| import yt | |
| ds = yt.load_sample("gizmo_64") # 3ish GB download | |
| center = ds.domain_center.to('Mpc').d | |
| z_hat_original = ds.arr([0.3, 0.3, 0.3], 'kpc') | |
| y_hat_original = ds.arr([1., 0., 0.], 'kpc') | |
| for x_loc in list(range(2,19,1)): | |
| c = ((x_loc, center[1], center[2]), 'Mpc') |
| import numpy as np | |
| import yt.utilities.linear_interpolators as lin | |
| from yt.testing import fake_random_ds | |
| import time | |
| import matplotlib.pyplot as plt | |
| times_3d_eval = [] | |
| times_3d_init = [] | |
| Nvals_3d = 2 ** np.arange(3, 9) | |
| for n in Nvals_3d: |
| import yt | |
| from yt.units import Mpc | |
| from yt.visualization.api import Streamlines | |
| from yt.visualization.volume_rendering.api import LineSource | |
| import numpy as np | |
| # streamline alpha value: determines opacity of LineSource | |
| # objects. A bit of trial and error to pick a good value | |
| # so that both the volume rendering and the lines show up. | |
| # this value works for the transfer function used below. |
| """ | |
| to store: | |
| $ python manual_grid_val_test.py 1 | |
| to compare | |
| $ python manual_grid_val_test.py 0 | |
| """ |
| function manual_lau_holtzman_fig2() | |
| % recreate fig 2 of lau and holtzman 2019 grl | |
| % https://doi.org/10.1029/2019GL083529 | |
| beta = 1e-4 | |
| alf = 1/3 | |
| Mu_in = 60*1e9; | |
| eta_ss = 1.8922e+21; | |
| tau_M = eta_ss / Mu_in; |
| ''' | |
| this takes the backup file from the Fast Notepad android app and saves every | |
| note as an individual file. loses info on folder hierarchy, it probably is | |
| buggy and may need tweaking but it was sufficient for my purposes... | |
| Requirements: | |
| python 3+ | |
| To use: | |
| 1. edit the fname, output_dir and output_format vars below |
A script for initially drafting release notes for yt.
Most of the code is from @neutrinoceros, with some minor updates from @chrishavlin.
It's designed to run with uv. To run directly off of this gist, use the url you get when vewing the raw draft_yt_release_notes.py and supply --help to see the command line options:
uv run https://gist.githubusercontent.com/chrishavlin/248adea4296abb7bcdbaac952f304cf0/raw/fc3443b281fea40f195c563aeddbc722fac4408a/draft_yt_release_notes.py --help
| addpath(getenv('vbrdir')) | |
| vbr_init | |
| %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
| % equilibrium partitioning | |
| % | |
| % solidii are in terms of volatile concentration in the | |
| % fluid phase. Can use equilibrium partitioning to estimate | |
| % | |
| % mass conservation: |