chrishavlin

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:

chrishavlin

draft_yt_notes.py

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 

chrishavlin

'''
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

chrishavlin

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;

chrishavlin

"""
to store:

    $ python manual_grid_val_test.py 1

to compare

    $ python manual_grid_val_test.py 0

"""

chrishavlin

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.

chrishavlin

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:

chrishavlin

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')

chrishavlin

import sys

import numpy as np
import yt

import yt_idv

# yt reminder: phi is the polar angle (0 to 2pi)
# theta is the angle from north (0 to pi)

chrishavlin

diff --git a/yt/_typing.py b/yt/_typing.py
index 0062c63dd..15fcd8a6f 100644
--- a/yt/_typing.py
+++ b/yt/_typing.py
@@ -1,4 +1,4 @@
-from typing import List, Optional, Tuple, Union
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 import unyt as un
 from numpy import ndarray