Value Error when Trying to Plot Filtered Waveforms

[mkohler]

Howdy yall. I am trying to apply a highpass filter to my waveform from a specific earthquake but I cant seem to understand the error that I get when it says that "x and y must have same first dimension." Could anyone explain to me what I'm doing wrong and how I can try to fix it? Here's my code.

import numpy as np
import matplotlib.pyplot as plt

import obspy


# Read the seismogram
#st = obspy.read(r"C:\Users\maddi\Spring Catch-Up\Waveform mseed\Spring Catch-UpGroundMotionM7.0Raw.mseed")
st = client.get_waveforms("II","ERM","00","BHZ", UTCDateTime('2008-07-19 02:39:47'), UTCDateTime('2008-07-19 02:46:00'))

# There is only one trace in the Stream object, let's work on that trace...
tr = st[0]

# Filtering with a lowpass on a copy of the original Trace
tr_filt = tr.copy()
tr_filt.filter('highpass', freq=1.0, corners=2, zerophase=True)

# Now let's plot the raw and filtered data...
t = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
plt.subplot(211)
plt.plot(t, tr.data)
plt.ylabel('Raw Data')
plt.subplot(212)
plt.plot(t, tr_filt.data, 'k')
plt.ylabel('highpassed Data')
plt.xlabel('Time [s]')
plt.suptitle(tr.stats.starttime)
plt.show()

Error:
ValueError                                Traceback (most recent call last)
Cell In[81], line 21
     19 t = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
     20 plt.subplot(211)
---> 21 plt.plot(t, tr.data)
     22 plt.ylabel('Raw Data')
     23 plt.subplot(212)

File ~\anaconda3\envs\obspy\lib\site-packages\matplotlib\pyplot.py:3590, in plot(scalex, scaley, data, *args, **kwargs)
   3582 @_copy_docstring_and_deprecators(Axes.plot)
   3583 def plot(
   3584     *args: float | ArrayLike | str,
   (...)
   3588     **kwargs,
   3589 ) -> list[Line2D]:
-> 3590     return gca().plot(
   3591         *args,
   3592         scalex=scalex,
   3593         scaley=scaley,
   3594         **({"data": data} if data is not None else {}),
   3595         **kwargs,
   3596     )

File ~\anaconda3\envs\obspy\lib\site-packages\matplotlib\axes\_axes.py:1724, in Axes.plot(self, scalex, scaley, data, *args, **kwargs)
   1481 """
   1482 Plot y versus x as lines and/or markers.
   1483 
   (...)
   1721 (``'green'``) or hex strings (``'#008000'``).
   1722 """
   1723 kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D)
-> 1724 lines = [*self._get_lines(self, *args, data=data, **kwargs)]
   1725 for line in lines:
   1726     self.add_line(line)

File ~\anaconda3\envs\obspy\lib\site-packages\matplotlib\axes\_base.py:303, in _process_plot_var_args.__call__(self, axes, data, *args, **kwargs)
    301     this += args[0],
    302     args = args[1:]
--> 303 yield from self._plot_args(
    304     axes, this, kwargs, ambiguous_fmt_datakey=ambiguous_fmt_datakey)

File ~\anaconda3\envs\obspy\lib\site-packages\matplotlib\axes\_base.py:499, in _process_plot_var_args._plot_args(self, axes, tup, kwargs, return_kwargs, ambiguous_fmt_datakey)
    496     axes.yaxis.update_units(y)
    498 if x.shape[0] != y.shape[0]:
--> 499     raise ValueError(f"x and y must have same first dimension, but "
    500                      f"have shapes {x.shape} and {y.shape}")
    501 if x.ndim > 2 or y.ndim > 2:
    502     raise ValueError(f"x and y can be no greater than 2D, but have "
    503                      f"shapes {x.shape} and {y.shape}")

ValueError: x and y must have same first dimension, but have shapes (7461,) and (7460,)

[deanhystad]

The error message is pretty clear.

Error:
ValueError: x and y must have same first dimension, but have shapes (7461,) and (7460,)

The line that raises this error is.

plt.plot(t, tr.data)

So it looks like t and tr.data are not the same size. That points to this line being wrong.

t = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)

I would expect this to be:

t = np.arange(0, tr.stats.npts * tr.stats.delta, tr.stats.delta)

Print out the values for tr.stats.delta and tr.stats.sampling_rate. I don't think tr.stats.delta * tr.stats.sampling_rate == 1. The error is in your data, and a bad assumption in your program. Another, less likely possibility is that tr.stats.npts != len(tr.data).