Skip to content

Commit

Permalink
add forgotted data file
Browse files Browse the repository at this point in the history
  • Loading branch information
@slayoo
slayoo committed Feb 13, 2024
1 parent 733a9e1 commit ae3824e
Showing 1 changed file with 392 additions and 0 deletions.
392 changes: 392 additions & 0 deletions examples/PySDM_examples/deJong_Azimi/cloudy_data_0d.py
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1,392 @@
import numpy as np

MOM_data = {
"Golovin": {
"t": np.array(
[
0.0,
10.0,
20.0,
30.0,
40.0,
50.0,
60.0,
70.0,
80.0,
90.0,
100.0,
110.0,
120.0,
]
),
"aM0": np.array(
[
100.0,
60.41666666666108,
36.50173611110569,
22.05313223379227,
13.32376739124922,
8.049776132212969,
4.863406413211965,
2.938308041315548,
1.775227774961471,
1.072533447372555,
0.6479889577875856,
0.39149332866333514,
0.23652721940076313,
]
),
"aM1": np.array(
[
10.0,
10.0,
10.0,
10.000000000000002,
10.000000000000002,
9.999999999999991,
10.000000000000007,
10.000000000000002,
9.999999999999956,
9.999999999999966,
9.999999999999872,
10.000000000000062,
10.000000000000108,
]
),
"aM2": np.array(
[
2.0,
5.333333333333704,
14.222222222223586,
37.92592592592996,
101.13580246914695,
269.69547325105935,
719.1879286694924,
1917.8344764519795,
5114.225270538599,
13637.934054769523,
36367.82414605215,
96980.86438947004,
258615.63837192673,
]
),
"aDists": np.array(
[
[100.0, 0.1, 1.0],
[4.863406413211965, 69.86262088575636, 0.029431646782264554],
[0.2365272194007631, 25819.285405029976, 0.0016374749145528168],
]
),
"bM0": np.array(
[
[
100.0,
56.396636657301194,
31.895287187247146,
18.294957761981376,
10.660817516471703,
6.290591039424345,
3.7443020392268367,
2.2413636351719695,
1.3464994349989194,
0.8107024270698977,
0.48877185047542177,
0.2949239965078066,
0.17804598720980272,
],
[
1.0e-6,
4.0200190988219875,
4.606433069139865,
3.758158525366545,
2.6629362775448184,
1.7591745237414111,
1.1190966122081454,
0.696938913153295,
0.42872454995378795,
0.2618284523381802,
0.15921539069060084,
0.09656819650467219,
0.058480487065190184,
],
]
),
"bM1": np.array(
[
[
10.0,
6.354890848885312,
3.815306159255158,
2.2491773102504062,
1.3276630984776567,
0.7884211778943261,
0.4708461282568907,
0.28236149853196507,
0.16980173598586254,
0.10229476631106786,
0.06169480173887945,
0.03723418494509775,
0.022481089449094008,
],
[
1.0e-5,
3.6451213684882426,
6.184706455055038,
7.75083495382188,
8.672348657723711,
9.211590117984043,
9.529164800771182,
9.717649154060018,
9.83020871507534,
9.89771554128402,
9.938315405635903,
9.962775953501628,
9.977529002206483,
],
]
),
"bM2": np.array(
[
[
2.0,
1.3279917682405473,
0.815368316209652,
0.484406234346711,
0.2866707891616959,
0.1703612676331259,
0.10175389387661611,
0.06101894293570185,
0.03669236327334466,
0.022103697711640027,
0.013330436832490668,
0.00804502307966626,
0.0048573143944901,
],
[
0.0002,
4.005880364582517,
13.40830335654937,
37.445419449158464,
100.85962493652575,
269.5533461366049,
719.1621396161328,
1917.977828184842,
5114.73836146586,
13639.390826596753,
36371.78858209591,
96991.55465118046,
258644.4048115109,
],
]
),
"bDists1": np.array(
[
[100.0, 3.7443020392268367, 0.17804598720980272],
[0.1, 0.09035855289429393, 0.08979659938892945],
[1.0, 1.3916783213625432, 1.4061293503242225],
]
).T,
"bDists2": np.array(
[
[1.0e-6, 1.1190998946220907, 0.05848079412663001],
[1.0, 66.94723995610593, 25749.457224681548],
[3.0, 0.12718999335996053, 0.00662584618581055],
]
).T,
},
"Geometric": {
"t": np.array(
[
0.0,
20.0,
40.0,
60.0,
80.0,
100.0,
120.0,
140.0,
160.0,
180.0,
200.0,
220.0,
240.0,
]
),
"aM0": np.array(
[
100.0,
83.09411530706723,
69.0668818692553,
57.42833556073367,
47.771892319320436,
39.760132461015466,
33.11299776856557,
27.59799298461195,
23.022057367028655,
19.22483391072762,
16.073111976893788,
13.456251155748634,
11.282412772916492,
]
),
"aM1": np.array(
[
10.0,
9.999999999999998,
9.999999999999995,
9.999999999999998,
10.000000000000002,
10.000000000000004,
9.999999999999996,
9.999999999999996,
9.999999999999998,
9.999999999999998,
9.999999999999998,
9.999999999999988,
9.99999999999999,
]
),
"aM2": np.array(
[
2.0,
2.8852151953194194,
4.151238620053756,
5.950500062169887,
8.485178624869318,
12.0129886133155,
16.84418831764611,
23.32258967740333,
31.78481092193408,
42.500028311068455,
55.60685101272762,
71.07585744751505,
88.7218493043981,
]
),
"aDists": np.array(
[
[100.0, 0.1, 1.0],
[33.12307697837833, 1.386085645680255, 0.21781072474918567],
[11.288994413248544, 8.001687588099609, 0.11070395858333783],
]
),
"bM0": np.array(
[
[
100.0,
83.08735661284119,
69.025406058178,
57.28710188741288,
47.43565678877952,
39.167760941853565,
32.289941767938586,
26.61554482816344,
21.95171830328991,
18.122227928945424,
14.977334881119972,
12.392963329500928,
10.267170524593165,
],
[
1.0e-6,
0.006754965534216085,
0.0414689469896406,
0.14122472581368004,
0.33622210669071656,
0.5923365303626719,
0.822966528248585,
0.9822712716512826,
1.0700559173008375,
1.1022183815198043,
1.0953066097618704,
1.062767038894064,
1.014700508663851,
],
]
),
"bM1": np.array(
[
[
10.0,
9.998176966812272,
9.983636638206804,
9.914575608610326,
9.648425409616147,
9.022885248658554,
8.145992984487792,
7.201239010259968,
6.289684097629613,
5.449920021025792,
4.694685159768059,
4.0259638571565235,
3.4404908668086382,
],
[
3.0e-6,
0.001826033187727366,
0.016366361793195474,
0.08542739138967238,
0.3515775903838529,
0.9771177513414488,
1.8540100155122126,
2.798763989740037,
3.7103189023703886,
4.55008297897421,
5.3053178402319405,
5.974039142843473,
6.559512133191355,
],
]
),
"bM2": np.array(
[
[
2.0,
2.884419791825751,
4.140031572580394,
5.841267749589132,
7.602242548420331,
8.443150132466357,
8.291305172948194,
7.649776302203622,
6.858287226599269,
6.056020626291585,
5.296417497830004,
4.600656776850216,
3.976052070235482,
],
[
1.2e-5,
0.0008129200697375103,
0.011232418249945829,
0.10926457152459564,
0.8829072854441761,
3.5698485088870786,
8.556214924636981,
15.693719076620901,
25.002698714778422,
36.65139187807145,
50.772315702453426,
67.35212811578029,
86.19438593789097,
],
]
),
"bDists1": np.array(
[
[100.0, 0.1, 1.0],
[10.267170524593165, 0.8205678828026997, 0.4083712124798814],
]
),
"bDists2": np.array(
[
[1.0e-6, 1.0, 3.0],
[1.014700508663851, 6.675884373858597, 0.968333274304494],
]
),
},
}

for kernel, data in MOM_data.items():
for prefix in ("a", "b"):
data[f"{prefix}Moments"] = np.array([data[f"{prefix}M{i}"] for i in range(3)])

0 comments on commit ae3824e

Please sign in to comment.