""" Figures for: "Strength reduction and strength-scaling relations of M40 concrete with untreated bamboo chips as partial coarse-aggregate replacement" Fig1 strength retained vs bamboo content Fig2 flexural and splitting tensile strength vs compressive strength (log-log) Fig3 compressive strength retained compared with published data Each figure is saved to ./figures as EPS and PDF (vector, fonts embedded) and as TIFF (LZW) and PNG at DPI resolution. Adjust the SETTINGS block to a journal's figure requirements (width ~84-90 mm for one column of a two-column page, ~174-190 mm for full page width). Requires: Python 3.8+, numpy, scipy, matplotlib Run: python make_figures.py """ import os import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt from matplotlib.lines import Line2D from scipy import stats from bamboo_data import LEVELS, COMPRESSIVE, SPLITTING, FLEXURAL, LITERATURE # ----------------------------------------------------------------- SETTINGS FIG_W_MM = 174 # figure width (mm) FONT_STYLE = "sans" # "sans" (Arial/Helvetica) or "serif" (Times) DPI = 600 # resolution of TIFF/PNG files FILE_PREFIX = "Fig" # files are named Fig1, Fig2, Fig3 # -------------------------------------------------------------------- STYLE MM = 1 / 25.4 NARROW = FIG_W_MM < 120 # narrow figures: smaller text, legend below FS = 7 if NARROW else 9 # base font size (pt) FIGSIZE = (FIG_W_MM * MM, (0.80 if NARROW else 0.66) * FIG_W_MM * MM) OUT = os.path.join(os.path.dirname(os.path.abspath(__file__)), "figures") mpl.rcParams.update({ "font.family": "sans-serif" if FONT_STYLE == "sans" else "serif", "font.sans-serif": ["Arial", "Helvetica", "Liberation Sans", "DejaVu Sans"], "font.serif": ["Times New Roman", "Liberation Serif", "DejaVu Serif"], "mathtext.fontset": "stixsans" if FONT_STYLE == "sans" else "stix", "font.size": FS, "axes.labelsize": FS, "xtick.labelsize": FS - 0.5, "ytick.labelsize": FS - 0.5, "legend.fontsize": FS - 1, "legend.frameon": False, "axes.linewidth": 0.6, "xtick.major.width": 0.6, "ytick.major.width": 0.6, "xtick.direction": "in", "ytick.direction": "in", "xtick.top": True, "ytick.right": True, "savefig.dpi": DPI, "savefig.bbox": "tight", "savefig.pad_inches": 0.02, "pdf.fonttype": 42, "ps.fonttype": 42, }) # Colour-blind-safe palette; each series also has its own marker and line # style so the figures remain readable in greyscale. BLACK, BLUE, VERMILION = "#000000", "#0072B2", "#D55E00" GREEN, ORANGE, GREY = "#009E73", "#E69F00", "#555555" FC = r"f^{\prime}_{\!c}" DOTTED, DASHED = (0, (1.2, 1.6)), (0, (5, 2.5)) def mean_sd(data): return (np.array([np.mean(data[k]) for k in LEVELS]), np.array([np.std(data[k], ddof=1) for k in LEVELS])) p = np.array(LEVELS) fc, fc_sd = mean_sd(COMPRESSIVE) fsp, fsp_sd = mean_sd(SPLITTING) fr, fr_sd = mean_sd(FLEXURAL) def save(fig, number): name = os.path.join(OUT, f"{FILE_PREFIX}{number}") for ext in ("eps", "pdf", "png"): fig.savefig(f"{name}.{ext}") fig.savefig(f"{name}.tiff", pil_kwargs={"compression": "tiff_lzw"}) plt.close(fig) def add_legend(ax, handles=None, labels=None, loc="upper left"): if handles is None: handles, labels = ax.get_legend_handles_labels() if NARROW: ax.legend(handles, labels, loc="upper center", bbox_to_anchor=(0.5, -0.2), ncol=2, handlelength=2.2, columnspacing=1.0) else: ax.legend(handles, labels, loc=loc, handlelength=2.5) def fig1(): fig, ax = plt.subplots(figsize=FIGSIZE) series = [(rf"Compressive, ${FC}$", fc, fc_sd, BLACK, "o", "-", BLACK), ("Flexural, $f_r$", fr, fr_sd, BLUE, "s", "--", "white"), ("Splitting tensile, $f_{sp}$", fsp, fsp_sd, VERMILION, "^", ":", "white")] for label, m, sd, c, marker, ls, mfc in series: retained = 100 * m / m[0] ax.errorbar(p, retained, yerr=100 * sd / m[0], color=c, ls=ls, marker=marker, mfc=mfc, mec=c, mew=0.9, ms=5.5, capsize=2.5, elinewidth=0.7, label=label, zorder=3) ax.annotate(f"{retained[-1]:.0f}%", xy=(p[-1], retained[-1]), xytext=(7, 0), textcoords="offset points", va="center", fontsize=FS - 1, color=c) ax.set(xlim=(-0.8, 18), ylim=(0, 105), xticks=p, yticks=np.arange(0, 101, 20), xlabel="Bamboo chips (% of coarse aggregate by volume)", ylabel="Strength retained (% of control)") add_legend(ax, loc="lower left") save(fig, 1) def fig2(): fig, ax = plt.subplots(figsize=FIGSIZE) xx = np.linspace(13.5, 47, 200) for m, sd, label, marker, c, lx, dy, va, ha in [ (fr, fr_sd, "Flexural, $f_r$", "s", BLUE, 26, 1.08, "bottom", "right"), (fsp, fsp_sd, "Splitting tensile, $f_{sp}$", "^", VERMILION, 31, 0.87, "top", "left")]: fit = stats.linregress(np.log(fc), np.log(m)) a, b = np.exp(fit.intercept), fit.slope k = np.mean(m / np.sqrt(fc)) ax.errorbar(fc, m, xerr=fc_sd, yerr=sd, ls="none", marker=marker, mfc="white", mec=c, ecolor=c, mew=0.9, ms=5.5, elinewidth=0.6, capsize=2, label=label, zorder=4) ax.plot(xx, a * xx ** b, color=c, lw=1.1, zorder=3) ax.plot(xx, k * np.sqrt(xx), color=GREY, lw=0.9, ls=DOTTED, zorder=2) symbol = "f_r" if c == BLUE else "f_{sp}" ax.text(lx, a * lx ** b * dy, rf"${symbol} = {a:.3f}\,({FC})^{{{b:.2f}}}$" + "\n" + rf"$R^2 = {fit.rvalue ** 2:.3f}$", color=c, fontsize=FS - 1, va=va, ha=ha) ax.plot(xx, 0.62 * np.sqrt(xx), color=GREY, lw=0.9, ls=DASHED, zorder=2) ax.set_xscale("log") ax.set_yscale("log") ax.set(xlim=(13.5, 47), ylim=(1.4, 6), xticks=[15, 20, 25, 30, 40], yticks=[1.5, 2, 3, 4, 5, 6], xlabel=rf"Compressive strength, ${FC}$ (MPa)", ylabel="Flexural or splitting tensile strength (MPa)") for axis in (ax.xaxis, ax.yaxis): axis.set_major_formatter(mpl.ticker.FuncFormatter(lambda v, _: f"{v:g}")) axis.set_minor_formatter(mpl.ticker.NullFormatter()) handles, labels = ax.get_legend_handles_labels() handles += [Line2D([], [], color=BLACK, lw=1.1), Line2D([], [], color=GREY, lw=0.9, ls=DOTTED), Line2D([], [], color=GREY, lw=0.9, ls=DASHED)] labels += [rf"Power-law fit, $a\,({FC})^{{b}}$", rf"$k\sqrt{{{FC}}}$ (exponent 0.5)", rf"ACI 318: $0.62\sqrt{{{FC}}}$"] add_legend(ax, handles, labels, loc="upper left") save(fig, 2) def fig3(): fig, ax = plt.subplots(figsize=FIGSIZE) styles = [(GREEN, "^", "--"), (ORANGE, "s", "--"), (VERMILION, "v", "--"), (BLUE, "D", ":")] ax.plot(p, 100 * fc / fc[0], color=BLACK, marker="o", ls="-", lw=1.8, ms=5.5, label="This study (M40, untreated chips)", zorder=4) for (label, (control, values)), (c, marker, ls) in zip(LITERATURE.items(), styles): x = [0] + list(values) y = [100] + [100 * v / control for v in values.values()] ax.plot(x, y, color=c, marker=marker, ls=ls, mfc="white", mec=c, mew=0.9, ms=5, lw=1.0, label=label, zorder=2) ax.set(xlim=(-1, 42), ylim=(0, 105), xticks=np.arange(0, 41, 5), yticks=np.arange(0, 101, 20), xlabel="Bamboo replacing coarse aggregate (%)", ylabel="Compressive strength retained (% of control)") add_legend(ax, loc="upper right") save(fig, 3) if __name__ == "__main__": os.makedirs(OUT, exist_ok=True) fig1() fig2() fig3() print(f"Figures saved to {OUT}")