CSS-LM

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import matplotlib.pyplot as plt
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import os
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import sys
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dir = sys.argv[1]
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fileDir = os.listdir(dir)
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filename_test = {int(f.split("_")[-1].replace(".txt","")):f for f in fileDir if "test_paper_results_" in f and "best" not in f}
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#x = sorted(list(filename_test.keys()))
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#print(x)
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#exit()
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#filename_dev = {int(f.split("_")[-1].replace(".txt","")):f for f in fileDir if "test_results_" in f}
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filename_dev = {int(f.split("_")[-1].replace(".txt","")):f for f in fileDir if "eval_results_" in f}
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x = sorted(list(filename_dev.keys()))
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#print(x)
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#exit()
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y_test_f1 = list()
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y_dev_acc = list()
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y_dev_loss = list()
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for id_ in x:
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    file_dev = filename_dev[id_]
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    file_test = filename_test[id_]
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    with open(dir+file_dev) as f:
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        for line in f:
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            line = line.strip().split()
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            if line[0]=='eval_accuracy':
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                y_dev_acc.append(float(line[-1]))
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            elif line[0]=='eval_loss':
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                y_dev_loss.append(float(line[-1]))
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            else:
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                pass
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    with open(dir+file_test) as f:
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        for line in f:
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            line = line.strip().split()
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            #print(line)
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            if line[0]=='F1':
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                y_test_f1.append(float(line[-1].replace("%",""))/100)
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                #print(y_test_f1)
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            else:
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                pass
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plt.plot(x, y_test_f1, label="test_f1", color='coral')
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plt.scatter(x, y_test_f1, color='coral')
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plt.plot(x, y_dev_loss, label="dev_loss", color='blue', linestyle='--')
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plt.scatter(x, y_dev_loss, color='blue')
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plt.plot(x, y_dev_acc, label="dev_f1", color='lightblue', linestyle='--')
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plt.scatter(x, y_dev_acc, color='lightblue')
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##########
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###loss###
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##########
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loss_x = list()
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loss_y = list()
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loss_no_pseudo_x = list()
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loss_no_pseudo_y = list()
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with open(dir+"loss") as f:
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    for i, line in enumerate(f):
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        if i%x[0] == 0 and i>=x[0]:
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            loss_x.append(i)
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            loss_y.append(float(line))
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try:
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    with open(dir+"loss_no_pseudo") as f:
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        for i, line in enumerate(f):
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            if i%x[0] == 0 and i>=x[0]:
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                loss_no_pseudo_x.append(i)
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                loss_no_pseudo_y.append(float(line))
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except:
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    print("Have no loss_no_pseudo")
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plt.plot(loss_x, loss_y, label="train_loss", color='lightgreen', linestyle='--')
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try:
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    plt.plot(loss_no_pseudo_x, loss_no_pseudo_y, label="train_loss_no_pseudo", color='green', linestyle='--')
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except:
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    pass
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plt.legend(loc='upper left')
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plt.savefig('loss.pdf',format="pdf")
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