Mailman 3 September 2019 - yt-users

Access User define function inside the yt derived field
by Prateek Gupta Sept. 16, 2019

Sept. 16, 2019

Hello all, I want to use a user-defined function (say, Maxwell distribution function) with a variable (say, p--momentum, because I want to integrate the function on that variable), and want to use density and temperature field information of each grid. This function applies individually on each grid. Please suggest me the way to do so. This could be very naive to ask but I stuck in it. That function can't be a yt-field (I think) because it has a variable, and if I want to use density and temperature field even after removing units inside the function, it will show an error, because the field is in vector form (3Dim) and the variable is scaler (basically shape miss-match error). I have to use many such functions as post-processing, please suggest me a way to achieve this goal. Many thanks and regards, -Prateek Gupta

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[yt v. 3.5.1] Issue running parallel yt script
by Andrew Cook Sept. 14, 2019

Sept. 14, 2019

Hello! I'm having issues running a yt 3.5.1 script to process an OffAxisProjectionPlot of some Enzo 2.5 data. Running mpi 4.0.1 I get this error: File "plot_time.py", line 28, in <module> val, loc = ds.find_max('density') File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/static_output.py", line 826, in find_max source.quantities.max_location(field) File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/derived_quantities.py", line 635, in __call__ rv = super(MaxLocation, self).__call__(field, sample_fields) File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/derived_quantities.py", line 591, in __call__ rv = super(SampleAtMaxFieldValues, self).__call__(field, sample_fields) File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/derived_quantities.py", line 68, in __call__ for sto, ds in parallel_objects(chunks, -1, storage = storage): File "/opt/apps/pkgs/yt/3.5.1/src/yt/utilities/parallel_tools/parallel_analysis_interface.py", line 520, in parallel_objects to_share, datatype = 'dict', op = 'join') File "/opt/apps/pkgs/yt/3.5.1/src/yt/utilities/parallel_tools/parallel_analysis_interface.py", line 284, in passage return func(self, *args, **kwargs) File "/opt/apps/pkgs/yt/3.5.1/src/yt/utilities/parallel_tools/parallel_analysis_interface.py", line 723, in par_combine_object data.update(self.comm.recv(source=i, tag=0)) File "mpi4py/MPI/Comm.pyx", line 1173, in mpi4py.MPI.Comm.recv File "mpi4py/MPI/msgpickle.pxi", line 302, in mpi4py.MPI.PyMPI_recv File "mpi4py/MPI/msgpickle.pxi", line 261, in mpi4py.MPI.PyMPI_recv_match P000 yt : [ERROR ] 2019-09-14 12:26:53,382 Exception: MPI_ERR_INTERN: internal error P000 yt : [ERROR ] 2019-09-14 12:26:53,383 Error occured on rank 0. I know that someone posted a similar error recently but I don't think there was a solid solution to the problem. If anyone can help please let me know. Also i'm sorry if I didn't explain this well enough, please let me know if anything is not clear. Many thanks Andy

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Magnetic flux over a disk
by Guido Granda Muñoz Sept. 11, 2019

Sept. 11, 2019

Hello, I want to compute the magnetic flux over a disk which length is the minimum possible i.e. the resolution. I wanted to approximate this quantity using : sp=ds.disk(center,normal,(1,'pc'),(1*res,'pc')) flux=sp.calculate_flux("sqrt_magx","sqrt_magy","sqrt_magz","sqrt_magx") Where I defined the quantities sqrt_magx (root square of the magnetic field along the x direction) with units of Gauss^0.5, so the output of calculate_flux has Gauss*cm^2 units. However, it is not possible to use calculate_flux on YTDisks and only calculate_isocontour_flux is available for this data container. Do you know how I can obtain exactly the same result for the magnetic flux using the available calculate_isocontour_flux instead of the calculate_flux function? Cheers,

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SlicePlot error
by Sam Patrick Sept. 11, 2019

Sept. 11, 2019

Hi all, I've been encountering an error recently whenever I try to save a slice plot, such as: data_sets = yt.load("DD*/output_[0-9][0-9][0-9][0-9]") for ds in data_sets: filename = "density_t={:.3f}_ho.png".format(ds.current_time.in_units('Myr').value) val, loc = ds.find_max('density') print("{:.3f}".format(val)) plt = yt.SlicePlot(ds, L, field, center= loc, width= (size, 'pc')) plt.save(filename) YT seems to think issue is with the call to 'find_max' but a little experimentation shows this is not the case. I'm unable to work out any of what comes back to me asides that: File "plot.py", line 67, in <module> val, loc = ds.find_max('density') File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/static_output.py", line 826, in find_max source.quantities.max_location(field) File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/derived_quantities.py", line 635, in __call__ rv = super(MaxLocation, self).__call__(field, sample_fields) File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/derived_quantities.py", line 591, in __call__ rv = super(SampleAtMaxFieldValues, self).__call__(field, sample_fields) File "/opt/apps/pkgs/yt/3.5.1/src/yt/data_objects/derived_quantities.py", line 68, in __call__ for sto, ds in parallel_objects(chunks, -1, storage = storage): File "/opt/apps/pkgs/yt/3.5.1/src/yt/utilities/parallel_tools/parallel_analysis_interface.py", line 520, in parallel_objects to_share, datatype = 'dict', op = 'join') File "/opt/apps/pkgs/yt/3.5.1/src/yt/utilities/parallel_tools/parallel_analysis_interface.py", line 284, in passage return func(self, *args, **kwargs) File "/opt/apps/pkgs/yt/3.5.1/src/yt/utilities/parallel_tools/parallel_analysis_interface.py", line 723, in par_combine_object data.update(self.comm.recv(source=i, tag=0)) File "mpi4py/MPI/Comm.pyx", line 1173, in mpi4py.MPI.Comm.recv File "mpi4py/MPI/msgpickle.pxi", line 302, in mpi4py.MPI.PyMPI_recv File "mpi4py/MPI/msgpickle.pxi", line 261, in mpi4py.MPI.PyMPI_recv_match Many thanks, Sam Patrick

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min_level and level_stats of a data container
by Guido granda muñoz Sept. 10, 2019

Sept. 10, 2019

Hello Yt users, I'm trying to obtain the maximum and minimum level of refinement of a data container in a simulation. What I am doing is the following: ds=yt.load(bname) sp_open=ds.disk(center,normal,radius,(res,'pc')) # smallest disk possible Where bname is the name of the snapshot, center, normal, radius, and res, are the desired center, normal, radius and height of the disk. I chose the resolution of the simulation as the height of the disk because I want it to represent a disk-like differential area and I the disk is located at the region of highest level of refinement. I tried to obtain the minimum and maximum levels of refinement over the sp_open subregion, however only max_level is implemented doing: sp_open.index.max_level Do you know how I can obtain the minimum level of refinement of a data container of a sub-region? Besides, when I print the level statistics of the subregion and the ones of the whole computational volume I get the same output. I print them using: sp_open.index.level_stats # subregion ds.index.level_stats # computational volume And I get: rec.array([( 1, 512, 0), ( 8, 4096, 1), ( 64, 32768, 2), ( 512, 262144, 3), ( 4096, 2097152, 4), (32768, 16777216, 5), ( 0, 0, 6), ( 0, 0, 7), ( 0, 0, 8), ( 0, 0, 9), ( 0, 0, 10), ( 0, 0, 11), ( 0, 0, 12), ( 0, 0, 13), ( 0, 0, 14), ( 0, 0, 15), ( 0, 0, 16), ( 0, 0, 17), ( 0, 0, 18), ( 0, 0, 19), ( 0, 0, 20), ( 0, 0, 21), ( 0, 0, 22), ( 0, 0, 23), ( 0, 0, 24), ( 0, 0, 25), ( 0, 0, 26), ( 0, 0, 27), ( 0, 0, 28), ( 0, 0, 29), ( 0, 0, 30), ( 0, 0, 31), ( 0, 0, 32), ( 0, 0, 33), ( 0, 0, 34), ( 0, 0, 35), ( 0, 0, 36), ( 0, 0, 37), ( 0, 0, 38), ( 0, 0, 39), ( 0, 0, 40), ( 0, 0, 41), ( 0, 0, 42), ( 0, 0, 43), ( 0, 0, 44), ( 0, 0, 45), ( 0, 0, 46), ( 0, 0, 47)], dtype=[('numgrids', '<i8'), ('numcells', '<i8'), ('level', '<i8')]) Which does not make sense to me, because the sub-region level statistics should not include coarse grids, even though this sub-region is in fact inside lower refinement regions. Shouldn't this statistics just print the lowest and highest refinement level inside the sub-region ? Thank you, -- Guido

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yt project calendar
by Britton Smith Sept. 9, 2019

Sept. 9, 2019

Greetings! We have created google calendar to keep track of yt project-related events. We'll post team meetings, workshops, or other events when people from yt are getting together. If you'd like to view it or add to your own calendar click here <https://calendar.google.com/calendar?cid=ZjJsaGJhcXAzcGRkY2xmNjRvN3RkNDBkbj…> . Britton

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AWS Certified SysOps Associate
by Kuldeep Tiwari Sept. 5, 2019

Sept. 5, 2019

Amazon has built a huge global infrastructure with 22 regions and 69 availability zones. All companies around the globe can use this globally present infrastructure to host their resources and hence they need certified, talented and skilled employees. The said expertise can only be achieved after studying the AWS Certified SysOps Associate course in Pune from a certified cloud instructor. AWS Certified SysOps Associate Training course in Pune helps one learn and understand, validate and demonstrate the expertise of hosting scalable, cost-effective and ultra-robust applications in the amazon cloud. Engineers certified on AWS Certified SysOps Associate can design a cloud infrastructure based on customer’s demand and budget. The certified engineers on AWS Certified SysOps Associate have a much upper hand as they will also be able to design a much secure and efficient infrastructure that RTO and RPO and other SLA objectives that large enterprises depend on. https://www.sevenmentor.com/aws-sysops-training-in-pune.php

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