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../../experiments/kupferschmidt1995.py
from typing import Dict, List
from sbmlsim.data import DataSet, load_pkdb_dataframes_by_substance
from sbmlsim.fit import FitMapping, FitData
from sbmlsim.plot import Figure, Axis
from sbmlsim.simulation import Timecourse, TimecourseSim
from . import MidazolamSimulationExperiment
class Kupferschmidt1995(MidazolamSimulationExperiment):
def datasets(self) -> Dict[str, DataSet]:
dsets = {}
for fig_id in ["Fig1", "Fig2"]:
dframes = load_pkdb_dataframes_by_substance(
f"{self.sid}_{fig_id}", data_path=self.data_path)
for substance, df in dframes.items():
dset = DataSet.from_df(df, self.ureg)
if substance == "midazolam":
dset.unit_conversion("mean", 1 / self.Mr.mid)
elif substance == "1-hydroxymidazolam":
dset.unit_conversion("mean", 1 / self.Mr.mid1oh)
else:
raise ValueError
for intervention in df.intervention.unique():
# tag route
if "po" in intervention:
route = "po"
elif "iv" in intervention:
route = "iv"
else:
raise ValueError
# tag intervention type
if "GRAP1" in intervention:
continue
else:
type = "control"
dsets[f"{fig_id}_{substance}_{route}_{type}"] = dset[dset.intervention == intervention]
return dsets
def simulations(self) -> Dict[str, TimecourseSim]:
return super(Kupferschmidt1995, self).simulations(
simulations={**self.simulations_mid()}
)
def simulations_mid(self) -> Dict[str, TimecourseSim]:
""" Kupferschmidt1995
- midazolam, iv, 5 [mg]
- midazolam, po, 15 [mg]
- grapefruit juice, po, 200 [mg], -60min and -15min
"""
Q_ = self.Q_
bodyweight = Q_(70, 'kg') # avg. bodyweight of 8 individuals. (se=1kg)
mid_iv = Q_(5, 'mg')
mid_po = Q_(15, 'mg')
sim_def = {
"mid_iv_c": {'end': 1500, 'steps': 3000, 'dose': {'IVDOSE_mid': mid_iv}, 'change': self.default_changes()},
"mid_po_c": {'end': 1500, 'steps': 3000, 'dose': {'PODOSE_mid': mid_po}, 'change': self.default_changes()},
}
tcsims = {}
for key, value in sim_def.items():
tcsims[key] = TimecourseSim([
Timecourse(start=0, end=value['end'], steps=value['steps'],
changes={**value['change'],
**value['dose'],
"BW": bodyweight}
)
])
return tcsims
def fit_mappings(self) -> Dict[str, FitMapping]:
# fit mapping: which data maps on which simulation
fit_dict = {
"fm_mid_iv": {"ref": "Fig1_midazolam_iv_control", "obs": "task_mid_iv_c", "yid": "[Cve_mid]"},
"fm_mid1oh_iv": {"ref": "Fig2_1-hydroxymidazolam_iv_control", "obs": "task_mid_iv_c", "yid": "[Cve_mid1oh]"},
"fm_mid_po": {"ref": "Fig1_midazolam_po_control", "obs": "task_mid_po_c", "yid": "[Cve_mid]"},
"fm_mid1oh_po": {"ref": "Fig2_1-hydroxymidazolam_po_control", "obs": "task_mid_po_c", "yid": "[Cve_mid1oh]"},
}
mappings = {}
for key, values in fit_dict.items():
mappings[key] = FitMapping(
self,
reference=FitData(self, dataset=values["ref"], xid="time", yid="mean", yid_sd="mean_sd"),
observable=FitData(self, task=values["obs"], xid="time", yid=values["yid"])
)
return mappings
def figures(self) -> Dict[str, Figure]:
return {
**self.figure_mid()
}
def figure_mid(self):
unit_time = "min"
unit_mid = "nmol/ml"
unit_mid1oh = "nmol/ml"
fig = Figure(self, sid="Fig1",
num_rows=2, num_cols=2, name=self.sid)
plots = fig.create_plots(
Axis("time", unit=unit_time),
legend=True
)
# set titles and labs
plots[0].set_title("midazolam iv, 5 [mg]")
plots[1].set_title("midazolam iv, 5 [mg] + Grapefruit Juice")
plots[2].set_title("midazolam po, 15 [mg]")
plots[3].set_title("midazolam po, 15 [mg] + Grapefruit Juice")
for k in (0, 1):
plots[k].set_yaxis("midazolam", unit_mid)
plots[k].xaxis.label_visible = False
for k in (2, 3):
plots[k].set_yaxis("1-hydroxymidazolam", unit_mid1oh)
# simulation
plot_dict = {
"mid_iv_c": {'plot': (0, 1), 'label': 'mid (ve blood; control)', "color": "black"},
"mid_po_c": {'plot': (2, 3), 'label': 'mid (ve blood; control)', "color": "black"},
}
for key, value in plot_dict.items():
for suffix in ["_sensitivity", ""]:
task_id = f"task_{key}{suffix}"
# plot midazolam
p = plots[value["plot"][0]]
p.add_data(task=task_id, xid='time', yid='[Cve_mid]',
label=value['label'], color=value['color'], linewidth=2)
# plot 1-hydroxymidazolam
p = plots[value["plot"][1]]
p.add_data(task=task_id, xid='time', yid='[Cve_mid1oh]',
label=value['label'], color=value['color'], linewidth=2)
# plot data
data_def = {
"Fig1_midazolam_iv_control": {'plot': 0, 'key': 'control', 'color': 'black'},
"Fig1_midazolam_po_control": {'plot': 1, 'key': 'control', 'color': 'black'},
"Fig2_1-hydroxymidazolam_iv_control": {'plot': 2, 'key': 'control', 'color': 'black'},
"Fig2_1-hydroxymidazolam_po_control": {'plot': 3, 'key': 'control', 'color': 'black'},
}
for dset_key, dset_info in data_def.items():
p = plots[dset_info['plot']]
p.add_data(dataset=dset_key,
xid="time", yid="mean", yid_sd="mean_sd",
count=None, color=dset_info['color'],
label=dset_info['key'])
return {"fig1": fig}