PySDM_examples.Alpert_and_Knopf_2016.table_1
1from PySDM_examples.Alpert_and_Knopf_2016.table import Table 2 3from PySDM.initialisation.spectra import Lognormal, TopHat 4from PySDM.physics import si 5 6 7class Table1(Table): 8 def label(self, key): 9 if isinstance(self[key]["ISA"], Lognormal): 10 return ( 11 f"σ=ln({int(self[key]['ISA'].s_geom)})," 12 f"N={int(self[key]['ISA'].norm_factor * self.volume)}" 13 ) 14 return key 15 16 def __init__(self, *, volume=1 * si.cm**3): 17 super().__init__( 18 volume=volume, 19 data={ 20 "Iso1": { 21 "ISA": Lognormal( 22 norm_factor=1000 / volume, m_mode=1e-5 * si.cm**2, s_geom=1 23 ), 24 "color": "#298131", 25 "J_het": 1e3 / si.cm**2 / si.s, 26 }, 27 "Iso2": { 28 "ISA": Lognormal( 29 norm_factor=30 / volume, m_mode=1e-5 * si.cm**2, s_geom=1 30 ), 31 "color": "#9ACFA4", 32 "J_het": 1e3 / si.cm**2 / si.s, 33 }, 34 "Iso3": { 35 "ISA": Lognormal( 36 norm_factor=1000 / volume, m_mode=1e-5 * si.cm**2, s_geom=10 37 ), 38 "color": "#1A62B4", 39 "J_het": 1e3 / si.cm**2 / si.s, 40 }, 41 "Iso4": { 42 "ISA": Lognormal( 43 norm_factor=30 / volume, m_mode=1e-5 * si.cm**2, s_geom=10 44 ), 45 "color": "#95BDE1", 46 "J_het": 1e3 / si.cm**2 / si.s, 47 }, 48 "IsoWR": { 49 "ISA": Lognormal( 50 norm_factor=1000 / volume, 51 m_mode=6.4e-3 * si.cm**2, 52 s_geom=9.5, 53 ), 54 "color": "#FED2B0", 55 "J_het": 6e-4 / si.cm**2 / si.s, 56 }, 57 "IsoBR": { 58 "ISA": TopHat( 59 norm_factor=63 / volume, 60 endpoints=(9.4e-8 * si.cm**2, 7.5e-7 * si.cm**2), 61 ), 62 "color": "#FED2B0", 63 "J_het": 2.8e3 / si.cm**2 / si.s, 64 }, 65 "IsoHE1": { 66 "ISA": Lognormal( 67 norm_factor=40 / volume, m_mode=1.2 * si.cm**2, s_geom=2.2 68 ), 69 "color": "#FED2B0", 70 "J_het": 4.1e-3 / si.cm**2 / si.s, 71 }, 72 "IsoHE2": { 73 "ISA": Lognormal( 74 norm_factor=40 / volume, m_mode=2e-2 * si.cm**2, s_geom=8.5 75 ), 76 "color": "#FED2B0", 77 "J_het": 2e-2 / si.cm**2 / si.s, 78 }, 79 "IsoDI1": { 80 "ISA": Lognormal( 81 norm_factor=45 / volume, m_mode=5.1e-1 * si.cm**2, s_geom=3.2 82 ), 83 "J_het": 1.8e-2 / si.cm**2 / si.s, 84 "color": "#9ACFA4", 85 }, 86 "IsoDI2": { 87 "ISA": Lognormal( 88 norm_factor=45 / volume, m_mode=5.1e-2 * si.cm**2, s_geom=3.2 89 ), 90 "J_het": 1 / si.cm**2 / si.s, 91 "color": "#FED2B0", 92 }, 93 "IsoDI3": { 94 "ISA": Lognormal( 95 norm_factor=45 / volume, m_mode=5.1e-1 * si.cm**2, s_geom=3.2 96 ), 97 "J_het": 1 / si.cm**2 / si.s, 98 "color": "#95BDE1", 99 }, 100 }, 101 )
8class Table1(Table): 9 def label(self, key): 10 if isinstance(self[key]["ISA"], Lognormal): 11 return ( 12 f"σ=ln({int(self[key]['ISA'].s_geom)})," 13 f"N={int(self[key]['ISA'].norm_factor * self.volume)}" 14 ) 15 return key 16 17 def __init__(self, *, volume=1 * si.cm**3): 18 super().__init__( 19 volume=volume, 20 data={ 21 "Iso1": { 22 "ISA": Lognormal( 23 norm_factor=1000 / volume, m_mode=1e-5 * si.cm**2, s_geom=1 24 ), 25 "color": "#298131", 26 "J_het": 1e3 / si.cm**2 / si.s, 27 }, 28 "Iso2": { 29 "ISA": Lognormal( 30 norm_factor=30 / volume, m_mode=1e-5 * si.cm**2, s_geom=1 31 ), 32 "color": "#9ACFA4", 33 "J_het": 1e3 / si.cm**2 / si.s, 34 }, 35 "Iso3": { 36 "ISA": Lognormal( 37 norm_factor=1000 / volume, m_mode=1e-5 * si.cm**2, s_geom=10 38 ), 39 "color": "#1A62B4", 40 "J_het": 1e3 / si.cm**2 / si.s, 41 }, 42 "Iso4": { 43 "ISA": Lognormal( 44 norm_factor=30 / volume, m_mode=1e-5 * si.cm**2, s_geom=10 45 ), 46 "color": "#95BDE1", 47 "J_het": 1e3 / si.cm**2 / si.s, 48 }, 49 "IsoWR": { 50 "ISA": Lognormal( 51 norm_factor=1000 / volume, 52 m_mode=6.4e-3 * si.cm**2, 53 s_geom=9.5, 54 ), 55 "color": "#FED2B0", 56 "J_het": 6e-4 / si.cm**2 / si.s, 57 }, 58 "IsoBR": { 59 "ISA": TopHat( 60 norm_factor=63 / volume, 61 endpoints=(9.4e-8 * si.cm**2, 7.5e-7 * si.cm**2), 62 ), 63 "color": "#FED2B0", 64 "J_het": 2.8e3 / si.cm**2 / si.s, 65 }, 66 "IsoHE1": { 67 "ISA": Lognormal( 68 norm_factor=40 / volume, m_mode=1.2 * si.cm**2, s_geom=2.2 69 ), 70 "color": "#FED2B0", 71 "J_het": 4.1e-3 / si.cm**2 / si.s, 72 }, 73 "IsoHE2": { 74 "ISA": Lognormal( 75 norm_factor=40 / volume, m_mode=2e-2 * si.cm**2, s_geom=8.5 76 ), 77 "color": "#FED2B0", 78 "J_het": 2e-2 / si.cm**2 / si.s, 79 }, 80 "IsoDI1": { 81 "ISA": Lognormal( 82 norm_factor=45 / volume, m_mode=5.1e-1 * si.cm**2, s_geom=3.2 83 ), 84 "J_het": 1.8e-2 / si.cm**2 / si.s, 85 "color": "#9ACFA4", 86 }, 87 "IsoDI2": { 88 "ISA": Lognormal( 89 norm_factor=45 / volume, m_mode=5.1e-2 * si.cm**2, s_geom=3.2 90 ), 91 "J_het": 1 / si.cm**2 / si.s, 92 "color": "#FED2B0", 93 }, 94 "IsoDI3": { 95 "ISA": Lognormal( 96 norm_factor=45 / volume, m_mode=5.1e-1 * si.cm**2, s_geom=3.2 97 ), 98 "J_het": 1 / si.cm**2 / si.s, 99 "color": "#95BDE1", 100 }, 101 }, 102 )
Table1(*, volume=1.0000000000000002e-06)
17 def __init__(self, *, volume=1 * si.cm**3): 18 super().__init__( 19 volume=volume, 20 data={ 21 "Iso1": { 22 "ISA": Lognormal( 23 norm_factor=1000 / volume, m_mode=1e-5 * si.cm**2, s_geom=1 24 ), 25 "color": "#298131", 26 "J_het": 1e3 / si.cm**2 / si.s, 27 }, 28 "Iso2": { 29 "ISA": Lognormal( 30 norm_factor=30 / volume, m_mode=1e-5 * si.cm**2, s_geom=1 31 ), 32 "color": "#9ACFA4", 33 "J_het": 1e3 / si.cm**2 / si.s, 34 }, 35 "Iso3": { 36 "ISA": Lognormal( 37 norm_factor=1000 / volume, m_mode=1e-5 * si.cm**2, s_geom=10 38 ), 39 "color": "#1A62B4", 40 "J_het": 1e3 / si.cm**2 / si.s, 41 }, 42 "Iso4": { 43 "ISA": Lognormal( 44 norm_factor=30 / volume, m_mode=1e-5 * si.cm**2, s_geom=10 45 ), 46 "color": "#95BDE1", 47 "J_het": 1e3 / si.cm**2 / si.s, 48 }, 49 "IsoWR": { 50 "ISA": Lognormal( 51 norm_factor=1000 / volume, 52 m_mode=6.4e-3 * si.cm**2, 53 s_geom=9.5, 54 ), 55 "color": "#FED2B0", 56 "J_het": 6e-4 / si.cm**2 / si.s, 57 }, 58 "IsoBR": { 59 "ISA": TopHat( 60 norm_factor=63 / volume, 61 endpoints=(9.4e-8 * si.cm**2, 7.5e-7 * si.cm**2), 62 ), 63 "color": "#FED2B0", 64 "J_het": 2.8e3 / si.cm**2 / si.s, 65 }, 66 "IsoHE1": { 67 "ISA": Lognormal( 68 norm_factor=40 / volume, m_mode=1.2 * si.cm**2, s_geom=2.2 69 ), 70 "color": "#FED2B0", 71 "J_het": 4.1e-3 / si.cm**2 / si.s, 72 }, 73 "IsoHE2": { 74 "ISA": Lognormal( 75 norm_factor=40 / volume, m_mode=2e-2 * si.cm**2, s_geom=8.5 76 ), 77 "color": "#FED2B0", 78 "J_het": 2e-2 / si.cm**2 / si.s, 79 }, 80 "IsoDI1": { 81 "ISA": Lognormal( 82 norm_factor=45 / volume, m_mode=5.1e-1 * si.cm**2, s_geom=3.2 83 ), 84 "J_het": 1.8e-2 / si.cm**2 / si.s, 85 "color": "#9ACFA4", 86 }, 87 "IsoDI2": { 88 "ISA": Lognormal( 89 norm_factor=45 / volume, m_mode=5.1e-2 * si.cm**2, s_geom=3.2 90 ), 91 "J_het": 1 / si.cm**2 / si.s, 92 "color": "#FED2B0", 93 }, 94 "IsoDI3": { 95 "ISA": Lognormal( 96 norm_factor=45 / volume, m_mode=5.1e-1 * si.cm**2, s_geom=3.2 97 ), 98 "J_het": 1 / si.cm**2 / si.s, 99 "color": "#95BDE1", 100 }, 101 }, 102 )