Reformulate Math Functions
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@@ -31,10 +31,10 @@ from datasets.synthetic_example import create_example_v1
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from utils.temp_sync import optimize_fn, evaluate_fn
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def draw_multi_fig(save_dir, timestamp, scatter_list, fig_title=None):
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def draw_multi_fig(save_dir, timestamp, scatter_list, wh, fig_title=None):
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save_path = save_dir / "{:04d}".format(timestamp)
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# print('Plot the figure at timestamp-{:} into {:}'.format(timestamp, save_path))
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dpi, width, height = 40, 2000, 1300
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dpi, width, height = 40, wh[0], wh[1]
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figsize = width / float(dpi), height / float(dpi)
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LabelSize, LegendFontsize, font_gap = 80, 80, 5
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@@ -61,8 +61,7 @@ def draw_multi_fig(save_dir, timestamp, scatter_list, fig_title=None):
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tick.label.set_rotation(10)
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for tick in cur_ax.yaxis.get_major_ticks():
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tick.label.set_fontsize(LabelSize - font_gap)
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plt.legend(loc=1, fontsize=LegendFontsize)
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plt.legend(loc=1, fontsize=LegendFontsize)
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fig.savefig(str(save_path) + ".pdf", dpi=dpi, bbox_inches="tight", format="pdf")
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fig.savefig(str(save_path) + ".png", dpi=dpi, bbox_inches="tight", format="png")
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plt.close("all")
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@@ -115,18 +114,19 @@ def compare_cl(save_dir):
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"color": "r",
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"s": 10,
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"xlim": (-6, 6 + timestamp * 0.2),
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"ylim": (-200, 40),
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"ylim": (-40, 40),
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"alpha": 0.99,
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"label": "Continual Learning",
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}
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)
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draw_multi_fig(
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save_dir, timestamp, scatter_list, "Timestamp={:03d}".format(timestamp)
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save_dir, timestamp, scatter_list,
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wh=(2000, 1300), fig_title="Timestamp={:03d}".format(timestamp)
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)
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print("Save all figures into {:}".format(save_dir))
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save_dir = save_dir.resolve()
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cmd = "ffmpeg -y -i {xdir}/%04d.png -pix_fmt yuv420p -vf fps=2 -vf scale=1500:1000 -vb 5000k {xdir}/vis.mp4".format(
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cmd = "ffmpeg -y -i {xdir}/%04d.png -pix_fmt yuv420p -vf fps=2 -vf scale=2000:1300 -vb 5000k {xdir}/vis.mp4".format(
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xdir=save_dir
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)
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os.system(cmd)
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