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https://github.com/sbrl/research-rainfallradar
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plot_metrics_multi: add option to plot train/val separately
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1 changed files with 27 additions and 6 deletions
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@ -33,15 +33,29 @@ def plot_metric(ax, train_list, val_list, metric_name, model_names, dir_output):
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# plt.savefig(os.path.join(dir_output, f"{name}.png"))
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# plt.close()
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def plot_metric_single(ax, data_list, metric_name, model_names, dir_output):
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i = 0
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for item in data_list:
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ax.plot(item, label=model_names[i], linewidth=1)
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i += 1
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ax.set_title(metric_name)
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ax.set_xlabel("epoch")
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ax.set_ylabel(metric_name)
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# plt.savefig(os.path.join(dir_output, f"{name}.png"))
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# plt.close()
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def make_dfs(filepaths_input):
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dfs = []
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for filepath_input in filepaths_input:
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print("DEBUG filepath_input", filepath_input)
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dfs = pd.read_csv(filepath_input, sep="\t")
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def plot_metrics(filepaths_input, model_names, dirpath_output, resolution=1):
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def plot_metrics(filepaths_input, model_names, dirpath_output, resolution=1, train_val_separate=False):
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dfs = [ pd.read_csv(filepath_input, sep="\t") for filepath_input in filepaths_input ]
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matplotlib.rcParams.update({'font.size': 15*resolution})
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matplotlib.rcParams.update({'font.size': 15*resolution*(0.5 if train_val_separate else 1)})
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fig = plt.figure(figsize=(10*resolution, 14*resolution))
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for i, colname in enumerate(filter(lambda colname: colname != "epoch" and not colname.startswith("val_"), dfs[0].columns.values.tolist())):
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train = [ df[colname] for df in dfs ]
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@ -50,9 +64,15 @@ def plot_metrics(filepaths_input, model_names, dirpath_output, resolution=1):
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colname_display = colname.replace("metric_dice_coefficient", "dice coefficient") \
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.replace("one_hot_mean_iou", "mean iou")
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ax = fig.add_subplot(3, 2, i+1)
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if train_val_separate:
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ax = fig.add_subplot(3*2, 2*2, (i+1)*2 - 1)
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plot_metric_single(ax, train, metric_name=colname_display, model_names=model_names, dir_output=dirpath_output)
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ax = fig.add_subplot(3*2, 2*2, (i+1)*2)
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plot_metric_single(ax, val, metric_name=f"val_{colname_display}", model_names=model_names, dir_output=dirpath_output)
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else:
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ax = fig.add_subplot(3 * 2, 2, i+1)
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plot_metric(ax, train, val, metric_name=colname_display, model_names=model_names, dir_output=dirpath_output)
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plot_metric(ax, train, val, metric_name=colname_display, model_names=model_names, dir_output=dirpath_output)
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# Ref https://stackoverflow.com/a/57484812/1460422
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@ -91,7 +111,7 @@ Usage:
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echo -e "filepathA\\nfilepathB..." | [OUTPUT="path/to/output_dir"] [REGEX_NAME=''] path/to/plot_metrics_multi.py
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""")
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sys.exit()
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TRAIN_VAL_SEPARATE = True if "TRAIN_VAL_SEPARATE" in os.environ else False
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REGEX_NAME = os.environ["REGEX_NAME"] if "REGEX_NAME" in os.environ else None
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if REGEX_NAME is None and len(sys.argv) >= 1:
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REGEX_NAME = sys.argv[1]
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@ -126,6 +146,7 @@ Usage:
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FILEPATHS_INPUT,
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MODEL_NAMES,
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DIRPATH_OUTPUT,
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resolution=float(os.environ["RESOLUTION"]) if "RESOLUTION" in os.environ else 1
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resolution=float(os.environ["RESOLUTION"]) if "RESOLUTION" in os.environ else 1,
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train_val_separate=TRAIN_VAL_SEPARATE
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)
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