch=19,cex=3,col=rgb({point_color},maxColorValue=255)) faktor<-rep(0.985,length(x)) for (i in 1:length(x)) {{ if (i>1 & ix[i-1] & x[i]>x[i+1]) {{ faktor[i]<-1.015 }} }} text((2008+i*0.25)-0.25,faktor[i]*x[i],x[i],col="{font_color}",cex={font_size}) }} axis(1,at=c(2008:2012),tck=0,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=NA,col.ticks="{y_scale_font_color}",lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.025,col.axis="{y_scale_font_color}") mtext("{title}",3,line=2.3,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=0,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(omi=c(0.65,0.75,0.95,0.75),mai=c(0.9,0,0.25,0.02),fg="{x_scale_font_color}",bg="{background_color}",las=1) plot(x,type="n",axes=F,xlim=c(2008,2012),ylim=c(560,670),xlab="",ylab="") abline(v=c(2008:2012),col="{scale_line_color}",lty=1,lwd=1) lines(x,lwd=8,type="b",col=rgb({line_color},80,maxColorValue=255)) points(x,pch=19,cex=3,col=rgb({point_color},maxColorValue=255)) faktor<-rep(0.985,length(x)) for (i in 1:length(x)) {{ if (i>1 & ix[i-1] & x[i]>x[i+1]) {{ faktor[i]<-1.015 }} }} text((2008+i*0.25)-0.25,faktor[i]*x[i],x[i],col="{font_color}",cex={font_size}) }} axis(1,at=c(2008:2012),tck=0,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=NA,col.ticks="{y_scale_font_color}",lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.025,col.axis="{y_scale_font_color}") mtext("{title}",3,line=2.3,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=0,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() svg("{out_path}.svg") par(omi=c(0.65,0.75,0.95,0.75),mai=c(0.9,0,0.25,0.02),fg="{x_scale_font_color}",bg="{background_color}",las=1) plot(x,type="n",axes=F,xlim=c(2008,2012),ylim=c(560,670),xlab="",ylab="") abline(v=c(2008:2012),col="{scale_line_color}",lty=1,lwd=1) lines(x,lwd=8,type="b",col=rgb({line_color},80,maxColorValue=255)) points(x,pch=19,cex=3,col=rgb({point_color},maxColorValue=255)) faktor<-rep(0.985,length(x)) for (i in 1:length(x)) {{ if (i>1 & ix[i-1] & x[i]>x[i+1]) {{ faktor[i]<-1.015 }} }} text((2008+i*0.25)-0.25,faktor[i]*x[i],x[i],col="{font_color}",cex={font_size}) }} axis(1,at=c(2008:2012),tck=0,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=NA,col.ticks="{y_scale_font_color}",lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.025,col.axis="{y_scale_font_color}") mtext("{title}",3,line=2.3,adj=0,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,line=0,adj=0,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.5,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, legend_1, legend_2, legend_size # 高级参数 legend_position, title_font_color, color_1, color_2, line_color # 示例文件 Radial_Polygons_Overlay.xlsx def Radial_Polygons_Overlay(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, legend_1, legend_2, legend_size, legend_position, title_font_color, color_1, color_2, line_color): color_1 = color_1[4:-1] color_2 = color_2[4:-1] code = f""" library(plotrix) library(gdata) myRegions <- read.xls("{file_path}", encoding="latin1") myRegions[,1]<-NULL myLabelling <- names(myRegions) myC1<-rgb({color_1},155,maxColorValue=255) myC2<-rgb({color_2},155,maxColorValue=255) pdf("{out_path}.pdf") par(omi=c(1,0.25,1,1),mai=c(0,2,0,0.5),cex.axis=1.5,cex.lab=1,xpd=T,las=1) # Create chart radial.plot(myRegions[2:3,],start=1,grid.left=T,labels=myLabelling,rp.type="p",main="",line.col=c(myC1,myC2),poly.col=c(myC1,myC2),show.grid=T,radial.lim=c(0,55),lwd=8,rad.col="{line_color}",grid.col="{line_color}") legend("{legend_position}",c("{legend_1}","{legend_2}"),pch=15,col=c(myC1,myC2),bty="n",cex={legend_size}) # Titling mtext(line=3,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=1,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=2,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() png("{out_path}.png") par(omi=c(1,0.25,1,1),mai=c(0,2,0,0.5),cex.axis=1.5,cex.lab=1,xpd=T,las=1) # Create chart radial.plot(myRegions[2:3,],start=1,grid.left=T,labels=myLabelling,rp.type="p",main="",line.col=c(myC1,myC2),poly.col=c(myC1,myC2),show.grid=T,radial.lim=c(0,55),lwd=8,rad.col="{line_color}",grid.col="{line_color}") legend("{legend_position}",c("{legend_1}","{legend_2}"),pch=15,col=c(myC1,myC2),bty="n",cex={legend_size}) # Titling mtext(line=3,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=1,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=2,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() svg("{out_path}.svg") par(omi=c(1,0.25,1,1),mai=c(0,2,0,0.5),cex.axis=1.5,cex.lab=1,xpd=T,las=1) # Create chart radial.plot(myRegions[2:3,],start=1,grid.left=T,labels=myLabelling,rp.type="p",main="",line.col=c(myC1,myC2),poly.col=c(myC1,myC2),show.grid=T,radial.lim=c(0,55),lwd=8,rad.col="{line_color}",grid.col="{line_color}") legend("{legend_position}",c("{legend_1}","{legend_2}"),pch=15,col=c(myC1,myC2),bty="n",cex={legend_size}) # Titling mtext(line=3,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=1,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=2,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(omi=c(1,0.25,1,1),mai=c(0,2,0,0.5),cex.axis=1.5,cex.lab=1,xpd=T,las=1) # Create chart radial.plot(myRegions[2:3,],start=1,grid.left=T,labels=myLabelling,rp.type="p",main="",line.col=c(myC1,myC2),poly.col=c(myC1,myC2),show.grid=T,radial.lim=c(0,55),lwd=8,rad.col="{line_color}",grid.col="{line_color}") legend("{legend_position}",c("{legend_1}","{legend_2}"),pch=15,col=c(myC1,myC2),bty="n",cex={legend_size}) # Titling mtext(line=3,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=1,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=2,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, annotation, annotation_size, deviations_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, annotation_color, color_1, color_2, deviations_color, mean_line_color # 示例文件 Scatter_Plot_Variant_2_Outliers_Highlighted.csv def Scatter_Plot_Variant_2_Outliers_Highlighted(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, annotation, annotation_size, deviations_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, annotation_color, color_1, color_2, deviations_color, mean_line_color): color_1 = color_1[4:-1] color_2 = color_2[4:-1] code = f""" library(gdata) myStructuralData<-read.csv(file="{file_path}",head=F,sep=";",dec=".") myData<-subset(myStructuralData,V2 > 0 & V34 > 10) attach(myData) myXDes<-"" myYDes<-"{y_name}" pdf("{out_path}.pdf") par(mar=c(4,4,0.5,2),omi=c(0.5,0.5,1,0),las=1) plot(type="n",xlab=myXDes,ylab=myYDes,V34,V21,xlim=c(10,26),ylim=c(-20,35),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,lwd.ticks=0.5,cex.axis={x_scale_font_size},tck=-0.015,col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.015,col.axis="{y_scale_font_color}",col="{y_scale_font_color}") myC1<-rgb({color_1},200,maxColorValue=255) myC2<-rgb({color_2},150,maxColorValue=255) fit<-lm(V21 ~ V34) myData$fit<-fitted(fit) points(V34,myData$fit,col=myC2,type="l",lwd=8) myData$resid<-residuals(fit) myData.sort<-myData[order(-abs(myData$resid)) ,] myData.sort_begin<-myData.sort[1:5,] myP1<-myData.sort[5+1:length(myData$fit),c("V34","V21")] myP2<-myData.sort_begin[c("V34","V21")] myR1<-sqrt(myData.sort$V6)/10 myR2<-sqrt(myData.sort_begin$V6)/10 symbols(myP1,circles=myR1,inches=0.3,bg=myC1,fg="white",add=T) symbols(myP2,circles=myR2,inches=0.3,bg=myC2,fg="white",add=T) text(myP2,iconv(as.matrix(myData.sort_begin["V3"]),"LATIN1","UTF-8"),cex={deviations_size},pos=3,offset=1.1,col="{deviations_color}") abline(v=mean(V34,na.rm=T),col="{mean_line_color}",lty=3) abline(h=mean(V21,na.rm=T),col="{mean_line_color}",lty=3) text(20,20, "{annotation}", adj=0,cex={annotation_size},col="{annotation_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=4,adj=1,cex={title_font_size}*0.4,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.52,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{out_path}.png") par(mar=c(4,4,0.5,2),omi=c(0.5,0.5,1,0),las=1) plot(type="n",xlab=myXDes,ylab=myYDes,V34,V21,xlim=c(10,26),ylim=c(-20,35),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,lwd.ticks=0.5,cex.axis={x_scale_font_size},tck=-0.015,col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.015,col.axis="{y_scale_font_color}",col="{y_scale_font_color}") myC1<-rgb({color_1},200,maxColorValue=255) myC2<-rgb({color_2},150,maxColorValue=255) fit<-lm(V21 ~ V34) myData$fit<-fitted(fit) points(V34,myData$fit,col=myC2,type="l",lwd=8) myData$resid<-residuals(fit) myData.sort<-myData[order(-abs(myData$resid)) ,] myData.sort_begin<-myData.sort[1:5,] myP1<-myData.sort[5+1:length(myData$fit),c("V34","V21")] myP2<-myData.sort_begin[c("V34","V21")] myR1<-sqrt(myData.sort$V6)/10 myR2<-sqrt(myData.sort_begin$V6)/10 symbols(myP1,circles=myR1,inches=0.3,bg=myC1,fg="white",add=T) symbols(myP2,circles=myR2,inches=0.3,bg=myC2,fg="white",add=T) text(myP2,iconv(as.matrix(myData.sort_begin["V3"]),"LATIN1","UTF-8"),cex={deviations_size},pos=3,offset=1.1,col="{deviations_color}") abline(v=mean(V34,na.rm=T),col="{mean_line_color}",lty=3) abline(h=mean(V21,na.rm=T),col="{mean_line_color}",lty=3) text(20,20, "{annotation}", adj=0,cex={annotation_size},col="{annotation_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=4,adj=1,cex={title_font_size}*0.4,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.52,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(mar=c(4,4,0.5,2),omi=c(0.5,0.5,1,0),las=1) plot(type="n",xlab=myXDes,ylab=myYDes,V34,V21,xlim=c(10,26),ylim=c(-20,35),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,lwd.ticks=0.5,cex.axis={x_scale_font_size},tck=-0.015,col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.015,col.axis="{y_scale_font_color}",col="{y_scale_font_color}") myC1<-rgb({color_1},200,maxColorValue=255) myC2<-rgb({color_2},150,maxColorValue=255) fit<-lm(V21 ~ V34) myData$fit<-fitted(fit) points(V34,myData$fit,col=myC2,type="l",lwd=8) myData$resid<-residuals(fit) myData.sort<-myData[order(-abs(myData$resid)) ,] myData.sort_begin<-myData.sort[1:5,] myP1<-myData.sort[5+1:length(myData$fit),c("V34","V21")] myP2<-myData.sort_begin[c("V34","V21")] myR1<-sqrt(myData.sort$V6)/10 myR2<-sqrt(myData.sort_begin$V6)/10 symbols(myP1,circles=myR1,inches=0.3,bg=myC1,fg="white",add=T) symbols(myP2,circles=myR2,inches=0.3,bg=myC2,fg="white",add=T) text(myP2,iconv(as.matrix(myData.sort_begin["V3"]),"LATIN1","UTF-8"),cex={deviations_size},pos=3,offset=1.1,col="{deviations_color}") abline(v=mean(V34,na.rm=T),col="{mean_line_color}",lty=3) abline(h=mean(V21,na.rm=T),col="{mean_line_color}",lty=3) text(20,20, "{annotation}", adj=0,cex={annotation_size},col="{annotation_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=4,adj=1,cex={title_font_size}*0.4,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.52,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() svg("{out_path}.svg") par(mar=c(4,4,0.5,2),omi=c(0.5,0.5,1,0),las=1) plot(type="n",xlab=myXDes,ylab=myYDes,V34,V21,xlim=c(10,26),ylim=c(-20,35),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,lwd.ticks=0.5,cex.axis={x_scale_font_size},tck=-0.015,col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,lwd.ticks=0.5,cex.axis={y_scale_font_size},tck=-0.015,col.axis="{y_scale_font_color}",col="{y_scale_font_color}") myC1<-rgb({color_1},200,maxColorValue=255) myC2<-rgb({color_2},150,maxColorValue=255) fit<-lm(V21 ~ V34) myData$fit<-fitted(fit) points(V34,myData$fit,col=myC2,type="l",lwd=8) myData$resid<-residuals(fit) myData.sort<-myData[order(-abs(myData$resid)) ,] myData.sort_begin<-myData.sort[1:5,] myP1<-myData.sort[5+1:length(myData$fit),c("V34","V21")] myP2<-myData.sort_begin[c("V34","V21")] myR1<-sqrt(myData.sort$V6)/10 myR2<-sqrt(myData.sort_begin$V6)/10 symbols(myP1,circles=myR1,inches=0.3,bg=myC1,fg="white",add=T) symbols(myP2,circles=myR2,inches=0.3,bg=myC2,fg="white",add=T) text(myP2,iconv(as.matrix(myData.sort_begin["V3"]),"LATIN1","UTF-8"),cex={deviations_size},pos=3,offset=1.1,col="{deviations_color}") abline(v=mean(V34,na.rm=T),col="{mean_line_color}",lty=3) abline(h=mean(V21,na.rm=T),col="{mean_line_color}",lty=3) text(20,20, "{annotation}", adj=0,cex={annotation_size},col="{annotation_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=4,adj=1,cex={title_font_size}*0.4,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1,adj=0.52,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, average, average_font_size, celebrities_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, average_line_color, celebrities_color, color_1, color_2, average_font_color # 示例文件 Scatter_Plot_Variant_3_Areas_Highlighted.xlsx def Scatter_Plot_Variant_3_Areas_Highlighted(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, average, average_font_size, celebrities_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, average_line_color, celebrities_color, color_1, color_2, average_font_color): code = f""" library(gdata) library(gdata) myPersons<-read.xls('{file_path}',encoding="latin1") names(myPersons) <- c("markings","name","s","group1","group2","group3","h","w","comment") attach(myPersons) myData<-subset(myPersons,w>0 & s=="m" & name!="Max Schmeling") attach(myData) pdf("{out_path}.pdf") par(mai=c(0.85,1,0.25,0.25),omi=c(1,0.5,1,0.5),las=1) plot(type="n",xlab="",ylab="{y_name}",h,w,xlim=c(160,220),ylim=c(50,125),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis={x_scale_font_size}) axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) myC1<-rgb(255,0,210,maxColorValue=255) myC2<-rgb(0,208,226,100,maxColorValue=255) myP1<-subset(myData[c("h","w")],w>20*(h/100*h/100) & w<25*(h/100*h/100)) myP2<-subset(myData[c("h","w")],w<20*(h/100*h/100)) myP3<-subset(myData[c("h","w")],w>25*(h/100*h/100)) myDes2<-as.matrix(subset(name,w<20*(h/100*h/100))) myDes3<-as.matrix(subset(name,w>25*(h/100*h/100))) symbols(myP1,bg='{color_1}',fg="white",circles=rep(1,nrow(myP1)),inches=0.25,add=T) symbols(myP2,bg='{color_2}',fg="white",circles=rep(1,nrow(myP2)),inches=0.25,add=T) symbols(myP3,bg='{color_2}',fg="white",circles=rep(1,nrow(myP3)),inches=0.25,add=T) text(myP2,myDes2,cex={celebrities_size},pos=1,offset=1.1,col="{celebrities_color}") text(myP3,myDes3,cex={celebrities_size},pos=3,offset=1.1,col="{celebrities_color}") curve(20*(x/100*x/100),xlim=c(160,220),add=T) curve(25*(x/100*x/100),xlim=c(160,220),add=T) abline(v=mean(h,na.rm=T),lty=3,col="{average_line_color}") abline(h=mean(w,na.rm=T),lty=3,col="{average_line_color}") text(182.5,52,"{average}",adj=0,font=3,cex={average_font_size},col="{average_font_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1.2,adj=0.535,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{out_path}.png",width=900,height=408) par(mai=c(0.85,1,0.25,0.25),omi=c(1,0.5,1,0.5),las=1) plot(type="n",xlab="",ylab="{y_name}",h,w,xlim=c(160,220),ylim=c(50,125),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis={x_scale_font_size}) axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) myC1<-rgb(255,0,210,maxColorValue=255) myC2<-rgb(0,208,226,100,maxColorValue=255) myP1<-subset(myData[c("h","w")],w>20*(h/100*h/100) & w<25*(h/100*h/100)) myP2<-subset(myData[c("h","w")],w<20*(h/100*h/100)) myP3<-subset(myData[c("h","w")],w>25*(h/100*h/100)) myDes2<-as.matrix(subset(name,w<20*(h/100*h/100))) myDes3<-as.matrix(subset(name,w>25*(h/100*h/100))) symbols(myP1,bg='{color_1}',fg="white",circles=rep(1,nrow(myP1)),inches=0.25,add=T) symbols(myP2,bg='{color_2}',fg="white",circles=rep(1,nrow(myP2)),inches=0.25,add=T) symbols(myP3,bg='{color_2}',fg="white",circles=rep(1,nrow(myP3)),inches=0.25,add=T) text(myP2,myDes2,cex={celebrities_size},pos=1,offset=1.1,col="{celebrities_color}") text(myP3,myDes3,cex={celebrities_size},pos=3,offset=1.1,col="{celebrities_color}") curve(20*(x/100*x/100),xlim=c(160,220),add=T) curve(25*(x/100*x/100),xlim=c(160,220),add=T) abline(v=mean(h,na.rm=T),lty=3,col="{average_line_color}") abline(h=mean(w,na.rm=T),lty=3,col="{average_line_color}") text(182.5,52,"{average}",adj=0,font=3,cex={average_font_size},col="{average_font_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1.2,adj=0.535,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(mai=c(0.85,1,0.25,0.25),omi=c(1,0.5,1,0.5),las=1) plot(type="n",xlab="",ylab="{y_name}",h,w,xlim=c(160,220),ylim=c(50,125),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis={x_scale_font_size}) axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) myC1<-rgb(255,0,210,maxColorValue=255) myC2<-rgb(0,208,226,100,maxColorValue=255) myP1<-subset(myData[c("h","w")],w>20*(h/100*h/100) & w<25*(h/100*h/100)) myP2<-subset(myData[c("h","w")],w<20*(h/100*h/100)) myP3<-subset(myData[c("h","w")],w>25*(h/100*h/100)) myDes2<-as.matrix(subset(name,w<20*(h/100*h/100))) myDes3<-as.matrix(subset(name,w>25*(h/100*h/100))) symbols(myP1,bg='{color_1}',fg="white",circles=rep(1,nrow(myP1)),inches=0.25,add=T) symbols(myP2,bg='{color_2}',fg="white",circles=rep(1,nrow(myP2)),inches=0.25,add=T) symbols(myP3,bg='{color_2}',fg="white",circles=rep(1,nrow(myP3)),inches=0.25,add=T) text(myP2,myDes2,cex={celebrities_size},pos=1,offset=1.1,col="{celebrities_color}") text(myP3,myDes3,cex={celebrities_size},pos=3,offset=1.1,col="{celebrities_color}") curve(20*(x/100*x/100),xlim=c(160,220),add=T) curve(25*(x/100*x/100),xlim=c(160,220),add=T) abline(v=mean(h,na.rm=T),lty=3,col="{average_line_color}") abline(h=mean(w,na.rm=T),lty=3,col="{average_line_color}") text(182.5,52,"{average}",adj=0,font=3,cex={average_font_size},col="{average_font_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1.2,adj=0.535,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() svg("{out_path}.svg") par(mai=c(0.85,1,0.25,0.25),omi=c(1,0.5,1,0.5),las=1) plot(type="n",xlab="",ylab="{y_name}",h,w,xlim=c(160,220),ylim=c(50,125),axes=F,cex.lab={y_font_size},col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis={x_scale_font_size}) axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) myC1<-rgb(255,0,210,maxColorValue=255) myC2<-rgb(0,208,226,100,maxColorValue=255) myP1<-subset(myData[c("h","w")],w>20*(h/100*h/100) & w<25*(h/100*h/100)) myP2<-subset(myData[c("h","w")],w<20*(h/100*h/100)) myP3<-subset(myData[c("h","w")],w>25*(h/100*h/100)) myDes2<-as.matrix(subset(name,w<20*(h/100*h/100))) myDes3<-as.matrix(subset(name,w>25*(h/100*h/100))) symbols(myP1,bg='{color_1}',fg="white",circles=rep(1,nrow(myP1)),inches=0.25,add=T) symbols(myP2,bg='{color_2}',fg="white",circles=rep(1,nrow(myP2)),inches=0.25,add=T) symbols(myP3,bg='{color_2}',fg="white",circles=rep(1,nrow(myP3)),inches=0.25,add=T) text(myP2,myDes2,cex={celebrities_size},pos=1,offset=1.1,col="{celebrities_color}") text(myP3,myDes3,cex={celebrities_size},pos=3,offset=1.1,col="{celebrities_color}") curve(20*(x/100*x/100),xlim=c(160,220),add=T) curve(25*(x/100*x/100),xlim=c(160,220),add=T) abline(v=mean(h,na.rm=T),lty=3,col="{average_line_color}") abline(h=mean(w,na.rm=T),lty=3,col="{average_line_color}") text(182.5,52,"{average}",adj=0,font=3,cex={average_font_size},col="{average_font_color}") mtext("{title}",3,adj=0,line=2,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=0,cex={title_font_size}*0.6,outer=T,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=1,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") mtext("{x_name}",1,line=-1.2,adj=0.535,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, font_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, font_color, line_color, color # 示例文件 Scatter_Plot_Variant_5_Connected_Points.xlsx def Scatter_Plot_Variant_5_Connected_Points(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, font_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, font_color, line_color, color): code = f""" library(gdata) myData<-read.xls('{file_path}',encoding="latin1") names(myData) <- c("Year","GDP","LEXP") myData<-myData[myData$Year>=1985, ] attach(myData) n<-nrow(myData) grGDP<-vector() grLEXP<-vector() for (i in 2:n) {{ grGDP[i]<-(GDP[i]-GDP[i-1])/GDP[i-1] grLEXP[i]<-(LEXP[i]-LEXP[i-1])/LEXP[i-1] }} myData$grGDP<-grGDP*100 myData$grLEXP<-grLEXP*100 myData<-myData[2:n, ] n<-nrow(myData) t <- 1:n ts <- seq(1, n, by = 1/10) xs <- splinefun(t, myData$grGDP)(ts) ys <- splinefun(t, myData$grLEXP)(ts) pdf("{out_path}.pdf") par(mai=c(1.1,1.25,0.15,0),omi=c(1,0.5,1,0.5), mgp=c(4.5,1,0),las=1) plot(myData$grGDP, myData$grLEXP, type="n", xlab="", ylab="{y_name}", cex.lab={y_font_size}, axes=F, col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}") lines(xs, ys,lwd=7,col="{line_color}") for (i in 1:n) {{ symbols(myData$grGDP[i],myData$grLEXP[i],bg="{color}",fg="{font_color}",circles=1,inches=0.25,add=T) text(myData$grGDP[i],myData$grLEXP[i], myData$Year[i],col="{font_color}",cex={font_size}) }} mtext("{title}",3,adj=0,line=1.5,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=-0.25,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1.05,adj=0.57,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{out_path}.png") par(mai=c(1.1,1.25,0.15,0),omi=c(1,0.5,1,0.5), mgp=c(4.5,1,0),las=1) plot(myData$grGDP, myData$grLEXP, type="n", xlab="", ylab="{y_name}", cex.lab={y_font_size}, axes=F, col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}") lines(xs, ys,lwd=7,col="{line_color}") for (i in 1:n) {{ symbols(myData$grGDP[i],myData$grLEXP[i],bg="{color}",fg="{font_color}",circles=1,inches=0.25,add=T) text(myData$grGDP[i],myData$grLEXP[i], myData$Year[i],col="{font_color}",cex={font_size}) }} mtext("{title}",3,adj=0,line=1.5,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=-0.25,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1.05,adj=0.57,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(mai=c(1.1,1.25,0.15,0),omi=c(1,0.5,1,0.5), mgp=c(4.5,1,0),las=1) plot(myData$grGDP, myData$grLEXP, type="n", xlab="", ylab="{y_name}", cex.lab={y_font_size}, axes=F, col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}") lines(xs, ys,lwd=7,col="{line_color}") for (i in 1:n) {{ symbols(myData$grGDP[i],myData$grLEXP[i],bg="{color}",fg="{font_color}",circles=1,inches=0.25,add=T) text(myData$grGDP[i],myData$grLEXP[i], myData$Year[i],col="{font_color}",cex={font_size}) }} mtext("{title}",3,adj=0,line=1.5,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=-0.25,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1.05,adj=0.57,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() svg("{out_path}.svg") par(mai=c(1.1,1.25,0.15,0),omi=c(1,0.5,1,0.5), mgp=c(4.5,1,0),las=1) plot(myData$grGDP, myData$grLEXP, type="n", xlab="", ylab="{y_name}", cex.lab={y_font_size}, axes=F, col.lab="{y_font_color}") axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}") lines(xs, ys,lwd=7,col="{line_color}") for (i in 1:n) {{ symbols(myData$grGDP[i],myData$grLEXP[i],bg="{color}",fg="{font_color}",circles=1,inches=0.25,add=T) text(myData$grGDP[i],myData$grLEXP[i], myData$Year[i],col="{font_color}",cex={font_size}) }} mtext("{title}",3,adj=0,line=1.5,cex={title_font_size},outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=-0.25,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext("{caption}",1,line=2,adj=1,cex={title_font_size}*0.4,font=3,outer=T,col="{title_font_color}") mtext("{x_name}",1,line=-1.05,adj=0.57,cex={x_font_size},font=3,outer=T,col="{x_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, font_size, character, time_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, font_color, time_color # 示例文件 Scatter_Plot_With_User_Defined_Symbols.xlsx def Scatter_Plot_With_User_Defined_Symbols(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, font_size, character, time_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, font_color, time_color): code = f""" library(maptools) library(gdata) myData<-read.xls("{file_path}", encoding="latin1") names(myData) <- c("WarNum","WarName","WarType","CcodeA","SideA","CcodeB","SideB","Intnl","StartMonth1","StartDay1","StartYear1","EndMonth1","EndDay1","EndYear1","StartMonth2","StartDay2","StartYear2","EndMonth2","EndDay2","EndYear2","TransFrom","WhereFought","Initiator","Outcome","TransTo","SideADeaths","SideBDeaths","Version") mySelection<-subset(myData, myData$StartYear1>=1995 & myData$SideADeaths > 0 & myData$SideADeaths < 2000 & myData$SideBDeaths > 0 & myData$SideBDeaths < 4000) attach(mySelection) myColour<-"{font_color}" myN<-nrow(mySelection) h<-rep(0, myN) v<-rep(0, myN) myOffset<-cbind(h, v) mySelection[, c("WarName", "StartYear1", "SideADeaths", "SideBDeaths")] myOffset[1, "h"]<--400 myOffset[5, "h"]<-232 myOffset[4, "h"]<--275 myOffset[2, "h"]<-270; myOffset[2, "v"]<-100; myOffset[13, "h"]<--275 myOffset[12, "h"]<--300 myX<-as.numeric(SideADeaths) myY<-as.numeric(SideBDeaths) pdf("{out_path}.pdf") par(omi=c(0.5,0.5,0,0),mai=c(0.5,1.25,0,0.25),las=1) plot(myX, myY, typ="n", xlab="", ylab="", axes=F, xlim=c(0, 2000), ylim=c(0, 4000)) axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis="{x_scale_font_size}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis="{y_scale_font_size}") text(myX+130+myOffset[, "h"], myY-180+myOffset[, "v"], paste(WarName, StartYear1, sep=" "), cex={time_size}, xpd=T, col="{time_color}") mtext(side=1, "{x_name}", adj=0.5, line=3, cex={x_font_size}, col="{x_font_color}") mtext(side=2, "{y_name}", las=0, adj=0.5, line=4, cex={y_font_size}, col="{y_font_color}") mtext("{title}",3,adj=1,line=-3,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,adj=1,line=-5,cex={title_font_size}*0.6,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") text(myX, myY, "{character}", col=myColour, cex={font_size}, xpd=T) dev.off() png("{out_path}.png") par(omi=c(0.5,0.5,0,0),mai=c(0.5,1.25,0,0.25),las=1) plot(myX, myY, typ="n", xlab="", ylab="", axes=F, xlim=c(0, 2000), ylim=c(0, 4000)) axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis="{x_scale_font_size}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis="{y_scale_font_size}") text(myX+130+myOffset[, "h"], myY-180+myOffset[, "v"], paste(WarName, StartYear1, sep=" "), cex={time_size}, xpd=T, col="{time_color}") mtext(side=1, "{x_name}", adj=0.5, line=3, cex={x_font_size}, col="{x_font_color}") mtext(side=2, "{y_name}", las=0, adj=0.5, line=4, cex={y_font_size}, col="{y_font_color}") mtext("{title}",3,adj=1,line=-3,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,adj=1,line=-5,cex={title_font_size}*0.6,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") text(myX, myY, "{character}", col=myColour, cex={font_size}, xpd=T) dev.off() png("{char_out_path}",width=900,height=540) par(omi=c(0.5,0.5,0,0),mai=c(0.5,1.25,0,0.25),las=1) plot(myX, myY, typ="n", xlab="", ylab="", axes=F, xlim=c(0, 2000), ylim=c(0, 4000)) axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis="{x_scale_font_size}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis="{y_scale_font_size}") text(myX+130+myOffset[, "h"], myY-180+myOffset[, "v"], paste(WarName, StartYear1, sep=" "), cex={time_size}, xpd=T, col="{time_color}") mtext(side=1, "{x_name}", adj=0.5, line=3, cex={x_font_size}, col="{x_font_color}") mtext(side=2, "{y_name}", las=0, adj=0.5, line=4, cex={y_font_size}, col="{y_font_color}") mtext("{title}",3,adj=1,line=-3,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,adj=1,line=-5,cex={title_font_size}*0.6,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") text(myX, myY, "{character}", col=myColour, cex={font_size}, xpd=T) dev.off() svg("{out_path}.svg") par(omi=c(0.5,0.5,0,0),mai=c(0.5,1.25,0,0.25),las=1) plot(myX, myY, typ="n", xlab="", ylab="", axes=F, xlim=c(0, 2000), ylim=c(0, 4000)) axis(1,col=par("bg"),col.ticks="{x_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{x_scale_font_color}",cex.axis="{x_scale_font_size}") axis(2,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis="{y_scale_font_size}") text(myX+130+myOffset[, "h"], myY-180+myOffset[, "v"], paste(WarName, StartYear1, sep=" "), cex={time_size}, xpd=T, col="{time_color}") mtext(side=1, "{x_name}", adj=0.5, line=3, cex={x_font_size}, col="{x_font_color}") mtext(side=2, "{y_name}", las=0, adj=0.5, line=4, cex={y_font_size}, col="{y_font_color}") mtext("{title}",3,adj=1,line=-3,cex={title_font_size},col="{title_font_color}") mtext("{subtitle}",3,adj=1,line=-5,cex={title_font_size}*0.6,font=3,col="{title_font_color}") mtext("{caption}",1,line=1,adj=0,cex={title_font_size}*0.4,outer=T,font=3,col="{title_font_color}") text(myX, myY, "{character}", col=myColour, cex={font_size}, xpd=T) dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, annotation, number_size # 高级参数 title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, number_font_color, color_1, color_2, color_3, line_color # 示例文件 Scatter_Plot_with_Few_Points.csv def Scatter_Plot_with_Few_Points(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, annotation, number_size, title_font_color, x_font_color, x_scale_font_color, y_font_color, y_scale_font_color, number_font_color, color_1, color_2, color_3, line_color): color_1 = color_1[4:-1] color_2 = color_2[4:-1] color_3 = color_3[4:-1] code = f""" datas <- read.csv("{file_path}", header = FALSE) myValue <- datas[,1] myRevenue <- datas[,2] myProfit <- datas[,3] myC1<-rgb({color_2},maxColorValue=255) myC2<-rgb({color_3},maxColorValue=255) myC3<-"grey" myC4<-rgb({color_1},maxColorValue=255) names<-c("BMW:\n44,6 Bn.","Daimler:\n45,5 Bn.","","Facebook:\n75-100 Bn.") pdf("{out_path}.pdf") dev.off() png("{out_path}.png") par(mai=c(2,1,1,1),omi=c(0,0,0,0),xpd=T,las=1) plot(myRevenue,myProfit,axes=F,type="n",xlab="",ylab="{y_name}",xlim=c(-20,100),ylim=c(-1,6),cex.lab={y_font_size},col.lab="{y_font_color}") for (i in 1:3) {{ arrows(myRevenue[i],-1,myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") arrows(-20,myProfit[i],myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") }} points(myRevenue,myProfit,pch=19,cex=myValue/2.6,col=c(myC1,myC2,myC3,myC4)) text(myRevenue,myProfit,names,col="{number_font_color}",cex={number_size}) axis(1,at=c(2.5,60.5,97.8),labels=c("2.5*","60.5","97.8"),cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,at=c(1,4.8),labels=c("1.0","4.8\n4.7"),cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}",col="{y_scale_font_color}") text(-25.5,5.08,"**",col="{y_scale_font_color}") text(-26.5,1.08,"*",col="{y_scale_font_color}") mtext(line=1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=6.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") mtext(side=1,line=4.5,"{annotation}",cex={title_font_size}*0.6,adj=0,col="{title_font_color}") mtext("{x_name}",1,3,adj=0.5,cex={x_font_size},col="{x_font_color}") par(mai=c(2,1,1,1),omi=c(0,0,0,0),xpd=T,las=1) plot(myRevenue,myProfit,axes=F,type="n",xlab="",ylab="{y_name}",xlim=c(-20,100),ylim=c(-1,6),cex.lab={y_font_size},col.lab="{y_font_color}") for (i in 1:3) {{ arrows(myRevenue[i],-1,myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") arrows(-20,myProfit[i],myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") }} points(myRevenue,myProfit,pch=19,cex=myValue/2.6,col=c(myC1,myC2,myC3,myC4)) text(myRevenue,myProfit,names,col="{number_font_color}",cex={number_size}) axis(1,at=c(2.5,60.5,97.8),labels=c("2.5*","60.5","97.8"),cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,at=c(1,4.8),labels=c("1.0","4.8\n4.7"),cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}",col="{y_scale_font_color}") text(-25.5,5.08,"**",col="{y_scale_font_color}") text(-26.5,1.08,"*",col="{y_scale_font_color}") mtext(line=1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=6.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") mtext(side=1,line=4.5,"{annotation}",cex={title_font_size}*0.6,adj=0,col="{title_font_color}") mtext("{x_name}",1,3,adj=0.5,cex={x_font_size},col="{x_font_color}") dev.off() png("{char_out_path}",width=900,height=540) par(mai=c(2,1,1,1),omi=c(0,0,0,0),xpd=T,las=1) plot(myRevenue,myProfit,axes=F,type="n",xlab="",ylab="{y_name}",xlim=c(-20,100),ylim=c(-1,6),cex.lab={y_font_size},col.lab="{y_font_color}") for (i in 1:3) {{ arrows(myRevenue[i],-1,myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") arrows(-20,myProfit[i],myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") }} points(myRevenue,myProfit,pch=19,cex=myValue/2.6,col=c(myC1,myC2,myC3,myC4)) text(myRevenue,myProfit,names,col="{number_font_color}",cex={number_size}) axis(1,at=c(2.5,60.5,97.8),labels=c("2.5*","60.5","97.8"),cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,at=c(1,4.8),labels=c("1.0","4.8\n4.7"),cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}",col="{y_scale_font_color}") text(-25.5,5.08,"**",col="{y_scale_font_color}") text(-26.5,1.08,"*",col="{y_scale_font_color}") mtext(line=1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=6.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") mtext(side=1,line=4.5,"{annotation}",cex={title_font_size}*0.6,adj=0,col="{title_font_color}") mtext("{x_name}",1,3,adj=0.5,cex={x_font_size},col="{x_font_color}") dev.off() svg("{out_path}.svg") par(mai=c(2,1,1,1),omi=c(0,0,0,0),xpd=T,las=1) plot(myRevenue,myProfit,axes=F,type="n",xlab="",ylab="{y_name}",xlim=c(-20,100),ylim=c(-1,6),cex.lab={y_font_size},col.lab="{y_font_color}") for (i in 1:3) {{ arrows(myRevenue[i],-1,myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") arrows(-20,myProfit[i],myRevenue[i],myProfit[i],length=0.10,lty="dotted",angle=10,code=0,lwd=1,col="{line_color}") }} points(myRevenue,myProfit,pch=19,cex=myValue/2.6,col=c(myC1,myC2,myC3,myC4)) text(myRevenue,myProfit,names,col="{number_font_color}",cex={number_size}) axis(1,at=c(2.5,60.5,97.8),labels=c("2.5*","60.5","97.8"),cex.axis={x_scale_font_size},col.axis="{x_scale_font_color}",col="{x_scale_font_color}") axis(2,at=c(1,4.8),labels=c("1.0","4.8\n4.7"),cex.axis={y_scale_font_size},col.axis="{y_scale_font_color}",col="{y_scale_font_color}") text(-25.5,5.08,"**",col="{y_scale_font_color}") text(-26.5,1.08,"*",col="{y_scale_font_color}") mtext(line=1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=6.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") mtext(side=1,line=4.5,"{annotation}",cex={title_font_size}*0.6,adj=0,col="{title_font_color}") mtext("{x_name}",1,3,adj=0.5,cex={x_font_size},col="{x_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, title_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, name_1, name_2 # 高级参数 title_font_color, x_scale_font_color, y_font_color, y_scale_font_color, color_1, color_2, name_color # 示例文件 Seasonal_Ranges_Panel.xlsx def Seasonal_Ranges_Panel(file_path, char_out_path, out_path, title, caption, title_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, name_1, name_2, title_font_color, x_scale_font_color, y_font_color, y_scale_font_color, color_1, color_2, name_font_size, name_color): code = f""" library(gplots) library(gdata) myData<-read.xls('{file_path}', encoding="latin1") attach(myData) myLines<-c(-5,0,5,10,15,20,25,30) pdf("{out_path}.pdf") par(omi=c(0.25,0.25,0.5,0.25),mai=c(0.45,0.35,0.5,0),mfcol=c(1,2),las=1) myT1<-barplot2(t(cbind(NY_min,NY_max-NY_min)),col=c(NA,"{color_1}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") for (i in 1:length(myLines)) {{text(-0.8,myLines[i]+1.1,myLines[i],xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size})}} text(0.25,33,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") mtext(side=3,"{name_1}",cex={name_font_size},col="{name_color}") myT2<-barplot2(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c(NA,"{color_2}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") mtext(side=3,"{name_2}",cex={name_font_size},col="{name_color}") mtext(side=3,"{title}",cex={title_font_size},outer=T,col="{title_font_color}") mtext(side=1,"{caption}",line=-0.4,cex={title_font_size}*0.6,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() png("{out_path}.png") par(omi=c(0.25,0.25,0.5,0.25),mai=c(0.45,0.35,0.5,0),mfcol=c(1,2),las=1) myT1<-barplot2(t(cbind(NY_min,NY_max-NY_min)),col=c(NA,"{color_1}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") for (i in 1:length(myLines)) {{text(-0.8,myLines[i]+1.1,myLines[i],xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size})}} text(0.25,33,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") mtext(side=3,"{name_1}",cex={name_font_size},col="{name_color}") myT2<-barplot2(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c(NA,"{color_2}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") mtext(side=3,"{name_2}",cex={name_font_size},col="{name_color}") mtext(side=3,"{title}",cex={title_font_size},outer=T,col="{title_font_color}") mtext(side=1,"{caption}",line=-0.4,cex={title_font_size}*0.6,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() png("{char_out_path}",width=900,height=408) par(omi=c(0.25,0.25,0.5,0.25),mai=c(0.45,0.35,0.5,0),mfcol=c(1,2),las=1) myT1<-barplot2(t(cbind(NY_min,NY_max-NY_min)),col=c(NA,"{color_1}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") for (i in 1:length(myLines)) {{text(-0.8,myLines[i]+1.1,myLines[i],xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size})}} text(0.25,33,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") mtext(side=3,"{name_1}",cex={name_font_size},col="{name_color}") myT2<-barplot2(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c(NA,"{color_2}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") mtext(side=3,"{name_2}",cex={name_font_size},col="{name_color}") mtext(side=3,"{title}",cex={title_font_size},outer=T,col="{title_font_color}") mtext(side=1,"{caption}",line=-0.4,cex={title_font_size}*0.6,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() svg("{out_path}.svg") par(omi=c(0.25,0.25,0.5,0.25),mai=c(0.45,0.35,0.5,0),mfcol=c(1,2),las=1) myT1<-barplot2(t(cbind(NY_min,NY_max-NY_min)),col=c(NA,"{color_1}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") for (i in 1:length(myLines)) {{text(-0.8,myLines[i]+1.1,myLines[i],xpd=T,col="{y_scale_font_color}",cex={y_scale_font_size})}} text(0.25,33,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") mtext(side=3,"{name_1}",cex={name_font_size},col="{name_color}") myT2<-barplot2(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c(NA,"{color_2}"),border=NA,names.arg=Month,ylim=c(-5,35),panel.first=abline(h=myLines,col="grey",lwd=1,lty="dotted"),axes=F,cex.names="{x_scale_font_size}",col.axis="{x_scale_font_color}") mtext(side=3,"{name_2}",cex={name_font_size},col="{name_color}") mtext(side=3,"{title}",cex={title_font_size},outer=T,col="{title_font_color}") mtext(side=1,"{caption}",line=-0.4,cex={title_font_size}*0.6,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, legend_1, legend_2, legend_size # 高级参数 title_font_color, x_scale_font_color, y_font_color, y_scale_font_color, color_1, color_2, line_color, legend_color # 示例文件 Seasonal_Ranges_Stacked.xlsx def Seasonal_Ranges_Stacked(file_path, char_out_path, out_path, title, caption, subtitle, title_font_size, x_scale_font_size, y_name, y_font_size, y_scale_font_size, legend_1, legend_2, legend_size, title_font_color, x_scale_font_color, y_font_color, y_scale_font_color, color_1, color_2, line_color, legend_color): code = f""" library(gdata) myData<-read.xls('{file_path}',encoding="latin1") names(myData) <- c("Month","NY_min","NY_max","MAJ_min","MAJ_max") myLines<-c(-5,0,5,10,15,20,25,30) attach(myData) pdf("{out_path}.pdf") par(omi=c(0.25,0,0.75,0.25),mai=c(0.5,2,0.5,2),las=1) myT1<-barplot(t(cbind(NY_min,NY_max-NY_min)),col=c("white","{color_2}"),border=NA,ylim=c(-5,35),axes=F,axisnames=F) myT2<-barplot(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c("white","{color_1}"),border=NA,add=T,axes=F,names.arg=Month,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) axis(2,at=myLines,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) abline(h=myLines,col="white",lwd=2) abline(v=seq(2.5,28.8,by=2.4),col="{line_color}") text(-0.95,34,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") legend(18,18,c("{legend_2}","{legend_1}"),col=c("{color_2}","{color_1}"),pch=15,bty="n",xjust=1,cex={legend_size},pt.cex={legend_size},xpd=T,text.col="{legend_color}") mtext(side=3,"{title}",cex={title_font_size},adj=0.1,outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=-0.25,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext(side=1,line=-1,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() png("{out_path}.png") par(omi=c(0.25,0,0.75,0.25),mai=c(0.5,2,0.5,2),las=1) myT1<-barplot(t(cbind(NY_min,NY_max-NY_min)),col=c("white","{color_2}"),border=NA,ylim=c(-5,35),axes=F,axisnames=F) myT2<-barplot(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c("white","{color_1}"),border=NA,add=T,axes=F,names.arg=Month,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) axis(2,at=myLines,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) abline(h=myLines,col="white",lwd=2) abline(v=seq(2.5,28.8,by=2.4),col="{line_color}") text(-0.95,34,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") legend(18,18,c("{legend_2}","{legend_1}"),col=c("{color_2}","{color_1}"),pch=15,bty="n",xjust=1,cex={legend_size},pt.cex={legend_size},xpd=T,text.col="{legend_color}") mtext(side=3,"{title}",cex={title_font_size},adj=0.1,outer=T,col="{title_font_color}") mtext("{subtitle}",3,adj=0,line=-0.25,cex={title_font_size}*0.6,font=3,outer=T,col="{title_font_color}") mtext(side=1,line=-1,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() png("{char_out_path}",width=900,height=408) par(omi=c(0.25,0,0.75,0.25),mai=c(0.5,2,0.5,2),las=1) myT1<-barplot(t(cbind(NY_min,NY_max-NY_min)),col=c("white","{color_2}"),border=NA,ylim=c(-5,35),axes=F,axisnames=F) myT2<-barplot(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c("white","{color_1}"),border=NA,add=T,axes=F,names.arg=Month,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) axis(2,at=myLines,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) abline(h=myLines,col="white",lwd=2) abline(v=seq(2.5,28.8,by=2.4),col="{line_color}") text(-0.95,34,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") legend(18,18,c("{legend_2}","{legend_1}"),col=c("{color_2}","{color_1}"),pch=15,bty="n",xjust=1,cex={legend_size},pt.cex={legend_size},xpd=T,text.col="{legend_color}") mtext(side=3,"{title}",cex={title_font_size},adj=0.1,outer=T,col="{title_font_color}") mtext(side=1,line=-1,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() svg("{out_path}.svg") par(omi=c(0.25,0,0.75,0.25),mai=c(0.5,2,0.5,2),las=1) myT1<-barplot(t(cbind(NY_min,NY_max-NY_min)),col=c("white","{color_2}"),border=NA,ylim=c(-5,35),axes=F,axisnames=F) myT2<-barplot(t(cbind(MAJ_min,MAJ_max-MAJ_min)),col=c("white","{color_1}"),border=NA,add=T,axes=F,names.arg=Month,col.axis="{x_scale_font_color}",cex.names={x_scale_font_size}) axis(2,at=myLines,col=par("bg"),col.ticks="{y_scale_font_color}",lwd.ticks=0.5,tck=-0.025,col.axis="{y_scale_font_color}",cex.axis={y_scale_font_size}) abline(h=myLines,col="white",lwd=2) abline(v=seq(2.5,28.8,by=2.4),col="{line_color}") text(-0.95,34,"{y_name}",xpd=T,cex={y_font_size},col="{y_font_color}") legend(18,18,c("{legend_2}","{legend_1}"),col=c("{color_2}","{color_1}"),pch=15,bty="n",xjust=1,cex={legend_size},pt.cex={legend_size},xpd=T,text.col="{legend_color}") mtext(side=3,"{title}",cex={title_font_size},adj=0.1,outer=T,col="{title_font_color}") mtext(side=1,line=-1,"{caption}",cex={title_font_size}*0.4,adj=1,font=3,outer=T,col="{title_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system( f"Rscript {out_path}.R") # 基础参数 file_path, char_out_path, out_path, title, caption, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, heading_font_size, date_size, percent_size, main_size, font_size # 高级参数 font_color, x_font_color, x_scale_font_color, y_font_color, heading_font_color, line_color, title_font_color, date_color, percent_color, main_color # 示例文件 Simplified_Gantt_Chart.xlsx def Simplified_Gantt_Chart(file_path, char_out_path, out_path, title, caption, title_font_size, x_name, x_font_size, x_scale_font_size, y_name, y_font_size, heading_font_size, date_size, percent_size, main_size, font_size, font_color, x_font_color, x_scale_font_color, y_font_color, heading_font_color, line_color, title_font_color, date_color, percent_color, main_color): y_name = "\n".join(y_name) code = f""" library(gdata) mySchedule<-read.xls('{file_path}',encoding="latin1") names(mySchedule) <- c("Milestone","when","Group","what","from","to","Durance","who","done","PAN","PAG","AG_from","AG_to","Persons") c0<-"black"; c1<-"green"; c2<-"red"; c3<-"blue"; c4<-"orange"; c5<-"brown" myColour_done<-"grey" myColour<-c(c0,c1,c1,c1,c0,c0,c2,c2,c2,c2,c0,c0,c3,c3,c3,c0,c0,c4,c4,c4,c0,c0,c5) n<-nrow(mySchedule) myScheduleData<-subset(mySchedule,nchar(as.character(mySchedule$from))>0) myBegin<-min(as.Date(as.matrix(myScheduleData[,c('from','to')]))) myEnd<-max(as.Date(as.matrix(myScheduleData[,c('from','to')]))) attach(mySchedule) pdf("{out_path}.pdf") par(lend=1,omi=c(0.25,1,1,0.25),mai=c(1,1.85,0.25,2.75),las=1) plot(from,1:n,type="n",xlab="{x_name}",ylab="",axes=F,xlim=c(myBegin,myEnd),ylim=c(n,1), col.lab="{x_font_color}",cex.lab={x_font_size}) for (i in 1:n) {{ if (nchar(as.character(Group[i]))>0) {{ text(myBegin-2,i,Group[i],adj=1,xpd=T,cex={heading_font_size},col="{heading_font_color}") }} else if (nchar(as.character(what[i]))>0) {{ x1<-as.Date(mySchedule[i,'from']) x2<-as.Date(mySchedule[i,'to']) x3<-x1+((x2-x1)*mySchedule[i,'done']/100) x<-c(x1,x2) x_done<-c(x1,x3) y<-c(i,i) segments(myBegin, i, myEnd, i, col="{line_color}") lines(x,y,lwd=20,col=myColour[i]) points(myEnd+90,i,cex=(mySchedule[i,'Persons']*mySchedule[i,'Durance'])**0.5,pch=19,col=rgb(110,110,110,50,maxColorValue=255),xpd=T) if (x3-x1>1) lines(x_done,y,lwd=20,col=myColour_done) if (mySchedule[i,'PAG'] > 0) {{ x4<-as.Date(mySchedule[i,'AG_from']) x5<-as.Date(mySchedule[i,'AG_to']) x_ag<-c(x4,x5) rect(x4,i-0.75,x5,i+0.75,lwd=2) }} text(myBegin-2,i,what[i],adj=1,xpd=T,cex={main_size},col="{main_color}") text(myEnd+25,i,paste(done[i],"%",sep=" "),adj=1,xpd=T,cex={percent_size},col="{percent_color}") text(myEnd+35,i,paste(format(x1,format="%d/%m/%y"),"-",format(x2,format="%d/%m/%y"),sep=" "),adj=0,xpd=T,cex={date_size},col="{date_color}") }} else # Milestone {{ x3<-as.Date(mySchedule[i,'when']) myHalf<-(myEnd-myBegin)/2 if (x3-x10) {{ text(myBegin-2,i,Group[i],adj=1,xpd=T,cex={heading_font_size},col="{heading_font_color}") }} else if (nchar(as.character(what[i]))>0) {{ x1<-as.Date(mySchedule[i,'from']) x2<-as.Date(mySchedule[i,'to']) x3<-x1+((x2-x1)*mySchedule[i,'done']/100) x<-c(x1,x2) x_done<-c(x1,x3) y<-c(i,i) segments(myBegin, i, myEnd, i, col="{line_color}") lines(x,y,lwd=20,col=myColour[i]) points(myEnd+90,i,cex=(mySchedule[i,'Persons']*mySchedule[i,'Durance'])**0.5,pch=19,col=rgb(110,110,110,50,maxColorValue=255),xpd=T) if (x3-x1>1) lines(x_done,y,lwd=20,col=myColour_done) if (mySchedule[i,'PAG'] > 0) {{ x4<-as.Date(mySchedule[i,'AG_from']) x5<-as.Date(mySchedule[i,'AG_to']) x_ag<-c(x4,x5) rect(x4,i-0.75,x5,i+0.75,lwd=2) }} text(myBegin-2,i,what[i],adj=1,xpd=T,cex={main_size},col="{main_color}") text(myEnd+25,i,paste(done[i],"%",sep=" "),adj=1,xpd=T,cex={percent_size},col="{percent_color}") text(myEnd+35,i,paste(format(x1,format="%d/%m/%y"),"-",format(x2,format="%d/%m/%y"),sep=" "),adj=0,xpd=T,cex={date_size},col="{date_color}") }} else # Milestone {{ x3<-as.Date(mySchedule[i,'when']) myHalf<-(myEnd-myBegin)/2 if (x3-x10) {{ text(myBegin-2,i,Group[i],adj=1,xpd=T,cex={heading_font_size},col="{heading_font_color}") }} else if (nchar(as.character(what[i]))>0) {{ x1<-as.Date(mySchedule[i,'from']) x2<-as.Date(mySchedule[i,'to']) x3<-x1+((x2-x1)*mySchedule[i,'done']/100) x<-c(x1,x2) x_done<-c(x1,x3) y<-c(i,i) segments(myBegin, i, myEnd, i, col="{line_color}") lines(x,y,lwd=20,col=myColour[i]) points(myEnd+90,i,cex=(mySchedule[i,'Persons']*mySchedule[i,'Durance'])**0.5,pch=19,col=rgb(110,110,110,50,maxColorValue=255),xpd=T) if (x3-x1>1) lines(x_done,y,lwd=20,col=myColour_done) if (mySchedule[i,'PAG'] > 0) {{ x4<-as.Date(mySchedule[i,'AG_from']) x5<-as.Date(mySchedule[i,'AG_to']) x_ag<-c(x4,x5) rect(x4,i-0.75,x5,i+0.75,lwd=2) }} text(myBegin-2,i,what[i],adj=1,xpd=T,cex={main_size},col="{main_color}") text(myEnd+25,i,paste(done[i],"%",sep=" "),adj=1,xpd=T,cex={percent_size},col="{percent_color}") text(myEnd+35,i,paste(format(x1,format="%d/%m/%y"),"-",format(x2,format="%d/%m/%y"),sep=" "),adj=0,xpd=T,cex={date_size},col="{date_color}") }} else # Milestone {{ x3<-as.Date(mySchedule[i,'when']) myHalf<-(myEnd-myBegin)/2 if (x3-x10) {{ text(myBegin-2,i,Group[i],adj=1,xpd=T,cex={heading_font_size},col="{heading_font_color}") }} else if (nchar(as.character(what[i]))>0) {{ x1<-as.Date(mySchedule[i,'from']) x2<-as.Date(mySchedule[i,'to']) x3<-x1+((x2-x1)*mySchedule[i,'done']/100) x<-c(x1,x2) x_done<-c(x1,x3) y<-c(i,i) segments(myBegin, i, myEnd, i, col="{line_color}") lines(x,y,lwd=20,col=myColour[i]) points(myEnd+90,i,cex=(mySchedule[i,'Persons']*mySchedule[i,'Durance'])**0.5,pch=19,col=rgb(110,110,110,50,maxColorValue=255),xpd=T) if (x3-x1>1) lines(x_done,y,lwd=20,col=myColour_done) if (mySchedule[i,'PAG'] > 0) {{ x4<-as.Date(mySchedule[i,'AG_from']) x5<-as.Date(mySchedule[i,'AG_to']) x_ag<-c(x4,x5) rect(x4,i-0.75,x5,i+0.75,lwd=2) }} text(myBegin-2,i,what[i],adj=1,xpd=T,cex={main_size},col="{main_color}") text(myEnd+25,i,paste(done[i],"%",sep=" "),adj=1,xpd=T,cex={percent_size},col="{percent_color}") text(myEnd+35,i,paste(format(x1,format="%d/%m/%y"),"-",format(x2,format="%d/%m/%y"),sep=" "),adj=0,xpd=T,cex={date_size},col="{date_color}") }} else # Milestone {{ x3<-as.Date(mySchedule[i,'when']) myHalf<-(myEnd-myBegin)/2 if (x3-x110, yes = 2, no = 1)), minor.ticks = 1, major.tick.length = 0.5, labels.niceFacing = FALSE) }} ) circos.clear() mtext(line=-1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=-0.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") dev.off() png("{out_path}.png") par(omi=c(0.25,0.25,0.25,0.25), mai=c(0,0,0,0),col="{scale_font_color}") circos.par(start.degree = 90, gap.degree = 4, track.margin = c(-0.1, 0.1), points.overflow.warning = FALSE) par(mar = rep(0, 4)) chordDiagram(x = df0, grid.col = df1$col, transparency = 0.25, order = df1$region, directional = 1, direction.type = c("arrows", "diffHeight"), diffHeight = -0.04, annotationTrack = "grid", annotationTrackHeight = c(0.05, 0.1), link.arr.type = "big.arrow", link.sort = TRUE, link.largest.ontop = TRUE) circos.trackPlotRegion( track.index = 1, bg.border = NA, panel.fun = function(x, y) {{ xlim = get.cell.meta.data("xlim") sector.index = get.cell.meta.data("sector.index") reg1 = df1$reg1[df1$region == sector.index] reg2 = df1$reg2[df1$region == sector.index] circos.text(x = mean(xlim), y = ifelse(test = nchar(reg2) == 0, yes = 5.2, no = 6.0), labels = reg1, facing = "bending", cex = {font_size}, col="{font_color}") circos.text(x = mean(xlim), y = 4.4, labels = reg2, facing = "bending", cex = {font_size}, col="{font_color}") circos.axis(h = "top", major.at = seq(from = 0, to = xlim[2], by = ifelse(test = xlim[2]>10, yes = 2, no = 1)), minor.ticks = 1, major.tick.length = 0.5, labels.niceFacing = FALSE) }} ) circos.clear() mtext(line=-1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=-0.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") dev.off() png("{char_out_path}",width=900,height=408) par(omi=c(0.25,0.25,0.25,0.25), mai=c(0,0,0,0),col="{scale_font_color}") circos.par(start.degree = 90, gap.degree = 4, track.margin = c(-0.1, 0.1), points.overflow.warning = FALSE) par(mar = rep(0, 4)) chordDiagram(x = df0, grid.col = df1$col, transparency = 0.25, order = df1$region, directional = 1, direction.type = c("arrows", "diffHeight"), diffHeight = -0.04, annotationTrack = "grid", annotationTrackHeight = c(0.05, 0.1), link.arr.type = "big.arrow", link.sort = TRUE, link.largest.ontop = TRUE) circos.trackPlotRegion( track.index = 1, bg.border = NA, panel.fun = function(x, y) {{ xlim = get.cell.meta.data("xlim") sector.index = get.cell.meta.data("sector.index") reg1 = df1$reg1[df1$region == sector.index] reg2 = df1$reg2[df1$region == sector.index] circos.text(x = mean(xlim), y = ifelse(test = nchar(reg2) == 0, yes = 5.2, no = 6.0), labels = reg1, facing = "bending", cex = {font_size}, col="{font_color}") circos.text(x = mean(xlim), y = 4.4, labels = reg2, facing = "bending", cex = {font_size}, col="{font_color}") circos.axis(h = "top", major.at = seq(from = 0, to = xlim[2], by = ifelse(test = xlim[2]>10, yes = 2, no = 1)), minor.ticks = 1, major.tick.length = 0.5, labels.niceFacing = FALSE) }} ) circos.clear() mtext(line=-1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=-0.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") dev.off() svg("{out_path}.svg") par(omi=c(0.25,0.25,0.25,0.25), mai=c(0,0,0,0),col="{scale_font_color}") circos.par(start.degree = 90, gap.degree = 4, track.margin = c(-0.1, 0.1), points.overflow.warning = FALSE) par(mar = rep(0, 4)) chordDiagram(x = df0, grid.col = df1$col, transparency = 0.25, order = df1$region, directional = 1, direction.type = c("arrows", "diffHeight"), diffHeight = -0.04, annotationTrack = "grid", annotationTrackHeight = c(0.05, 0.1), link.arr.type = "big.arrow", link.sort = TRUE, link.largest.ontop = TRUE) circos.trackPlotRegion( track.index = 1, bg.border = NA, panel.fun = function(x, y) {{ xlim = get.cell.meta.data("xlim") sector.index = get.cell.meta.data("sector.index") reg1 = df1$reg1[df1$region == sector.index] reg2 = df1$reg2[df1$region == sector.index] circos.text(x = mean(xlim), y = ifelse(test = nchar(reg2) == 0, yes = 5.2, no = 6.0), labels = reg1, facing = "bending", cex = {font_size}, col="{font_color}") circos.text(x = mean(xlim), y = 4.4, labels = reg2, facing = "bending", cex = {font_size}, col="{font_color}") circos.axis(h = "top", major.at = seq(from = 0, to = xlim[2], by = ifelse(test = xlim[2]>10, yes = 2, no = 1)), minor.ticks = 1, major.tick.length = 0.5, labels.niceFacing = FALSE) }} ) circos.clear() mtext(line=-1,"{title}",cex={title_font_size},adj=0,col="{title_font_color}") mtext(line=-2.5,"{subtitle}",cex={title_font_size}*0.6,adj=0,font=3,col="{title_font_color}") mtext(side=1,line=-0.5,"{caption}",cex={title_font_size}*0.6,adj=1,font=3,col="{title_font_color}") dev.off() """ keep_txt_to_file(code, f"{out_path}.R") os.system(f"Rscript {out_path}.R")