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# Authentication to Apollo
class LogReader(object):
__version__ = '0.0.1'
def __init__(self, target_directory, target_log):
'''
x = [0, 0 ,0 ,0 ,0 ,300 ,300,300,300,300,600,600,600,600,600,900,900,900,900,900]
y = [4.4 ,5.6,5.2,5.4,4.4,9.1,8.6,8.5,9.3,9,12.8,13.4,13.2,12.6,13.2,17,17.3,16.5,16.8,17.2]
colors = ["#A800FF", "#0079FF", "#00F11D", "#FF7F00", "#FF0900"]
pyo.init_notebook_mode()
fig = go.Figure()
fig.add_trace(
def plot_distribution(distributions):
import plotly.graph_objects as go
colors = ["#A800FF", "#0079FF", "#00F11D", "#FFEF00", "#FF7F00", "#FF0900"]
fig = go.Figure()
fig.add_trace(go.Bar(
x=[0, 1, 2, 3, 4, 5],
@Sulstice
Sulstice / image.png
Last active January 21, 2021 21:42
Image
image.png
#nexus
begin trees;
tree the_tree = ('PREDICTED: tyrosine-protein kinase Mer [Chrysochloris asiatica]':0.0148037, (('tyrosine-protein kinase Mer [Carlito syrichta]':0.00622156, 'tyrosine-protein kinase Mer [Saimiri boliviensis boliviensis]':0.00733839)primates:0.00136197, ((('tyrosine-protein kinase Mer [Tupaia chinensis]':0, 'Tyrosine-protein kinase Mer [Tupaia chinensis]':0)placentals:0.0117037, ((('tyrosine-protein kinase Mer isoform X1 [Callithrix jacchus]':0, 'tyrosine-protein kinase Mer isoform X2 [Callithrix jacchus]':0)primates:0, 'tyrosine-protein kinase Mer isoform X3 [Callithrix jacchus]':0)primates:0.00864, 'tyrosine-protein kinase Mer [Trichechus manatus latirostris]':0.0186688)primates_and_placentals:0.000235324)primates_and_placentals:4.0391e-05, (('tyrosine-protein kinase Mer isoform X1 [Sapajus apella]':0, 'tyrosine-protein kinase Mer isoform X2 [Sapajus apella]':0)primates:0.00455301, ((('tyrosine-protein kinase Mer [Enhydra lutris kenyoni]':0.0033587, ('tyrosine-protein kinase Mer [Lontra
This file has been truncated, but you can view the full file.
{"_default": {"1": {"smiles": "CNS(=O)(=O)C1=CSC=C1", "param_penalty": "130.500", "charm_penalty": "5.290", "atom_penalties": [["CG331", "-0.020", "2.749"], ["NG311", "-0.493", "5.290"], ["SG3O2", "0.633", "4.628"], ["OG2P1", "-0.416", "0.000"], ["OG2P1", "-0.416", "0.000"], ["CG2R51", "-0.252", "4.641"], ["CG2R51", "-0.036", "2.593"], ["SG2R50", "-0.105", "2.500"], ["CG2R51", "-0.001", "0.000"], ["CG2R51", "-0.226", "0.304"], ["HGA3", "0.090", "0.000"], ["HGA3", "0.090", "0.000"], ["HGA3", "0.090", "0.000"], ["HGP1", "0.348", "4.565"], ["HGR52", "0.291", "0.645"], ["HGR52", "0.180", "0.000"], ["HGR51", "0.243", "0.000"]], "dihedrals": [["CG2R51", "CG2R51", "CG2R51", "CG2R51", "2"], ["CG2R51", "CG2R51", "CG2R51", "SG2R50", "2"], ["CG2R51", "CG2R51", "CG2R51", "SG3O2", "2"], ["CG2R51", "CG2R51", "CG2R51", "HGR51", "2"], ["CG2R51", "CG2R51", "CG2R51", "HGR52", "2"], ["SG2R50", "CG2R51", "CG2R51", "SG3O2", "2"], ["SG2R50", "CG2R51", "CG2R51", "HGR51", "2"], ["SG3O2", "CG2R51", "CG2R51", "HGR51", "2"], ["SG3O2",
<?xml version='1.0' encoding='UTF-8'?>
<R_replacements><center SMILES="*O" degree="13627"><first_layer SMILES="*OC" edge_weight="2273"><second_layer SMILES="*Cl" edge_weight="3455" /><second_layer SMILES="*OCC" edge_weight="788" /></first_layer><first_layer SMILES="*N" edge_weight="958"><second_layer SMILES="*NC" edge_weight="305" /><second_layer SMILES="*NC(C)=O" edge_weight="300" /></first_layer><first_layer SMILES="*CO" edge_weight="301"><second_layer SMILES="*C(C)O" edge_weight="75" /><second_layer SMILES="*C(C)(C)O" edge_weight="53" /></first_layer><first_layer SMILES="*OC(C)=O" edge_weight="200" /><first_layer SMILES="*C(=O)NO" edge_weight="89"><second_layer SMILES="*CC(=O)NO" edge_weight="43" /></first_layer></center><center SMILES="*OC" degree="12408"><first_layer SMILES="*Cl" edge_weight="3455"><second_layer SMILES="*F" edge_weight="4152" /><second_layer SMILES="*Br" edge_weight="2208" /></first_layer><first_layer SMILES="*O" edge_weight="2273"><second_layer SMILES="*N" edge_weight="958" /><second_la
A chemical dataset spread with filters.