Checkout my page
djpugh / mtfit Goto Github PK
View Code? Open in Web Editor NEWMTfit code for Bayesian Moment Tensor Fitting
MTfit code for Bayesian Moment Tensor Fitting
Checkout my page
Please fill in the following details as much as possible when submitting your issue as this will help with testing and reproducing the issue
use (print(MTfit.get_details_json()))
in a python terminal (or MTfit --details
from the command line)
I studied your paper Pugh et al. 2016 A Bayesian method for microseismic source inversion
where you list in appendix A the station propagation coefficients. Thanks a lot for this! Nevertheless, I was comparing your notation from the paper with the station_angles function implementation in inversion.py l. https://github.com/djpugh/MTfit/blob/develop/src/MTfit/inversion.py#L3217
Some of these lines are vastly inconsistent with the equations from the paper. Do you use a different coordinate system here or other transformations, that I did not find? Thanks a lot for your response!
Consistent implementation to paper.
What do we need to do to reproduce the issue?
Please fill in the following details as much as possible when submitting your issue as this will help with testing and reproducing the issue
{
"python version info": "sys.version_info(major=2, minor=7, micro=9, releaselevel='final', serial=0)",
"num_threads": 8,
"python version": "2.7.9 (default, Sep 14 2019, 20:00:08) \n[GCC 4.9.2]",
"c_extensions present": [
"cmarkov_chain_monte_carlo",
"cprobability",
"cmoment_tensor_conversion",
"cscatangle"
],
"platform": "linux2",
"dependency info": {
"cython": "0.29.21",
"pyqsub": "unknown",
"scipy": "0.14.0",
"numpy": "1.16.6",
"matplotlib": "1.4.2"
},
"version": "1.0.5"
}
ERROR:MTfit.probability:Error running cython code
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/MTfit/probability/probability.py", line 871, in ln_marginalise
return cprobability.ln_marginalise(ln_pdf.astype(np.float64))
File "src/MTfit/probability/cprobability.pyx", line 130, in MTfit.probability.cprobability.ln_marginalise
ValueError: Buffer has wrong number of dimensions (expected 2, got 1)
ERROR:MTfit.probability:Error running cython code
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/MTfit/probability/probability.py", line 1269, in exp
return cprobability.ln_exp(self._ln_pdf)
File "src/MTfit/probability/cprobability.pyx", line 1817, in MTfit.probability.cprobability.ln_exp
ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
Solve the issue
This issue comes up once inversion has started and it's blocking solutions.
{
"version": "1.0.6a5",
"c_extensions present": [
"cprobability",
"cmoment_tensor_conversion"
],
"platform": "darwin",
"num_threads": 4,
"python version": "3.7.4 (default, Aug 13 2019, 15:17:50) \n[Clang 4.0.1 (tags/RELEASE_401/final)]",
"python version info": [
3,
7,
4,
"final",
0
],
"dependency info": {
"numpy": "1.17.2",
"scipy": "1.3.1",
"matplotlib": "3.1.1",
"cython": "0.29.13",
"sphinx": "2.2.0",
"h5py": "2.9.0"
}
}
1
python setup.py build-docs
invalid command name 'build-docs'
2.
python setup.py testFAILED (errors=1)Test failed: <unittest.runner.TextTestResult run=1 errors=1 failures=0>error: Test failed: <unittest.runner.TextTestResult run=1 errors=1 failures=0> 3.
import MTfit
MTfit.run_tests()
Traceback (most recent call last): File "", line 1, in AttributeError: module 'MTfit' has no attribute 'run_tests'
I did not have any error for installing. I created the c files with cython on the src directory and I can import MTfit correctly in terminal and python scipt. But in python it is not recognized aby atribute (eg. MTfit.run() , inversion=MTfit.Inversion(*args,**kwargs) , etc. )
What do we need to do to reproduce the issue?
just in a python enviroment write import MTfit and then try to call any attribute MTfit.run_tests()
I thought there was a test for the examples to run them through, but not sure where it's got to in the reorganisation - need to find it again and re-implement it within tox
Hi David,
The following moment tensor configuration plots incorrectly and produces the incorrect fault planes
mt = np.array([[0.0, 0.0, 0.0], [0.0, 0.0, -1.0], [0.0, -1.0, 0.0]])
a = mtfit.convert.MT33_SDR(np.array(mt))
print("a", np.degrees(a))
Seems like there is some numerical issue for this particular case. Most other MT configurations seem to work ok.
Hi David,
currently missing 'src/mtfit/probability/cprobability.c' on install.
Current return from running 'python setup.py install'
running install running bdist_egg running egg_info writing requirements to src/mtfit.egg-info/requires.txt writing src/mtfit.egg-info/PKG-INFO writing top-level names to src/mtfit.egg-info/top_level.txt writing dependency_links to src/mtfit.egg-info/dependency_links.txt writing entry points to src/mtfit.egg-info/entry_points.txt reading manifest file 'src/mtfit.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' writing manifest file 'src/mtfit.egg-info/SOURCES.txt' installing library code to build/bdist.linux-x86_64/egg running install_lib running build_py UPDATING build/lib.linux-x86_64-2.7/mtfit/_version.py set build/lib.linux-x86_64-2.7/mtfit/_version.py to '1.0.0+5.g750c2a6' running build_ext building 'mtfit.probability.cprobability' extension gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/jds70/miniconda2/lib/python2.7/site-packages/numpy/core/include -I/home/jds70/miniconda2/include/python2.7 -c src/mtfit/probability/cprobability.c -o build/temp.linux-x86_64-2.7/src/mtfit/probability/cprobability.o -O3 -march=native gcc: error: src/mtfit/probability/cprobability.c: No such file or directory gcc: fatal error: no input files compilation terminated. error: command 'gcc' failed with exit status 4
Add pip install info in docs
Raised by Jesse Hutchinson
File "/opt/antelope/python2.7.8/lib/python2.7/site-packages/matplotlib/artist.py", line 881, in _update_property
raise AttributeError('Unknown property %s' % k)
AttributeError: Unknown property show_max
I tried removing the show_max argument from the script, and I no longer experienced a crash. After going through the code, I found a values called ‘show_max_likelihood’.
Travis CI can't build windows wheels so need to manually build and publish the wheels
Automatic wheel building in the build steps using e.g. appveyor
Raised by Jesse Hutchinson -
It turned out that installing from pip led to many of the references to MTfit to be mtfit. When installing from the Github zip with setup.py, I didn’t experience the same issue.
Please fill in the following details as much as possible when submitting your issue as this will help with testing and reproducing the issue
{
"version": "1.0.5",
"c_extensions present": [
"cmarkov_chain_monte_carlo",
"cprobability",
"cmoment_tensor_conversion",
"cscatangle"
],
"platform": "darwin",
"num_threads": 8,
"python version": "3.7.1 (default, Dec 14 2018, 13:28:58) \n[Clang 4.0.1 (tags/RELEASE_401/final)]",
"python version info": [
3,
7,
1,
"final",
0
],
"dependency info": {
"numpy": "1.15.4",
"scipy": "1.1.0",
"matplotlib": "3.0.2",
"cython": "0.29.2",
"sphinx": "1.8.2",
"h5py": "2.8.0"
}
}
Error running cython code
Traceback (most recent call last):
File "/Users/jesse/anaconda3/lib/python3.7/site-packages/MTfit/probability/probability.py", line 871, in ln_marginalise
return cprobability.ln_marginalise(ln_pdf.astype(np.float64))
File "src/MTfit/probability/cprobability.pyx", line 130, in MTfit.probability.cprobability.ln_marginalise
ValueError: Buffer has wrong number of dimensions (expected 2, got 1)
Error running cython code
Traceback (most recent call last):
File "/Users/jesse/anaconda3/lib/python3.7/site-packages/MTfit/probability/probability.py", line 1269, in exp
return cprobability.ln_exp(self._ln_pdf)
File "src/MTfit/probability/cprobability.pyx", line 1817, in MTfit.probability.cprobability.ln_exp
ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
To not get the errors, hopefully!
This occurs after every inversion I have attempted. I could send in the input pickle file to see if the issue can be reproduced.
Dear djpugh
Me and my team would like to include the algorithm to automatic determination of Polarity in "Integrated Seismic Program":
Pugh, D J, White, R S and Christie, P A F, 2016b, Automatic Bayesian polarity determination, GJI, 206(1), 275-291.
However, I cannot find it anywhere. Please do you mind let a link to download it or send it this via,
Thank you very much in advance!
Best Regards,
Roberto Cabieces
krafla_axample.py now runs fine in parallel but, as it finishes, the following error is thrown:
Traceback (most recent call last):
File "/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.54.g931200b-py3.6-linux-x86_64.egg/mtfit/inversion.py", line 2485, in _random_sampling_forward
MTs, end = self._parse_job_result(result)
File "/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.54.g931200b-py3.6-linux-x86_64.egg/mtfit/inversion.py", line 2804, in _parse_job_result
return self.algorithm.iterate(job_result)
File "/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.54.g931200b-py3.6-linux-x86_64.egg/mtfit/algorithms/monte_carlo.py", line 103, in iterate
self.pdf_sample.append(**result)
File "/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.54.g931200b-py3.6-linux-x86_64.egg/mtfit/sampling.py", line 88, in append
elif not isinstance(ln_pdf, (float, long, int, np.float64, np.float32)) and moment_tensors.shape[1] != ln_pdf.shape[1]:
AttributeError: 'dict' object has no attribute 'shape'
--------
DC inversion complete, elapsed time: 184.96504020690918
Worker-1 Ending
This is Ubuntu 14.04, python 3.6. Haven't tried on py 2.7 yet.
Please fill in the following details as much as possible when submitting your issue as this will help with testing and reproducing the issue
{
"version": "1.0.5",
"c_extensions present": [
"cmarkov_chain_monte_carlo",
"cprobability",
"cmoment_tensor_conversion",
"cscatangle"
],
"platform": "darwin",
"num_threads": 8,
"python version": "3.7.1 (default, Dec 14 2018, 13:28:58) \n[Clang 4.0.1 (tags/RELEASE_401/final)]",
"python version info": [
3,
7,
1,
"final",
0
],
"dependency info": {
"numpy": "1.15.4",
"scipy": "1.1.0",
"matplotlib": "3.0.2",
"cython": "0.29.2",
"sphinx": "1.8.2",
"h5py": "2.8.0"
}
}
Warning: divide by zero encountered in log
Cython Error
Traceback (most recent call last):
File "/Users/jesse/anaconda3/lib/python3.7/site-packages/MTfit/algorithms/markov_chain_monte_carlo.py", line 1582, in _acceptance_check
dc_prior=getattr(self, 'dc_prior', 0.))
TypeError: Argument 'x' has incorrect type (expected list, got dict)
This causes the program to stop, should be performing an McMC inversion. The regular 'iterate' algorithm works fine.
Run an McMC inversion using the following parameters:
algorithm = 'mcmc'
dc = False
parallel = False
phys_mem = 1
output_format = 'pickle'
conversion = False
inversion_options = ['PPolarity','P/SHAmplitudeRatio']
burn_length = 30000
chain_length = 100000
min_acceptance_rate = 0.1
max_acceptance_rate = 0.3
inversion_object = Inversion(event,algorithm=algorithm, dc=dc,parallel=parallel,phys_mem=phys_mem,convert=conversion,output_format=output_format, inversion_options=inversion_options, burn_length=burn_length,chain_length=chain_length, min_acceptance_rate=min_acceptance_rate,max_acceptance_rate=max_acceptance_rate)
inversion_object.forward()
Tox tests don't seem to be fully running
Want to automatically build and publish gh-pages but currently include epub/pdf and unable to compile latex automatically
Traceback (most recent call last):
File "build_docs.py", line 283, in build_docs
build_pdf()
File "build_docs.py", line 340, in build_pdf
p = subprocess.Popen(['pdflatex', '-interaction=nonstopmode', 'MTfit.tex'], stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
File "/opt/python/3.6.3/lib/python3.6/subprocess.py", line 709, in __init__
restore_signals, start_new_session)
File "/opt/python/3.6.3/lib/python3.6/subprocess.py", line 1344, in _execute_child
raise child_exception_type(errno_num, err_msg, err_filename)
FileNotFoundError: [Errno 2] No such file or directory: 'pdflatex': 'pdflatex'
pdflatex to be installed/available (docker image?)
There's a deprecation warning occuring in cprobability
- combined_ln_pdf
function which needs investigation (I think it is line 1499 that is causing the problem, but this needs a bit more debugging.
Remove old references to MTINV
More of a question than an issue, but as autopol
is referenced in the docs, are there plans to provide access to that or a link to where it lives?
Want to setup build scripts for building a release
Please fill in the following details as much as possible when submitting your issue as this will help with testing and reproducing the issue
use (print(MTfit.get_details_json()))
in a python terminal (or MTfit --details
from the command line)
{
"version": "1.0.5",
"c_extensions present": [
"cprobability",
"cmoment_tensor_conversion"
],
"platform": "win32",
"num_threads": 12,
"python version": "3.7.3 (default, Mar 27 2019, 17:13:21) [MSC v.1915 64 bit (AMD64)]",
"python version info": [
3,
7,
3,
"final",
0
],
"dependency info": {
"numpy": "1.16.2",
"scipy": "1.2.1",
"matplotlib": "3.1.1",
"cython": "0.29.6",
"sphinx": "1.8.5",
"h5py": "2.9.0"
},
"windows version": [
10,
0,
17134,
2,
""
]
}
two gridlines on hudson plot are off
all gridlines in their correct place
What do we need to do to reproduce the issue?
MTfit.plot.MTplot(np.array([[1],[0],[-1],[0],[0],[0]]),'hudson',text=True)
Scale factors not working correctly with location uncertainty
Extensions documentation is not tidied and needs some fixing with the updated module structure
A lot of output is done using print (and verbosity) - use logging instead
tox tests can throw errors in a few tests, and test_single_life
can also throw errors in python setup.py test
Css/JS not present
CSS/JS to be pushed via deploy
I ask because the installation instructions I find here:
https://djpugh.github.io/MTfit/setup.html#running-the-test-suite
do not seem to correspond with the repo I just cloned from:
https://github.com/djpugh/MTfit.git
setup.py does not recognize build-docs or build-ext so neither of those work.
e.g.,
python setup.py build-docs
invalid command name 'build-docs'
Thx!
No response
First off, the amount of documentation for MTfit is really excellent. Thank you for putting in the time. It makes the package accessible to a wider audience.
There are a couple of places where the input parameters could benefit from additional details.
On the following page: https://djpugh.github.io/MTfit/inversion.html
Azimuth: numpy matrix of azimuth values in degrees
Is this from station to earthquake or earthquake to station?
Measured: numpy matrix of corrected numerator and denominator amplitude ratio observations, needs to have two columns, one for the numerator and one for the denominator.
In the Pugh et al., 2016 paper, there is a correction (Z) based on the Vp/Vs ratio that is applied to the numerator of the ratio (equation 36). Is this what you mean by the "corrected numerator"? Or are you referring to a Q correction? Note: we are assuming a constant Vp/Vs.
Error: numpy matrix of uncertainty (standard deviation) in the amplitude ratio observations, needs to have two columns, one for the numerator and one for the denominator.
Back to equation 37 of the Pugh et al., 2016 paper, the standard deviation of the individual waves is normalized by the amplitude. Should this correction be applied for the standard deviations for the "error" input, or is this taken care of with theoretical amplitudes inside the code?
Raised by Jesse Hutchinson - Here is the output from my terminal:
In [7]: >>> import MTfit.plot as plot
In [8]: >>> import numpy as np
In [9]: >>> plot.MTplot(np.array([[1],[0],[-1],[0],[0],[0]]),'beachball',
...: fault_plane=True)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-9-dc0ffaf1a397> in <module>()
1 plot.MTplot(np.array([[1],[0],[-1],[0],[0],[0]]),'beachball',
----> 2 fault_plane=True)
/opt/antelope/python2.7.8/lib/python2.7/site-packages/MTfit-develop-py2.7-macosx-10.4-x86_64.egg/MTfit/plot/plot_classes.pyc in __init__(self, MTs, plot_type, stations, plot, label, save_file, save_dpi, *args, **kwargs)
894 # initialisation arguments
895 if plot:
--> 896 self.plot(**kwargs)
897
898 def _prep_data(self, param, name):
/opt/antelope/python2.7.8/lib/python2.7/site-packages/MTfit-develop-py2.7-macosx-10.4-x86_64.egg/MTfit/plot/plot_classes.pyc in plot(self, *args, **kwargs)
954 """
955 for plot_class in self.plot_classes:
--> 956 plot_class(*args, **kwargs)
957 self.fig.patch.set_facecolor('w')
958 if self.show:
/opt/antelope/python2.7.8/lib/python2.7/site-packages/MTfit-develop-py2.7-macosx-10.4-x86_64.egg/MTfit/plot/plot_classes.pyc in __call__(self, *args, **kwargs)
1070 Plots the result
1071 """
-> 1072 self.plot(*args, **kwargs)
1073
1074 def plot(self, MTs=False, *args, **kwargs):
/opt/antelope/python2.7.8/lib/python2.7/site-packages/MTfit-develop-py2.7-macosx-10.4-x86_64.egg/MTfit/plot/plot_classes.pyc in plot(self, MTs, *args, **kwargs)
1095 'text', 'colormap', 'linewidth',
1096 'hex_bin']}
-> 1097 handle = self._ax_plot(*args, **plot_kwargs)
1098 self._background(handle)
1099 if self.show:
/opt/antelope/python2.7.8/lib/python2.7/site-packages/MTfit-develop-py2.7-macosx-10.4-x86_64.egg/MTfit/plot/plot_classes.pyc in _ax_plot(self, *args, **kwargs)
1950 # self.ydata = self.ydata[np.isfinite(self.ydata)] #
1951 # print(len(self.xdata),len(self.ydata),len(self.zdata))
-> 1952 return self._surf_plot(self.xdata, self.ydata, self.zdata, self.cdata, *args, **kwargs)
1953
1954 def _background(self, handle):
/opt/antelope/python2.7.8/lib/python2.7/site-packages/MTfit-develop-py2.7-macosx-10.4-x86_64.egg/MTfit/plot/plot_classes.pyc in _surf_plot(self, x, y, z, c, zorder, **kwargs)
1161 """
1162 if self.dimension < 3:
-> 1163 return self._2d_surf_plot(x, y, c, **kwargs)
1164 return self._3d_surf_plot(x, y, z, c, **kwargs)
1165
/opt/antelope/python2.7.8/lib/python2.7/site-packages/MTfit-develop-py2.7-macosx-10.4-x86_64.egg/MTfit/plot/plot_classes.pyc in _2d_surf_plot(self, x, y, c, zorder, **kwargs)
1258 kwargs.pop('colormap', None)
1259 kwargs.pop('bins', None)
-> 1260 return self.ax.pcolormesh(x, y, c, cmap=self.colormap, shading='flat', zorder=zorder, **kwargs)
1261
1262 def _2d_scatter_plot(self, x, y, c, marker='.', markersize=10, zorder=0, **kwargs):
/opt/antelope/python2.7.8/lib/python2.7/site-packages/matplotlib/__init__.pyc in inner(ax, *args, **kwargs)
1853 "the Matplotlib list!)" % (label_namer, func.__name__),
1854 RuntimeWarning, stacklevel=2)
-> 1855 return func(ax, *args, **kwargs)
1856
1857 inner.__doc__ = _add_data_doc(inner.__doc__,
/opt/antelope/python2.7.8/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in pcolormesh(self, *args, **kwargs)
5928 allmatch = (shading == 'gouraud')
5929
-> 5930 X, Y, C = self._pcolorargs('pcolormesh', *args, allmatch=allmatch)
5931 Ny, Nx = X.shape
5932 X = X.ravel()
/opt/antelope/python2.7.8/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in _pcolorargs(funcname, *args, **kw)
5539 if np.ma.is_masked(X) or np.ma.is_masked(Y):
5540 raise ValueError(
-> 5541 'x and y arguments to pcolormesh cannot have '
5542 'non-finite values or be of type '
5543 'numpy.ma.core.MaskedArray with masked values')
ValueError: x and y arguments to pcolormesh cannot have non-finite values or be of type numpy.ma.core.MaskedArray with masked values
I traced down the exact line where the issue comes up. After line 1952, above which I believe is 1950 in the original version of the script, has non-finite values for xdata and ydata. Earlier in the script, the values of x and y are finite, so I believe _2d_surf_plot command is altering the xdata and ydata values. I just used a very simple input here, so that shouldn’t be the problem. I haven’t been able to figure out what the solution would be.
Hi David,
I've been having a go at the tutorial data and have been running into issues when running with multiprocessing. The examples work fine on a single thread.
I've compiled from the most recent commits to develop (as of about 24 hours ago) and have run into the same issue on both py 2.7 and 3.6, in separate conda envs.
I ran mtfit from the command prompt like so:
mtfit --location_pdf_file_path=krafla_event.scatangle --algorithm=iterate -m=1 --double-couple -n 5 --max_samples=100000 -i=PPolarity --convert --bin_scatangle -V 4 krafla_event_data_py36.inv
krafla_event_data_py36.inv was pickled with:
from example_data import krafla_event
data = krafla_event()
pickle.dump(data, open('krafla_event_data_py36.inv', 'wb'))
This being multiprocessing, the traceback isn't very useful, but here it is anyways:
*********
Event 1
--------
UID: krafla_event
Number of Random Samples: 49823 with 26372 location samples and 20 stations
Iterate algorithm chosen, maximum samples: 100000
Initialisation Complete
Beginning Inversion
/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.51.g44ce305.dirty-py3.6-linux-x86_64.egg/mtfit/inversion.py:200: DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.
marginalised=int(self.marginalise), location_samples_multipliers=ln_location_sample_multipliers)
/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.51.g44ce305.dirty-py3.6-linux-x86_64.egg/mtfit/inversion.py:200: DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.
marginalised=int(self.marginalise), location_samples_multipliers=ln_location_sample_multipliers)
/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.51.g44ce305.dirty-py3.6-linux-x86_64.egg/mtfit/inversion.py:200: DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.
marginalised=int(self.marginalise), location_samples_multipliers=ln_location_sample_multipliers)
/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.51.g44ce305.dirty-py3.6-linux-x86_64.egg/mtfit/inversion.py:200: DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.
marginalised=int(self.marginalise), location_samples_multipliers=ln_location_sample_multipliers)
/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/site-packages/mtfit-0+untagged.51.g44ce305.dirty-py3.6-linux-x86_64.egg/mtfit/inversion.py:200: DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.
marginalised=int(self.marginalise), location_samples_multipliers=ln_location_sample_multipliers)
Traceback (most recent call last):
File "/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/multiprocessing/queues.py", line 234, in _feed
obj = _ForkingPickler.dumps(obj)
File "/home/chet/anaconda3/envs/mtfit_36/lib/python3.6/multiprocessing/reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
TypeError: 'NoneType' object is not callable
Which, I guess points to an issue with pickling the data before they're passed to the Pool, but I haven't the foggiest what the actuall issue would be.
All 5 jobs encounter this error and cease working, but no cleanup is done and the process hangs up.
I'm having a go at debugging, but I wanted to leave this here on the off chance that you had a hunch as to what was causing this.
-Chet
Current argparsing is not very nicely/pythonically implemented, use click
to handle the argparsing
Setup the CI scripts to run and build MTfit
Hi again David,
I'm looking at a seismic warm with near-repeating waveforms. Polarity / amplitude data are sparse, so I'd like to compute a single moment tensor / focal mechanism for all events using all available polarities.
I really like using the NLLoc take-off angle uncertainties to compute the range of focal mechanisms, but I was wondering how easy it might be to do this for multiple events? I.e. to read multiple NLL .hyp files to compute a single composite moment tensor? Do you have any thoughts on whether you think this might be feasible?
Thanks!
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