mirror of
https://github.com/Findus23/collision-analyisis-and-interpolation.git
synced 2024-09-19 15:13:50 +02:00
support RSMC dataset and three layers
This commit is contained in:
parent
e2e0ae067b
commit
0a5f4f261e
GPG key ID:
54DE4D798D244853
8 changed files with 135 additions and 357 deletions
4
.gitignore
vendored
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.gitignore
vendored
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@ -11,3 +11,7 @@ logs/
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*.npy
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*.npy
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accuracy.csv
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accuracy.csv
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grid-testing-cache*
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grid-testing-cache*
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xl1
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xl2
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xl3
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xl12
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62
import_simruns.py
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import_simruns.py
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@ -0,0 +1,62 @@
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from pathlib import Path
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from simulation import Simulation
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from simulation_list import SimulationList
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simulations = SimulationList()
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with open("RSMC_ML_dataset.txt") as f:
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for line in f:
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if line.startswith("#"):
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continue
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sim = Simulation()
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cols = line.split()
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sim.type = "simrun_import"
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rsmc_run, col_no, time, impact_vel, impact_vel_vesc, impact_angle, \
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mass_p, mass_t, mass_la, mass_sla, \
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wmf_p, wmf_t, wmf_la, wmf_sla, \
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cmf_p, cmf_t, cmf_la, cmf_sla = cols
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sim.runid = rsmc_run + " " + col_no
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sim.v = float(impact_vel_vesc)
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sim.alpha = float(impact_angle)
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sim.projectile_mass = float(mass_p)
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sim.target_mass = float(mass_t)
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sim.total_mass = sim.projectile_mass + sim.target_mass
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sim.largest_aggregate_mass = float(mass_la)
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if sim.largest_aggregate_mass < 0:
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sim.largest_aggregate_mass = 0
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sim.second_largest_aggregate_mass = float(mass_sla)
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if sim.second_largest_aggregate_mass < 0:
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sim.second_largest_aggregate_mass = 0
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sim.projectile_water_fraction = float(wmf_p)
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sim.target_water_fraction = float(wmf_t)
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sim.largest_aggregate_water_fraction = float(wmf_la)
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if sim.largest_aggregate_water_fraction < 0:
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sim.largest_aggregate_water_fraction = 0
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sim.second_largest_aggregate_water_fraction = float(wmf_sla)
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if sim.second_largest_aggregate_water_fraction < 0:
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sim.second_largest_aggregate_water_fraction = 0
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sim.projectile_core_fraction = float(cmf_p)
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sim.target_core_fraction = float(cmf_t)
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sim.largest_aggregate_core_fraction = float(cmf_la)
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if sim.largest_aggregate_core_fraction < 0:
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sim.largest_aggregate_core_fraction = 0
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sim.second_largest_aggregate_core_fraction = float(cmf_sla)
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if sim.second_largest_aggregate_core_fraction < 0:
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sim.second_largest_aggregate_core_fraction = 0
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if not sim.initial_water_mass or not sim.initial_core_mass:
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print(vars(sim))
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print(cols)
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# exit()
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continue
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simulations.append(sim)
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# if len(simulations.simlist)>1000:
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# break
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print(len(simulations.simlist))
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simulations.jsonlines_save(Path("rsmc_dataset.jsonl"))
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323
poetry.lock
generated
323
poetry.lock
generated
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@ -1,323 +0,0 @@
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[[package]]
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name = "cycler"
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version = "0.10.0"
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description = "Composable style cycles"
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category = "main"
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optional = false
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python-versions = "*"
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[package.dependencies]
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six = "*"
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[[package]]
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name = "kiwisolver"
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version = "1.3.1"
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description = "A fast implementation of the Cassowary constraint solver"
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category = "main"
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optional = false
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python-versions = ">=3.6"
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[[package]]
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name = "matplotlib"
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version = "3.3.3"
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description = "Python plotting package"
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category = "main"
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optional = false
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python-versions = ">=3.6"
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[package.dependencies]
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cycler = ">=0.10"
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kiwisolver = ">=1.0.1"
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numpy = ">=1.15"
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pillow = ">=6.2.0"
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pyparsing = ">=2.0.3,<2.0.4 || >2.0.4,<2.1.2 || >2.1.2,<2.1.6 || >2.1.6"
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python-dateutil = ">=2.1"
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[[package]]
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name = "numpy"
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version = "1.19.4"
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description = "NumPy is the fundamental package for array computing with Python."
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category = "main"
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optional = false
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python-versions = ">=3.6"
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[[package]]
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name = "pillow"
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version = "8.0.1"
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description = "Python Imaging Library (Fork)"
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category = "main"
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optional = false
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python-versions = ">=3.6"
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[[package]]
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name = "pyparsing"
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version = "2.4.7"
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description = "Python parsing module"
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category = "main"
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optional = false
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python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
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[[package]]
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name = "pyqt5"
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version = "5.12.1"
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description = "Python bindings for the Qt cross platform UI and application toolkit"
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category = "dev"
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optional = false
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python-versions = "*"
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[package.dependencies]
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PyQt5_sip = ">=4.19.14,<4.20"
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[[package]]
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name = "pyqt5-sip"
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version = "4.19.19"
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description = "Python extension module support for PyQt5"
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category = "dev"
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optional = false
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python-versions = "*"
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[[package]]
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name = "python-dateutil"
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version = "2.8.1"
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description = "Extensions to the standard Python datetime module"
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category = "main"
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optional = false
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python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
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[package.dependencies]
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six = ">=1.5"
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[[package]]
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name = "scipy"
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version = "1.5.4"
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description = "SciPy: Scientific Library for Python"
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category = "main"
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optional = false
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python-versions = ">=3.6"
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[package.dependencies]
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numpy = ">=1.14.5"
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[[package]]
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name = "six"
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version = "1.15.0"
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description = "Python 2 and 3 compatibility utilities"
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category = "main"
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optional = false
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python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
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[[package]]
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name = "tabulate"
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version = "0.8.7"
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description = "Pretty-print tabular data"
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category = "main"
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optional = false
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python-versions = "*"
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[package.extras]
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widechars = ["wcwidth"]
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[metadata]
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lock-version = "1.1"
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python-versions = "^3.8"
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content-hash = "f30005ca5da290b1c740fff0d61bf872d42523e97fb67f891209dee8b6eb6196"
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[metadata.files]
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cycler = [
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{file = "cycler-0.10.0-py2.py3-none-any.whl", hash = "sha256:1d8a5ae1ff6c5cf9b93e8811e581232ad8920aeec647c37316ceac982b08cb2d"},
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{file = "cycler-0.10.0.tar.gz", hash = "sha256:cd7b2d1018258d7247a71425e9f26463dfb444d411c39569972f4ce586b0c9d8"},
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]
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kiwisolver = [
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{file = "kiwisolver-1.3.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:fd34fbbfbc40628200730bc1febe30631347103fc8d3d4fa012c21ab9c11eca9"},
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{file = "kiwisolver-1.3.1-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:d3155d828dec1d43283bd24d3d3e0d9c7c350cdfcc0bd06c0ad1209c1bbc36d0"},
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{file = "kiwisolver-1.3.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:5a7a7dbff17e66fac9142ae2ecafb719393aaee6a3768c9de2fd425c63b53e21"},
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{file = "kiwisolver-1.3.1-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:f8d6f8db88049a699817fd9178782867bf22283e3813064302ac59f61d95be05"},
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{file = "kiwisolver-1.3.1-cp36-cp36m-manylinux2014_ppc64le.whl", hash = "sha256:5f6ccd3dd0b9739edcf407514016108e2280769c73a85b9e59aa390046dbf08b"},
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{file = "kiwisolver-1.3.1-cp36-cp36m-win32.whl", hash = "sha256:225e2e18f271e0ed8157d7f4518ffbf99b9450fca398d561eb5c4a87d0986dd9"},
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{file = "kiwisolver-1.3.1-cp36-cp36m-win_amd64.whl", hash = "sha256:cf8b574c7b9aa060c62116d4181f3a1a4e821b2ec5cbfe3775809474113748d4"},
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{file = "kiwisolver-1.3.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:232c9e11fd7ac3a470d65cd67e4359eee155ec57e822e5220322d7b2ac84fbf0"},
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||||||
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||||||
{file = "kiwisolver-1.3.1-pp36-pypy36_pp73-win32.whl", hash = "sha256:401a2e9afa8588589775fe34fc22d918ae839aaaf0c0e96441c0fdbce6d8ebe6"},
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||||||
{file = "kiwisolver-1.3.1.tar.gz", hash = "sha256:950a199911a8d94683a6b10321f9345d5a3a8433ec58b217ace979e18f16e248"},
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]
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matplotlib = [
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{file = "matplotlib-3.3.3-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:b2a5e1f637a92bb6f3526cc54cc8af0401112e81ce5cba6368a1b7908f9e18bc"},
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{file = "matplotlib-3.3.3-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:9b03722c89a43a61d4d148acfc89ec5bb54cd0fd1539df25b10eb9c5fa6c393a"},
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{file = "matplotlib-3.3.3-cp36-cp36m-win32.whl", hash = "sha256:2c2c5041608cb75c39cbd0ed05256f8a563e144234a524c59d091abbfa7a868f"},
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||||||
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{file = "matplotlib-3.3.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:27c9393fada62bd0ad7c730562a0fecbd3d5aaa8d9ed80ba7d3ebb8abc4f0453"},
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||||||
{file = "matplotlib-3.3.3-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:b8ba2a1dbb4660cb469fe8e1febb5119506059e675180c51396e1723ff9b79d9"},
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|
||||||
{file = "PyQt5_sip-4.19.19-cp35-none-win32.whl", hash = "sha256:7fbb6389c20aff4c3257e89bb1787effffcaf05c32d937c00094ae45846bffd5"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp35-none-win_amd64.whl", hash = "sha256:828d9911acc483672a2bae1cc1bf79f591eb3338faad1f2c798aa2f45459a318"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp36-cp36m-macosx_10_6_intel.whl", hash = "sha256:ac9e5b282d1f0771a8310ed974afe1961ec31e9ae787d052c0e504ea46ae323a"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:d7b26e0b6d81bf14c1239e6a891ac1303a7e882512d990ec330369c7269226d7"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp36-none-win32.whl", hash = "sha256:f8b7a3e05235ce58a38bf317f71a5cb4ab45d3b34dc57421dd8cea48e0e4023e"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp36-none-win_amd64.whl", hash = "sha256:a9460dac973deccc6ff2d90f18fd105cbaada147f84e5917ed79374dcb237758"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp37-cp37m-macosx_10_6_intel.whl", hash = "sha256:ba41bd21b89c6713f7077b5f7d4a1c452989190aad5704e215560a266a1ecbab"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:7b3b8c015e545fa30e42205fc1115b7c6afcb6acec790ce3f330a06323730523"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp37-none-win32.whl", hash = "sha256:59f5332f86f3ccd3ac94674fe91eae6e8aca26da7c6588917cabd0fe22af106d"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp37-none-win_amd64.whl", hash = "sha256:54b99a3057e8f01b90d49cca9ca566b1ea23d8920038760f44e75b90c62b9d5f"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp38-cp38-macosx_10_6_intel.whl", hash = "sha256:39d2677f4de46ed4d7aa3b612f31c74c881975efe51c6a23fbb1d9382e4cc850"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:304acf771b6033cb4bafc415939d227c91265d30664ed643b298d7e95f509f81"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp38-none-win32.whl", hash = "sha256:cfc21b1f80d4655ffa776c505a2576b4d148bbc52bb3e33fedbf6cfbdbc09d1b"},
|
|
||||||
{file = "PyQt5_sip-4.19.19-cp38-none-win_amd64.whl", hash = "sha256:72be07a21b0f379987c4ec59bc86834a9719a2f9cfb49606a4d4e34dae9aa549"},
|
|
||||||
]
|
|
||||||
python-dateutil = [
|
|
||||||
{file = "python-dateutil-2.8.1.tar.gz", hash = "sha256:73ebfe9dbf22e832286dafa60473e4cd239f8592f699aa5adaf10050e6e1823c"},
|
|
||||||
{file = "python_dateutil-2.8.1-py2.py3-none-any.whl", hash = "sha256:75bb3f31ea686f1197762692a9ee6a7550b59fc6ca3a1f4b5d7e32fb98e2da2a"},
|
|
||||||
]
|
|
||||||
scipy = [
|
|
||||||
{file = "scipy-1.5.4-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:4f12d13ffbc16e988fa40809cbbd7a8b45bc05ff6ea0ba8e3e41f6f4db3a9e47"},
|
|
||||||
{file = "scipy-1.5.4-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:a254b98dbcc744c723a838c03b74a8a34c0558c9ac5c86d5561703362231107d"},
|
|
||||||
{file = "scipy-1.5.4-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:368c0f69f93186309e1b4beb8e26d51dd6f5010b79264c0f1e9ca00cd92ea8c9"},
|
|
||||||
{file = "scipy-1.5.4-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:4598cf03136067000855d6b44d7a1f4f46994164bcd450fb2c3d481afc25dd06"},
|
|
||||||
{file = "scipy-1.5.4-cp36-cp36m-win32.whl", hash = "sha256:e98d49a5717369d8241d6cf33ecb0ca72deee392414118198a8e5b4c35c56340"},
|
|
||||||
{file = "scipy-1.5.4-cp36-cp36m-win_amd64.whl", hash = "sha256:65923bc3809524e46fb7eb4d6346552cbb6a1ffc41be748535aa502a2e3d3389"},
|
|
||||||
{file = "scipy-1.5.4-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:9ad4fcddcbf5dc67619379782e6aeef41218a79e17979aaed01ed099876c0e62"},
|
|
||||||
{file = "scipy-1.5.4-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:f87b39f4d69cf7d7529d7b1098cb712033b17ea7714aed831b95628f483fd012"},
|
|
||||||
{file = "scipy-1.5.4-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:25b241034215247481f53355e05f9e25462682b13bd9191359075682adcd9554"},
|
|
||||||
{file = "scipy-1.5.4-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:fa789583fc94a7689b45834453fec095245c7e69c58561dc159b5d5277057e4c"},
|
|
||||||
{file = "scipy-1.5.4-cp37-cp37m-win32.whl", hash = "sha256:d6d25c41a009e3c6b7e757338948d0076ee1dd1770d1c09ec131f11946883c54"},
|
|
||||||
{file = "scipy-1.5.4-cp37-cp37m-win_amd64.whl", hash = "sha256:2c872de0c69ed20fb1a9b9cf6f77298b04a26f0b8720a5457be08be254366c6e"},
|
|
||||||
{file = "scipy-1.5.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:e360cb2299028d0b0d0f65a5c5e51fc16a335f1603aa2357c25766c8dab56938"},
|
|
||||||
{file = "scipy-1.5.4-cp38-cp38-manylinux1_i686.whl", hash = "sha256:3397c129b479846d7eaa18f999369a24322d008fac0782e7828fa567358c36ce"},
|
|
||||||
{file = "scipy-1.5.4-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:168c45c0c32e23f613db7c9e4e780bc61982d71dcd406ead746c7c7c2f2004ce"},
|
|
||||||
{file = "scipy-1.5.4-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:213bc59191da2f479984ad4ec39406bf949a99aba70e9237b916ce7547b6ef42"},
|
|
||||||
{file = "scipy-1.5.4-cp38-cp38-win32.whl", hash = "sha256:634568a3018bc16a83cda28d4f7aed0d803dd5618facb36e977e53b2df868443"},
|
|
||||||
{file = "scipy-1.5.4-cp38-cp38-win_amd64.whl", hash = "sha256:b03c4338d6d3d299e8ca494194c0ae4f611548da59e3c038813f1a43976cb437"},
|
|
||||||
{file = "scipy-1.5.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3d5db5d815370c28d938cf9b0809dade4acf7aba57eaf7ef733bfedc9b2474c4"},
|
|
||||||
{file = "scipy-1.5.4-cp39-cp39-manylinux1_i686.whl", hash = "sha256:6b0ceb23560f46dd236a8ad4378fc40bad1783e997604ba845e131d6c680963e"},
|
|
||||||
{file = "scipy-1.5.4-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:ed572470af2438b526ea574ff8f05e7f39b44ac37f712105e57fc4d53a6fb660"},
|
|
||||||
{file = "scipy-1.5.4-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:8c8d6ca19c8497344b810b0b0344f8375af5f6bb9c98bd42e33f747417ab3f57"},
|
|
||||||
{file = "scipy-1.5.4-cp39-cp39-win32.whl", hash = "sha256:d84cadd7d7998433334c99fa55bcba0d8b4aeff0edb123b2a1dfcface538e474"},
|
|
||||||
{file = "scipy-1.5.4-cp39-cp39-win_amd64.whl", hash = "sha256:cc1f78ebc982cd0602c9a7615d878396bec94908db67d4ecddca864d049112f2"},
|
|
||||||
{file = "scipy-1.5.4.tar.gz", hash = "sha256:4a453d5e5689de62e5d38edf40af3f17560bfd63c9c5bd228c18c1f99afa155b"},
|
|
||||||
]
|
|
||||||
six = [
|
|
||||||
{file = "six-1.15.0-py2.py3-none-any.whl", hash = "sha256:8b74bedcbbbaca38ff6d7491d76f2b06b3592611af620f8426e82dddb04a5ced"},
|
|
||||||
{file = "six-1.15.0.tar.gz", hash = "sha256:30639c035cdb23534cd4aa2dd52c3bf48f06e5f4a941509c8bafd8ce11080259"},
|
|
||||||
]
|
|
||||||
tabulate = [
|
|
||||||
{file = "tabulate-0.8.7-py3-none-any.whl", hash = "sha256:ac64cb76d53b1231d364babcd72abbb16855adac7de6665122f97b593f1eb2ba"},
|
|
||||||
{file = "tabulate-0.8.7.tar.gz", hash = "sha256:db2723a20d04bcda8522165c73eea7c300eda74e0ce852d9022e0159d7895007"},
|
|
||||||
]
|
|
||||||
|
|
@ -1,5 +1,6 @@
|
||||||
from glob import glob
|
from glob import glob
|
||||||
from os import path
|
from os import path
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
from simulation import Simulation
|
from simulation import Simulation
|
||||||
from simulation_list import SimulationList
|
from simulation_list import SimulationList
|
||||||
|
|
@ -51,4 +52,4 @@ for set_type, directories in simulation_sets.items():
|
||||||
|
|
||||||
print(len(simulations.simlist))
|
print(len(simulations.simlist))
|
||||||
|
|
||||||
simulations.jsonlines_save()
|
simulations.jsonlines_save(Path("output.jsonl"))
|
||||||
|
|
|
||||||
|
|
@ -18,11 +18,15 @@ class Simulation:
|
||||||
self.projectile_mass = None # mp
|
self.projectile_mass = None # mp
|
||||||
self.target_mass = None # mt
|
self.target_mass = None # mt
|
||||||
self.projectile_water_fraction = None # wp
|
self.projectile_water_fraction = None # wp
|
||||||
|
self.projectile_core_fraction = None
|
||||||
self.target_water_fraction = None # wt
|
self.target_water_fraction = None # wt
|
||||||
|
self.target_core_fraction = None
|
||||||
self.largest_aggregate_mass = None # mS1
|
self.largest_aggregate_mass = None # mS1
|
||||||
self.largest_aggregate_water_fraction = None # wmfS1
|
self.largest_aggregate_water_fraction = None # wmfS1
|
||||||
|
self.largest_aggregate_core_fraction = None
|
||||||
self.second_largest_aggregate_mass = None # mS2
|
self.second_largest_aggregate_mass = None # mS2
|
||||||
self.second_largest_aggregate_water_fraction = None # wmfS2
|
self.second_largest_aggregate_water_fraction = None # wmfS2
|
||||||
|
self.second_largest_aggregate_core_fraction = None
|
||||||
self.rel_velocity = None # vrel
|
self.rel_velocity = None # vrel
|
||||||
self.rel_velocity_per_esc_velocity = None # vrel_over_vesc
|
self.rel_velocity_per_esc_velocity = None # vrel_over_vesc
|
||||||
self.desired_N = None
|
self.desired_N = None
|
||||||
|
|
@ -57,6 +61,10 @@ class Simulation:
|
||||||
"""
|
"""
|
||||||
return self.largest_aggregate_mass / self.target_mass
|
return self.largest_aggregate_mass / self.target_mass
|
||||||
|
|
||||||
|
@property
|
||||||
|
def largest_aggregate_mantle_fraction(self) -> float:
|
||||||
|
return 1 - self.largest_aggregate_core_fraction - self.largest_aggregate_water_fraction
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def second_largest_aggregate_relative_mass(self) -> float:
|
def second_largest_aggregate_relative_mass(self) -> float:
|
||||||
"""
|
"""
|
||||||
|
|
@ -65,20 +73,29 @@ class Simulation:
|
||||||
return self.second_largest_aggregate_mass / self.projectile_mass
|
return self.second_largest_aggregate_mass / self.projectile_mass
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def projectile_stone_fraction(self):
|
def second_largest_aggregate_mantle_fraction(self) -> float:
|
||||||
return 1 - self.projectile_water_fraction
|
return 1 - self.second_largest_aggregate_core_fraction - self.second_largest_aggregate_water_fraction
|
||||||
|
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def target_stone_fraction(self):
|
def projectile_mantle_fraction(self):
|
||||||
return 1 - self.target_water_fraction
|
return 1 - self.projectile_water_fraction - self.projectile_core_fraction
|
||||||
|
|
||||||
|
@property
|
||||||
|
def target_mantle_fraction(self):
|
||||||
|
return 1 - self.target_water_fraction - self.target_core_fraction
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def initial_water_mass(self) -> float:
|
def initial_water_mass(self) -> float:
|
||||||
return self.projectile_mass * self.projectile_water_fraction + self.target_mass * self.target_water_fraction
|
return self.projectile_mass * self.projectile_water_fraction + self.target_mass * self.target_water_fraction
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def initial_stone_mass(self) -> float:
|
def initial_core_mass(self) -> float:
|
||||||
return self.projectile_mass * self.projectile_stone_fraction + self.target_mass * self.target_stone_fraction
|
return self.projectile_mass * self.projectile_core_fraction + self.target_mass * self.target_core_fraction
|
||||||
|
|
||||||
|
@property
|
||||||
|
def initial_mantle_mass(self) -> float:
|
||||||
|
return self.projectile_mass * self.projectile_mantle_fraction + self.target_mass * self.target_mantle_fraction
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def water_retention_both(self) -> float:
|
def water_retention_both(self) -> float:
|
||||||
|
|
@ -91,12 +108,18 @@ class Simulation:
|
||||||
) / self.initial_water_mass
|
) / self.initial_water_mass
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def mass_retention_both(self) -> float:
|
def core_retention_both(self) -> float:
|
||||||
return (
|
return (
|
||||||
self.largest_aggregate_mass * (1 - self.largest_aggregate_water_fraction)
|
self.largest_aggregate_mass * self.largest_aggregate_core_fraction
|
||||||
+ self.second_largest_aggregate_mass * (1 - self.second_largest_aggregate_water_fraction)
|
+ self.second_largest_aggregate_mass * self.largest_aggregate_core_fraction
|
||||||
) / (self.projectile_mass * (1 - self.projectile_water_fraction) + self.target_mass * (
|
) / self.initial_core_mass
|
||||||
1 - self.target_water_fraction))
|
|
||||||
|
@property
|
||||||
|
def mantle_retention_both(self) -> float:
|
||||||
|
return (
|
||||||
|
self.largest_aggregate_mass * self.largest_aggregate_mantle_fraction
|
||||||
|
+ self.second_largest_aggregate_mass * self.largest_aggregate_mantle_fraction
|
||||||
|
) / self.initial_mantle_mass
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def water_retention_main(self) -> float:
|
def water_retention_main(self) -> float:
|
||||||
|
|
@ -111,7 +134,7 @@ class Simulation:
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def testcase(self) -> bool:
|
def testcase(self) -> bool:
|
||||||
return not self.original_simulation and 529 <= self.runid <= 631
|
return self.type == "cloud" and 529 <= self.runid <= 631
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def simulation_key(self):
|
def simulation_key(self):
|
||||||
|
|
@ -184,9 +207,9 @@ class Simulation:
|
||||||
def load_params_from_pythontiming_json(self, filename: str) -> None:
|
def load_params_from_pythontiming_json(self, filename: str) -> None:
|
||||||
with open(filename) as f:
|
with open(filename) as f:
|
||||||
data = json.load(f)
|
data = json.load(f)
|
||||||
self.miluphcuda_time=data["miluphcuda"]
|
self.miluphcuda_time = data["miluphcuda"]
|
||||||
self.relaxation_time=data["relaxation"]
|
self.relaxation_time = data["relaxation"]
|
||||||
self.setup_time=data["setup"]
|
self.setup_time = data["setup"]
|
||||||
|
|
||||||
def assert_all_loaded(self) -> None:
|
def assert_all_loaded(self) -> None:
|
||||||
for key, value in self.__dict__.items():
|
for key, value in self.__dict__.items():
|
||||||
|
|
|
||||||
|
|
@ -65,12 +65,16 @@ class SimulationList:
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def Y(self):
|
def Y(self):
|
||||||
return self.Y_water if water_fraction else self.Y_mass
|
return self.Y_water if water_fraction else self.Y_mantle
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def Y_mass(self):
|
def Y_core(self):
|
||||||
return np.array([s.mass_retention_both for s in self.simlist if not s.testcase])
|
return np.array([s.core_retention_both for s in self.simlist if not s.testcase])
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def Y_water(self):
|
def Y_water(self):
|
||||||
return np.array([s.water_retention_both for s in self.simlist if not s.testcase])
|
return np.array([s.water_retention_both for s in self.simlist if not s.testcase])
|
||||||
|
|
||||||
|
@property
|
||||||
|
def Y_mantle(self):
|
||||||
|
return np.array([s.mantle_retention_both for s in self.simlist if not s.testcase])
|
||||||
|
|
|
||||||
22
sliders.py
22
sliders.py
|
|
@ -1,3 +1,5 @@
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
import matplotlib.pyplot as plt
|
import matplotlib.pyplot as plt
|
||||||
import numpy as np
|
import numpy as np
|
||||||
from matplotlib.collections import QuadMesh
|
from matplotlib.collections import QuadMesh
|
||||||
|
|
@ -7,7 +9,7 @@ from CustomScaler import CustomScaler
|
||||||
from interpolators.rbf import RbfInterpolator
|
from interpolators.rbf import RbfInterpolator
|
||||||
from simulation_list import SimulationList
|
from simulation_list import SimulationList
|
||||||
|
|
||||||
simlist = SimulationList.jsonlines_load()
|
simlist = SimulationList.jsonlines_load(Path("rsmc_dataset.jsonl"))
|
||||||
|
|
||||||
data = simlist.X
|
data = simlist.X
|
||||||
values = simlist.Y
|
values = simlist.Y
|
||||||
|
|
@ -31,19 +33,19 @@ datagrid = np.zeros_like(grid_alpha)
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mesh = plt.pcolormesh(grid_alpha, grid_v, datagrid, cmap="Blues", vmin=0, vmax=1) # type:QuadMesh
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mesh = plt.pcolormesh(grid_alpha, grid_v, datagrid, cmap="Blues", vmin=0, vmax=1) # type:QuadMesh
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plt.colorbar()
|
plt.colorbar()
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|
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axcolor = 'lightgoldenrodyellow'
|
# axcolor = 'lightgoldenrodyellow'
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ax_mcode = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
|
ax_mcode = plt.axes([0.25, 0.1, 0.65, 0.03])
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ax_gamma = plt.axes([0.25, 0.15, 0.65, 0.03], facecolor=axcolor)
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ax_gamma = plt.axes([0.25, 0.15, 0.65, 0.03])
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ax_wt = plt.axes([0.25, 0.20, 0.65, 0.03], facecolor=axcolor)
|
ax_wt = plt.axes([0.25, 0.20, 0.65, 0.03])
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ax_wp = plt.axes([0.25, 0.25, 0.65, 0.03], facecolor=axcolor)
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ax_wp = plt.axes([0.25, 0.25, 0.65, 0.03])
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buttonax = plt.axes([0.8, 0.025, 0.1, 0.04])
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buttonax = plt.axes([0.8, 0.025, 0.1, 0.04])
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button = Button(buttonax, 'Update', color=axcolor, hovercolor='0.975')
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button = Button(buttonax, 'Update', hovercolor='0.975')
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# thetext = ax.text(-10, 0, "hello", fontsize=12) #type:Text
|
# thetext = ax.text(-10, 0, "hello", fontsize=12) #type:Text
|
||||||
|
|
||||||
s_mcode = Slider(ax_mcode, 'mcode', 21, 25, valinit=mcode_default)
|
s_mcode = Slider(ax_mcode, 'mcode', 21, 25, valinit=mcode_default)
|
||||||
s_gamma = Slider(ax_gamma, 'gamma', 0.1, 1, valinit=gamma_default)
|
s_gamma = Slider(ax_gamma, 'gamma', 0.1, 1, valinit=gamma_default)
|
||||||
s_wt = Slider(ax_wt, 'wt', 10, 20, valinit=wt_default)
|
s_wt = Slider(ax_wt, 'wt', 1e-5, 1e-4, valinit=wt_default)
|
||||||
s_wp = Slider(ax_wp, 'wp', 10, 20, valinit=wp_default)
|
s_wp = Slider(ax_wp, 'wp', 1e-5, 1e-4, valinit=wp_default)
|
||||||
|
|
||||||
|
|
||||||
def update(val):
|
def update(val):
|
||||||
|
|
@ -55,7 +57,7 @@ def update(val):
|
||||||
gamma = s_gamma.val
|
gamma = s_gamma.val
|
||||||
wt = s_wt.val
|
wt = s_wt.val
|
||||||
wp = s_wp.val
|
wp = s_wp.val
|
||||||
parameters = [grid_alpha, grid_v, 10 ** mcode, gamma, wt/100, wp/100]
|
parameters = [grid_alpha, grid_v, 10 ** mcode, gamma, wt / 100, wp / 100]
|
||||||
scaled_parameters = list(scaler.transform_parameters(parameters))
|
scaled_parameters = list(scaler.transform_parameters(parameters))
|
||||||
|
|
||||||
datagrid = interpolator.interpolate(*scaled_parameters)
|
datagrid = interpolator.interpolate(*scaled_parameters)
|
||||||
|
|
|
||||||
15
visualize.py
15
visualize.py
|
|
@ -1,3 +1,6 @@
|
||||||
|
from copy import copy
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
import numpy as np
|
import numpy as np
|
||||||
from matplotlib import pyplot as plt, cm
|
from matplotlib import pyplot as plt, cm
|
||||||
|
|
||||||
|
|
@ -6,12 +9,13 @@ from config import water_fraction
|
||||||
from interpolators.rbf import RbfInterpolator
|
from interpolators.rbf import RbfInterpolator
|
||||||
from simulation_list import SimulationList
|
from simulation_list import SimulationList
|
||||||
|
|
||||||
plt.style.use('dark_background')
|
|
||||||
|
# plt.style.use('dark_background')
|
||||||
|
|
||||||
|
|
||||||
def main():
|
def main():
|
||||||
mcode, gamma, wt, wp = [10 ** 22, 0.6, 15 / 100, 15 / 100]
|
mcode, gamma, wt, wp = [10 ** 21, 0.6, 1e-5, 1e-5]
|
||||||
simlist = SimulationList.jsonlines_load()
|
simlist = SimulationList.jsonlines_load(Path("rsmc_dataset.jsonl"))
|
||||||
# for s in simlist.simlist:
|
# for s in simlist.simlist:
|
||||||
# if s.type!="original":
|
# if s.type!="original":
|
||||||
# continue
|
# continue
|
||||||
|
|
@ -41,8 +45,9 @@ def main():
|
||||||
print("minmax")
|
print("minmax")
|
||||||
print(np.nanmin(grid_result), np.nanmax(grid_result))
|
print(np.nanmin(grid_result), np.nanmax(grid_result))
|
||||||
|
|
||||||
plt.title("m={:3.0e}, gamma={:3.1f}, wt={:2.0f}%, wp={:2.0f}%\n".format(mcode, gamma, wt*100, wp*100))
|
plt.title("m={:3.0e}, gamma={:3.1f}, wt={:2.0e}, wp={:2.0e}\n".format(mcode, gamma, wt, wp))
|
||||||
cmap = cm.Blues if water_fraction else cm.Oranges
|
cmap = cm.get_cmap("Blues") if water_fraction else cm.get_cmap("Oranges")
|
||||||
|
cmap = copy(cmap)
|
||||||
cmap.set_bad('white', 1.) # show nan white
|
cmap.set_bad('white', 1.) # show nan white
|
||||||
# plt.contourf(grid_alpha, grid_v, grid_result, 100, cmap="Blues", vmin=0, vmax=1)
|
# plt.contourf(grid_alpha, grid_v, grid_result, 100, cmap="Blues", vmin=0, vmax=1)
|
||||||
# plt.pcolormesh(grid_alpha, grid_v, grid_result, cmap="Blues", vmin=0, vmax=1)
|
# plt.pcolormesh(grid_alpha, grid_v, grid_result, cmap="Blues", vmin=0, vmax=1)
|
||||||
|
|
|
||||||
Loading…
Reference in a new issue