Создание этого базового участка с ggplot2: Это ошибка ggplot2?

Question

Я пытаюсь построить эту базовую Plot

df <- 
structure(list(X = c(1e-04, 2e-04, 3e-04, 4e-04, 5e-04, 6e-04, 
7e-04, 8e-04, 9e-04, 0.001, 0.0011, 0.0012, 0.0013, 0.0014, 0.0015, 
0.0016, 0.0017, 0.0018, 0.0019, 0.002, 0.0021, 0.0022, 0.0023, 
0.0024, 0.0025, 0.0026, 0.0027, 0.0028, 0.0029, 0.003, 0.0031, 
0.0032, 0.0033, 0.0034, 0.0035, 0.0036, 0.0037, 0.0038, 0.0039, 
0.004, 0.0041, 0.0042, 0.0043, 0.0044, 0.0045, 0.0046, 0.0047, 
0.0048, 0.0049, 0.005, 0.0051, 0.0052, 0.0053, 0.0054, 0.0055, 
0.0056, 0.0057, 0.0058, 0.0059, 0.006, 0.0061, 0.0062, 0.0063, 
0.0064, 0.0065, 0.0066, 0.0067, 0.0068, 0.0069, 0.007, 0.0071, 
0.0072, 0.0073, 0.0074, 0.0075, 0.0076, 0.0077, 0.0078, 0.0079, 
0.008, 0.0081, 0.0082, 0.0083, 0.0084, 0.0085, 0.0086, 0.0087, 
0.0088, 0.0089, 0.009, 0.0091, 0.0092, 0.0093, 0.0094, 0.0095, 
0.0096, 0.0097, 0.0098, 0.0099, 0.01, 0.0101, 0.0102, 0.0103, 
0.0104, 0.0105, 0.0106, 0.0107, 0.0108, 0.0109, 0.011, 0.0111, 
0.0112, 0.0113, 0.0114, 0.0115, 0.0116, 0.0117, 0.0118, 0.0119, 
0.012, 0.0121, 0.0122, 0.0123, 0.0124, 0.0125, 0.0126, 0.0127, 
0.0128, 0.0129, 0.013, 0.0131, 0.0132, 0.0133, 0.0134, 0.0135, 
0.0136, 0.0137, 0.0138, 0.0139, 0.014, 0.0141, 0.0142, 0.0143, 
0.0144, 0.0145, 0.0146, 0.0147, 0.0148, 0.0149, 0.015, 0.0151, 
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0.0184, 0.0185, 0.0186, 0.0187, 0.0188, 0.0189, 0.019, 0.0191, 
0.0192, 0.0193, 0.0194, 0.0195, 0.0196, 0.0197, 0.0198, 0.0199, 
0.02, 0.0201, 0.0202, 0.0203, 0.0204, 0.0205, 0.0206, 0.0207, 
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0.0592, 0.0593, 0.0594, 0.0595, 0.0596, 0.0597, 0.0598, 0.0599, 
0.06, 0.0601, 0.0602, 0.0603, 0.0604, 0.0605, 0.0606, 0.0607, 
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0.0792, 0.0793, 0.0794, 0.0795, 0.0796, 0.0797, 0.0798, 0.0799, 
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0.0808, 0.0809, 0.081, 0.0811, 0.0812, 0.0813, 0.0814, 0.0815, 
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0.0992, 0.0993, 0.0994, 0.0995, 0.0996, 0.0997, 0.0998, 0.0999, 
0.1), Y = c(3.9e-125, 1.47e-124, 3.1e-124, 5.19e-124, 7.62e-124, 
1.03e-123, 1.32e-123, 1.62e-123, 1.93e-123, 2.24e-123, 2.55e-123, 
2.86e-123, 3.15e-123, 3.44e-123, 3.71e-123, 3.97e-123, 4.21e-123, 
4.44e-123, 4.66e-123, 4.85e-123, 5.03e-123, 5.19e-123, 5.33e-123, 
5.46e-123, 5.57e-123, 5.67e-123, 5.75e-123, 5.81e-123, 5.86e-123, 
5.9e-123, 5.92e-123, 5.93e-123, 5.93e-123, 5.92e-123, 5.9e-123, 
5.87e-123, 5.83e-123, 5.78e-123, 5.73e-123, 5.67e-123, 5.6e-123, 
5.52e-123, 5.44e-123, 5.36e-123, 5.27e-123, 5.18e-123, 5.08e-123, 
4.98e-123, 4.88e-123, 4.78e-123, 4.68e-123, 4.57e-123, 4.46e-123, 
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3.1e-123, 3.01e-123, 2.91e-123, 2.82e-123, 2.73e-123, 2.64e-123, 
2.55e-123, 2.46e-123, 2.38e-123, 2.3e-123, 2.22e-123, 2.14e-123, 
2.07e-123, 1.99e-123, 1.92e-123, 1.85e-123, 1.78e-123, 1.72e-123, 
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1.31e-123, 1.26e-123, 1.21e-123, 1.16e-123, 1.12e-123, 1.07e-123, 
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4.87e-125, 4.63e-125, 4.41e-125, 4.19e-125, 3.98e-125, 3.79e-125, 
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2.66e-125, 2.53e-125, 2.4e-125, 2.28e-125, 2.17e-125, 2.06e-125, 
1.96e-125, 1.86e-125, 1.77e-125, 1.68e-125, 1.59e-125, 1.51e-125, 
1.44e-125, 1.37e-125, 1.3e-125, 1.23e-125, 1.17e-125, 1.11e-125, 
1.05e-125, 1e-125, 9.5e-126, 9.02e-126, 8.56e-126, 8.12e-126, 
7.71e-126, 7.32e-126, 6.94e-126, 6.59e-126, 6.25e-126, 5.93e-126, 
5.63e-126, 5.34e-126, 5.06e-126, 4.8e-126, 4.55e-126, 4.32e-126, 
4.1e-126, 3.89e-126, 3.68e-126, 3.49e-126, 3.31e-126, 3.14e-126, 
2.98e-126, 2.82e-126, 2.68e-126, 2.54e-126, 2.41e-126, 2.28e-126, 
2.16e-126, 2.05e-126, 1.94e-126, 1.84e-126, 1.74e-126, 1.65e-126, 
1.57e-126, 1.48e-126, 1.41e-126, 1.33e-126, 1.26e-126, 1.2e-126, 
1.13e-126, 1.07e-126, 1.02e-126, 9.63e-127, 9.12e-127, 8.64e-127, 
8.18e-127, 7.75e-127, 7.34e-127, 6.95e-127, 6.58e-127, 6.23e-127, 
5.9e-127, 5.59e-127, 5.29e-127, 5.01e-127, 4.74e-127, 4.49e-127, 
4.25e-127, 4.03e-127, 3.81e-127, 3.61e-127, 3.41e-127, 3.23e-127, 
3.06e-127, 2.89e-127, 2.74e-127, 2.59e-127, 2.45e-127, 2.32e-127, 
2.2e-127, 2.08e-127, 1.97e-127, 1.86e-127, 1.76e-127, 1.67e-127, 
1.58e-127, 1.49e-127, 1.41e-127, 1.33e-127, 1.26e-127, 1.19e-127, 
1.13e-127, 1.07e-127, 1.01e-127, 9.56e-128, 9.04e-128, 8.55e-128, 
8.09e-128, 7.65e-128, 7.23e-128, 6.84e-128, 6.47e-128, 6.12e-128, 
5.78e-128, 5.47e-128, 5.17e-128, 4.89e-128, 4.62e-128, 4.37e-128, 
4.13e-128, 3.91e-128, 3.69e-128, 3.49e-128, 3.3e-128, 3.12e-128, 
2.95e-128, 2.79e-128, 2.63e-128, 2.49e-128, 2.35e-128, 2.22e-128, 
2.1e-128, 1.99e-128, 1.88e-128, 1.77e-128, 1.68e-128, 1.58e-128, 
1.5e-128, 1.41e-128, 1.34e-128, 1.26e-128, 1.19e-128, 1.13e-128, 
1.06e-128, 1.01e-128, 9.5e-129, 8.98e-129, 8.48e-129, 8.01e-129, 
7.57e-129, 7.15e-129, 6.75e-129, 6.38e-129, 6.02e-129, 5.69e-129, 
5.37e-129, 5.08e-129, 4.79e-129, 4.53e-129, 4.28e-129, 4.04e-129, 
3.81e-129, 3.6e-129, 3.4e-129, 3.21e-129, 3.03e-129, 2.86e-129, 
2.7e-129, 2.55e-129, 2.41e-129, 2.28e-129, 2.15e-129, 2.03e-129, 
1.92e-129, 1.81e-129, 1.71e-129, 1.61e-129, 1.52e-129, 1.44e-129, 
1.36e-129, 1.28e-129, 1.21e-129, 1.14e-129, 1.08e-129, 1.02e-129, 
9.59e-130, 9.05e-130, 8.54e-130, 8.06e-130, 7.61e-130, 7.18e-130, 
6.78e-130, 6.4e-130, 6.04e-130, 5.7e-130, 5.38e-130, 5.07e-130, 
4.79e-130, 4.52e-130, 4.26e-130, 4.02e-130, 3.8e-130, 3.58e-130, 
3.38e-130, 3.19e-130, 3.01e-130, 2.84e-130, 2.68e-130, 2.53e-130, 
2.38e-130, 2.25e-130, 2.12e-130, 2e-130, 1.89e-130, 1.78e-130, 
1.68e-130, 1.58e-130, 1.49e-130, 1.41e-130, 1.33e-130, 1.25e-130, 
1.18e-130, 1.12e-130, 1.05e-130, 9.92e-131, 9.36e-131, 8.83e-131, 
8.32e-131, 7.85e-131, 7.4e-131, 6.98e-131, 6.58e-131, 6.21e-131, 
5.85e-131, 5.52e-131, 5.21e-131, 4.91e-131, 4.63e-131, 4.36e-131, 
4.12e-131, 3.88e-131, 3.66e-131, 3.45e-131, 3.25e-131, 3.07e-131, 
2.89e-131, 2.73e-131, 2.57e-131, 2.42e-131, 2.28e-131, 2.15e-131, 
2.03e-131, 1.91e-131, 1.8e-131, 1.7e-131, 1.6e-131, 1.51e-131, 
1.42e-131, 1.34e-131, 1.27e-131, 1.19e-131, 1.12e-131, 1.06e-131, 
9.99e-132, 9.41e-132, 8.87e-132, 8.36e-132, 7.88e-132, 7.43e-132, 
7e-132, 6.59e-132, 6.22e-132, 5.86e-132, 5.52e-132, 5.2e-132, 
4.9e-132, 4.62e-132, 4.35e-132, 4.1e-132, 3.86e-132, 3.64e-132, 
3.43e-132, 3.23e-132, 3.05e-132, 2.87e-132, 2.7e-132, 2.55e-132, 
2.4e-132, 2.26e-132, 2.13e-132, 2.01e-132, 1.89e-132, 1.78e-132, 
1.68e-132, 1.58e-132, 1.49e-132, 1.4e-132, 1.32e-132, 1.25e-132, 
1.17e-132, 1.11e-132, 1.04e-132, 9.81e-133, 9.24e-133, 8.7e-133, 
8.19e-133, 7.72e-133, 7.27e-133, 6.85e-133, 6.45e-133, 6.07e-133, 
5.72e-133, 5.39e-133, 5.07e-133, 4.78e-133, 4.5e-133, 4.24e-133, 
3.99e-133, 3.76e-133, 3.54e-133, 3.33e-133, 3.14e-133, 2.96e-133, 
2.78e-133, 2.62e-133, 2.47e-133, 2.32e-133, 2.19e-133, 2.06e-133, 
1.94e-133, 1.83e-133, 1.72e-133, 1.62e-133, 1.53e-133, 1.44e-133, 
1.35e-133, 1.27e-133, 1.2e-133, 1.13e-133, 1.06e-133, 1e-133, 
9.42e-134, 8.87e-134, 8.35e-134, 7.86e-134, 7.4e-134, 6.96e-134, 
6.56e-134, 6.17e-134, 5.81e-134, 5.47e-134, 5.15e-134, 4.85e-134, 
4.56e-134, 4.29e-134, 4.04e-134, 3.8e-134, 3.58e-134, 3.37e-134, 
3.17e-134, 2.99e-134, 2.81e-134, 2.64e-134, 2.49e-134, 2.34e-134, 
2.2e-134, 2.08e-134, 1.95e-134, 1.84e-134, 1.73e-134, 1.63e-134, 
1.53e-134, 1.44e-134, 1.36e-134, 1.28e-134, 1.2e-134, 1.13e-134, 
1.06e-134, 1e-134, 9.42e-135, 8.86e-135, 8.34e-135, 7.85e-135, 
7.39e-135, 6.95e-135, 6.54e-135, 6.15e-135, 5.79e-135, 5.45e-135, 
5.12e-135, 4.82e-135, 4.54e-135, 4.27e-135, 4.02e-135, 3.78e-135, 
3.55e-135, 3.34e-135, 3.15e-135, 2.96e-135, 2.78e-135, 2.62e-135, 
2.46e-135, 2.32e-135, 2.18e-135, 2.05e-135, 1.93e-135, 1.82e-135, 
1.71e-135, 1.61e-135, 1.51e-135, 1.42e-135, 1.34e-135, 1.26e-135, 
1.18e-135, 1.11e-135, 1.05e-135, 9.84e-136, 9.26e-136, 8.71e-136, 
8.19e-136, 7.7e-136, 7.25e-136, 6.81e-136, 6.41e-136, 6.03e-136, 
5.67e-136, 5.33e-136, 5.01e-136, 4.72e-136, 4.43e-136, 4.17e-136, 
3.92e-136, 3.69e-136, 3.47e-136, 3.26e-136, 3.07e-136, 2.88e-136, 
2.71e-136, 2.55e-136, 2.4e-136, 2.26e-136, 2.12e-136, 1.99e-136, 
1.87e-136, 1.76e-136, 1.66e-136, 1.56e-136, 1.47e-136, 1.38e-136, 
1.3e-136, 1.22e-136, 1.15e-136, 1.08e-136, 1.01e-136, 9.52e-137, 
8.95e-137, 8.41e-137, 7.91e-137, 7.44e-137, 6.99e-137, 6.57e-137, 
6.18e-137, 5.81e-137, 5.46e-137, 5.13e-137, 4.83e-137, 4.54e-137, 
4.26e-137, 4.01e-137, 3.77e-137, 3.54e-137, 3.33e-137, 3.13e-137, 
2.94e-137, 2.77e-137, 2.6e-137, 2.44e-137, 2.3e-137, 2.16e-137, 
2.03e-137, 1.91e-137, 1.79e-137, 1.68e-137, 1.58e-137, 1.49e-137, 
1.4e-137, 1.31e-137, 1.24e-137, 1.16e-137, 1.09e-137, 1.03e-137, 
9.64e-138, 9.06e-138, 8.51e-138, 8e-138, 7.52e-138, 7.07e-138, 
6.64e-138, 6.24e-138, 5.86e-138, 5.51e-138, 5.18e-138, 4.87e-138, 
4.57e-138, 4.3e-138, 4.04e-138, 3.79e-138, 3.56e-138, 3.35e-138, 
3.15e-138, 2.96e-138, 2.78e-138, 2.61e-138, 2.45e-138, 2.31e-138, 
2.17e-138, 2.04e-138, 1.91e-138, 1.8e-138, 1.69e-138, 1.59e-138, 
1.49e-138, 1.4e-138, 1.32e-138, 1.24e-138, 1.16e-138, 1.09e-138, 
1.02e-138, 9.62e-139, 9.04e-139, 8.49e-139, 7.98e-139, 7.5e-139, 
7.04e-139, 6.61e-139, 6.21e-139, 5.84e-139, 5.48e-139, 5.15e-139, 
4.84e-139, 4.55e-139, 4.27e-139, 4.01e-139, 3.77e-139, 3.54e-139, 
3.32e-139, 3.12e-139, 2.93e-139, 2.75e-139, 2.59e-139, 2.43e-139, 
2.28e-139, 2.14e-139, 2.01e-139, 1.89e-139, 1.78e-139, 1.67e-139, 
1.57e-139, 1.47e-139, 1.38e-139, 1.3e-139, 1.22e-139, 1.14e-139, 
1.07e-139, 1.01e-139, 9.48e-140, 8.9e-140, 8.36e-140, 7.85e-140, 
7.37e-140, 6.92e-140, 6.5e-140, 6.1e-140, 5.73e-140, 5.38e-140, 
5.05e-140, 4.75e-140, 4.46e-140, 4.19e-140, 3.93e-140, 3.69e-140, 
3.46e-140, 3.25e-140, 3.05e-140, 2.87e-140, 2.69e-140, 2.53e-140, 
2.37e-140, 2.23e-140, 2.09e-140, 1.97e-140, 1.84e-140, 1.73e-140, 
1.63e-140, 1.53e-140, 1.43e-140, 1.35e-140, 1.26e-140, 1.19e-140, 
1.11e-140, 1.05e-140, 9.81e-141, 9.21e-141, 8.65e-141, 8.12e-141, 
7.62e-141, 7.16e-141, 6.72e-141, 6.31e-141, 5.92e-141, 5.56e-141, 
5.22e-141, 4.9e-141, 4.6e-141, 4.31e-141, 4.05e-141, 3.8e-141, 
3.57e-141, 3.35e-141, 3.14e-141, 2.95e-141, 2.77e-141, 2.6e-141, 
2.44e-141, 2.29e-141, 2.15e-141, 2.02e-141, 1.89e-141, 1.78e-141, 
1.67e-141, 1.57e-141, 1.47e-141, 1.38e-141, 1.29e-141, 1.21e-141, 
1.14e-141, 1.07e-141, 1e-141, 9.42e-142, 8.84e-142, 8.3e-142, 
7.79e-142, 7.31e-142, 6.86e-142, 6.44e-142, 6.04e-142, 5.67e-142, 
5.32e-142, 4.99e-142, 4.68e-142, 4.39e-142, 4.12e-142, 3.87e-142, 
3.63e-142, 3.41e-142, 3.2e-142, 3e-142, 2.81e-142, 2.64e-142, 
2.48e-142, 2.33e-142, 2.18e-142, 2.05e-142, 1.92e-142, 1.8e-142, 
1.69e-142, 1.59e-142, 1.49e-142, 1.4e-142, 1.31e-142, 1.23e-142, 
1.15e-142, 1.08e-142, 1.01e-142, 9.52e-143, 8.93e-143, 8.38e-143, 
7.86e-143, 7.38e-143, 6.92e-143, 6.49e-143, 6.09e-143, 5.71e-143, 
5.36e-143, 5.03e-143, 4.72e-143, 4.42e-143, 4.15e-143, 3.89e-143, 
3.65e-143, 3.43e-143, 3.21e-143, 3.01e-143, 2.83e-143, 2.65e-143, 
2.49e-143, 2.33e-143, 2.19e-143, 2.05e-143, 1.93e-143, 1.81e-143, 
1.69e-143, 1.59e-143, 1.49e-143, 1.4e-143, 1.31e-143, 1.23e-143, 
1.15e-143, 1.08e-143, 1.01e-143, 9.51e-144, 8.92e-144, 8.37e-144, 
7.85e-144, 7.36e-144, 6.9e-144, 6.47e-144, 6.07e-144, 5.69e-144, 
5.34e-144, 5.01e-144, 4.7e-144, 4.4e-144, 4.13e-144, 3.87e-144, 
3.63e-144, 3.41e-144, 3.19e-144, 2.99e-144, 2.81e-144, 2.63e-144, 
2.47e-144, 2.32e-144, 2.17e-144, 2.04e-144, 1.91e-144, 1.79e-144, 
1.68e-144, 1.57e-144, 1.48e-144, 1.38e-144, 1.3e-144, 1.22e-144, 
1.14e-144, 1.07e-144, 1e-144, 9.4e-145, 8.81e-145, 8.26e-145, 
7.75e-145, 7.26e-145, 6.81e-145, 6.38e-145, 5.99e-145, 5.61e-145, 
5.26e-145, 4.93e-145, 4.62e-145, 4.33e-145, 4.06e-145, 3.81e-145, 
3.57e-145, 3.35e-145, 3.14e-145, 2.94e-145, 2.76e-145, 2.59e-145, 
2.42e-145, 2.27e-145, 2.13e-145, 2e-145, 1.87e-145, 1.75e-145, 
1.64e-145, 1.54e-145, 1.44e-145, 1.35e-145, 1.27e-145, 1.19e-145, 
1.12e-145, 1.05e-145, 9.8e-146, 9.18e-146, 8.61e-146, 8.07e-146, 
7.56e-146, 7.09e-146, 6.64e-146, 6.23e-146, 5.84e-146, 5.47e-146, 
5.13e-146, 4.8e-146, 4.5e-146, 4.22e-146, 3.95e-146, 3.71e-146, 
3.47e-146, 3.26e-146, 3.05e-146, 2.86e-146, 2.68e-146, 2.51e-146, 
2.35e-146, 2.21e-146, 2.07e-146, 1.94e-146, 1.81e-146, 1.7e-146, 
1.59e-146, 1.49e-146, 1.4e-146, 1.31e-146, 1.23e-146, 1.15e-146, 
1.08e-146, 1.01e-146, 9.47e-147, 8.88e-147, 8.32e-147, 7.79e-147, 
7.3e-147, 6.84e-147, 6.41e-147, 6.01e-147, 5.63e-147)), .Names = c("X", 
"Y"), class = "data.frame", row.names = c(NA, -1000L)) 

Code

plot(x=df$X, y=df$Y) 

с ggplot2

library(ggplot2) 
library(scales) 
p <- ggplot(data=df, aes(x=X, y=Y))+geom_point() 
p 

Я не мог понять, как установить ylim в ggplot2, чтобы получить правильный график. Любая помощь будет высоко оценена. Благодаря

Answer 1

Если вы абсолютно хотите использовать ggplot2, то вы можете использовать масштабирование и маркировку, чтобы работать вокруг ошибки до тех пор, пока не будет исправлено:

# a scaling constant 
s <- 1E120 

# scale Y to get around bug, but then unscale Y's labels 
ggplot(df, aes(x=X, y=Y*s)) + 
    geom_point() + 
    scale_y_continuous(labels=function(x) as.character(x/s)) + 
    ylab("Y")