def reset(self):
enz = extract_enzyme_set("para.txt", PARAMETER_NO)
self.base = ODEAnalysis(SYSTEM, 1, enz)
if PARAMETER_NO == 0:
self.base.normalize_enzymes()
self.base.attain_steady_state()
for key in self.para_dict:
self.para_dict[key]["v"].setValue(self.base.enz[key].v)
self.para_dict[key]["k"].setValue(self.base.enz[key].k)
def plot(self):
# instead of ax.hold(False)
self.figure.clear()
enz = extract_enzyme_set("para.txt", PARAMETER_NO)
enz2 = extract_enzyme_set("para.txt",
PARAMETER_NO) # Required because ODEAnalysis
# changes enzyme values
base = ODEAnalysis(SYSTEM, 1, enz)
feed = ODEAnalysis(SYSTEM, 1, enz2, self.feed_para)
provide_condition(base)
provide_condition(feed)
ax = self.figure.add_subplot(111)
for lipid in self.lipids_to_analyze:
base_con = base.concentration_array[:, lipid]
feed_con = feed.concentration_array[:, lipid]
if not self.show_standard:
base_con = base_con * 100 / base_con[0]
feed_con = feed_con * 100 / feed_con[0]
ax.plot(base.time_array, base_con,
label=LIPID_NAMES[lipid], color=COLORS_PRIMARY[lipid],
linestyle="--")
ax.plot(feed.time_array, feed_con,
label=LIPID_NAMES[lipid] + "(with Feedback)",
color=COLORS_PRIMARY[lipid])
if self.mutant_enzyme != E_NONE:
enz3 = extract_enzyme_set("para.txt", PARAMETER_NO)
mut = ODEAnalysis(SYSTEM, 1, enz3, self.feed_para)
mut.enz[self.mutant_enzyme].v *= MUTANT_DEPLETION
provide_condition(mut)
for lipid in self.lipids_to_analyze:
mut_con = mut.concentration_array[:, lipid]
if not self.show_standard:
mut_con = mut_con * 100 / mut_con[0]
ax.plot(mut.time_array, mut_con,
label=LIPID_NAMES[lipid] + "(Mutant)",
color=COLORS_PRIMARY[lipid], linestyle="-.")
if self.show_standard:
ax.set_ylabel("Scaled Concentration")
else:
ax.set_ylabel("Concentration Percentage\n(w.r.t. Steady State)")
ax.set_xlabel("Time (arbitrary)")
ax.legend(loc=0)
plt.axvline(0, linestyle="--", color="k")
# refresh canvas
self.canvas.draw()
def plot_test():
enz = extract_enzyme_set("para.txt", 0)
enz2 = extract_enzyme_set("para.txt", 0) # Required because ODEAnalysis
# changes enzyme values
base = ODEAnalysis(S_OPEN_2, 1, enz)
# feed = ODEAnalysis(S_OPEN_2, 1, enz2, FEED_PARA)
provide_condition(base, 6)
# provide_condition(feed)
fig = plt.figure()
ax = fig.add_subplot(111)
for lipid in LIPIDS_TO_ANALYZE:
scaled_array = base.concentration_array[:, lipid]
scaled_array = [x * 100 / max(scaled_array) for x in scaled_array]
ax.plot(
base.time_array,
scaled_array,
label=LIPID_NAMES[lipid],
color=COLORS_PRIMARY[lipid],
)
# ax.plot(feed.time_array, feed.concentration_array[:, lipid],
# label=LIPID_NAMES[lipid] + "(with Feedback)",
# color=COLORS_PRIMARY[lipid])
ax.set_ylabel("Scaled Concentration")
ax.set_xlabel("Time (arbitrary)")
ax.legend(loc=0)
plt.axvline(0, linestyle="--", color="k")
plt.show()
def __init__(self, parent=None):
super(MutantWindow, self).__init__(parent)
self.setWindowTitle('Mutant Interactive Analysis')
self.figure = plt.figure()
self.canvas = FigureCanvas(self.figure)
self.toolbar = NavigationToolbar(self.canvas, self)
self.show_standard = False
self.para_dict = {}
self.mutant_enzyme = E_NONE
self.enz_box = None
enz = extract_enzyme_set("para.txt", PARAMETER_NO)
self.base = ODEAnalysis(SYSTEM, 1, enz)
if PARAMETER_NO == 0:
self.base.normalize_enzymes()
self.base.attain_steady_state()
self.parameter_box = QGridLayout()
self.ss_label = QLabel("Steady State Ratios: PIP2: 0.05, PI4P:0.05, "
"DAG: 0.008, PA: 0.1677")
self.grid = QGridLayout()
self.plot()
self.set_layout()
def plot_pi():
enz = extract_enzyme_set("para.txt", PARAMETER_SET)
# changes enzyme values
base = ODEAnalysis(S_OPEN_2, 1, enz)
if PARAMETER_SET == 0:
base.normalize_enzymes()
base.attain_steady_state()
s = [x for x in base.steady_state]
s.append(
base.steady_state[I_PMPA] + base.steady_state[I_ERPA])
s.append(
base.steady_state[I_PMPI] + base.steady_state[I_ERPI])
base.enz[MUTANT].v *= 0.1
if MUTANT == E_SOURCE:
base.enz[MUTANT].k *= 0.1
base.attain_steady_state()
mt = [x for x in base.steady_state]
mt.append(base.steady_state[I_PMPA] + base.steady_state[I_ERPA])
mt.append(base.steady_state[I_PMPI] + base.steady_state[I_ERPI])
figure = plt.figure()
ax = figure.add_subplot(111)
ind = np.arange(len(LIPID_NAMES) + 2) # the x locations for the groups
width = 0.35 # the width of the bars
ax.bar(ind, np.asanyarray(mt) / np.asanyarray(s), width, color="#00b6cb")
ax.set_xticks(ind)
k = [round(x, 3) for x in np.asanyarray(mt) / np.asanyarray(s)]
km = ""
for s in k:
km += str(s) + "\t"
print(km)
plt.axhline(1, linestyle="--", color="k")
# plt.yscale("log")
nm = [L_PMPI, L_PI4P, L_PIP2, L_DAG, L_PMPA, L_ERPA, L_CDPDAG,
L_ERPI, "PA$_{total}$", "PI$_{total}$"]
ax.set_xticklabels(nm)
ax.set_ylim(0, 2)
ax.set_ylabel("$\\frac{Mutant}{Wild Type}$ steady states")
class MutantWindow(QDialog):
def __init__(self, parent=None):
super(MutantWindow, self).__init__(parent)
self.setWindowTitle('Mutant Interactive Analysis')
self.figure = plt.figure()
self.canvas = FigureCanvas(self.figure)
self.toolbar = NavigationToolbar(self.canvas, self)
self.show_standard = False
self.para_dict = {}
self.mutant_enzyme = E_NONE
self.enz_box = None
enz = extract_enzyme_set("para.txt", PARAMETER_NO)
self.base = ODEAnalysis(SYSTEM, 1, enz)
if PARAMETER_NO == 0:
self.base.normalize_enzymes()
self.base.attain_steady_state()
self.parameter_box = QGridLayout()
self.ss_label = QLabel("Steady State Ratios: PIP2: 0.05, PI4P:0.05, "
"DAG: 0.008, PA: 0.1677")
self.grid = QGridLayout()
self.plot()
self.set_layout()
@property
def enzyme_parameters(self):
p_box = QGridLayout()
col = 0
row = 1
for i in ENZYME_NAMES:
main_box_layout = QGroupBox(i.upper())
main_box = QVBoxLayout()
main_box_layout.setLayout(main_box)
main_box_layout.setContentsMargins(1, 10, 10, 1)
box = QHBoxLayout()
box.addWidget(QLabel("Vmax"))
v = MySpinBox()
v.setValue(self.base.enz[i].v)
if i == E_PLC or i == E_SOURCE:
v.setEnabled(False)
box.addWidget(v)
box.addWidget(QLabel("Km"))
k = MySpinBox()
k.setValue(self.base.enz[i].k)
v.valueChanged.connect(partial(self.on_parameter_change, i, "v",
v))
k.valueChanged.connect(partial(self.on_parameter_change, i, "k",
k))
self.para_dict[i] = {
"v": v, "k": k
}
box.addWidget(k)
box.addStretch()
if col == 3:
row += 1
col = 1
else:
col += 1
main_box.addLayout(box)
p_box.addWidget(main_box_layout, row, col)
self.parameter_box = p_box
return p_box
@property
def mutant_list(self):
e_box = QHBoxLayout()
e_box.setContentsMargins(30, 1, 1, 1)
e_box.addStretch()
e_box.addWidget(QLabel("Mutant Enzyme : "))
self.enz_box = QComboBox(self)
self.enz_box.addItem(E_NONE)
for e in ENZYME_NAMES:
self.enz_box.addItem(e)
self.enz_box.activated[str].connect(self.on_mutant_selection)
e_box.addWidget(self.enz_box)
e_box.addStretch()
return e_box
@property
def reset_btn(self):
btn = QPushButton("Reset")
btn.clicked[bool].connect(self.on_reset_click)
return btn
@property
def print_btn(self):
btn = QPushButton("Print Parameters")
btn.clicked[bool].connect(self.print)
return btn
@property
def toggle_plot(self):
btn = QPushButton("Toggle Plot")
btn.clicked[bool].connect(self.on_toggle_plot)
return btn
def on_toggle_plot(self):
if self.show_standard:
self.show_standard = False
else:
self.show_standard = True
self.plot()
def print(self):
enz = {}
for k in self.base.enz:
enz[k] = self.base.enz[k].properties
data = {"Enzymes": enz}
print(json.dumps(data))
def reset(self):
enz = extract_enzyme_set("para.txt", PARAMETER_NO)
self.base = ODEAnalysis(SYSTEM, 1, enz)
if PARAMETER_NO == 0:
self.base.normalize_enzymes()
self.base.attain_steady_state()
for key in self.para_dict:
self.para_dict[key]["v"].setValue(self.base.enz[key].v)
self.para_dict[key]["k"].setValue(self.base.enz[key].k)
def on_reset_click(self):
self.mutant_enzyme = E_NONE
self.enz_box.setCurrentIndex(0)
self.reset()
self.plot()
def on_parameter_change(self, enzyme, pro, new_val):
if pro == "v":
self.base.enz[enzyme].v = new_val.value()
elif pro == "k":
self.base.enz[enzyme].k = new_val.value()
self.plot()
def on_mutant_selection(self, value):
self.mutant_enzyme = value
self.reset()
self.plot()
def plot(self):
self.figure.clear()
self.base.attain_steady_state()
s = self.base.steady_state
p = s[I_PMPI] + s[I_ERPI]
e_pip2 = abs((s[I_PIP2] / p) / 0.05 - 1)
e_pi4p = abs((s[I_PI4P] / p) / 0.05 - 1)
e_dag = abs((s[I_DAG] / p) / 0.008 - 1)
e_pa = abs(((s[I_PMPA] + s[I_ERPA]) / p) / 0.1677 - 1)
e_cdpdag = abs((s[I_CDPDAG] / p) / 0.001 - 1)
error = e_pip2 + e_pi4p + e_dag + e_pa + e_cdpdag
self.ss_label.setText("Steady State Ratios \n(w.r.t. Total PI): "
"\n\nPIP2: %.4f, \nPI4P: %.4f, "
"\nDAG: %.4f, \nPA: %.4f, \nCDPDAG: "
"%.4f\n\n\nTotal WT Error: "
"%.3f %% \n\nPMPI/ERPI: "
"%.4f\nPMPA/ERPA: %.4f" %
(s[I_PIP2] / p, s[I_PI4P] / p, s[I_DAG] / p,
(s[I_PMPA] + s[I_ERPA]) / p, s[I_CDPDAG] / p,
error * 100,
s[I_PMPI] / s[I_ERPI], s[I_PMPA] / s[I_ERPA]))
if self.show_standard:
self.standard_plot()
else:
self.individual_plot()
self.canvas.draw()
def individual_plot(self):
s = [x for x in self.base.steady_state]
s.append(
self.base.steady_state[I_PMPA] + self.base.steady_state[I_ERPA])
s.append(
self.base.steady_state[I_PMPI] + self.base.steady_state[I_ERPI])
if self.mutant_enzyme != E_NONE:
self.base.enz[self.mutant_enzyme].v *= MUTANT_DEPLETION
self.base.attain_steady_state()
mt = [x for x in self.base.steady_state]
mt.append(
self.base.steady_state[I_PMPA] + self.base.steady_state[I_ERPA])
mt.append(
self.base.steady_state[I_PMPI] + self.base.steady_state[I_ERPI])
ax = self.figure.add_subplot(111)
ind = np.arange(len(LIPID_NAMES) + 2) # the x locations for the groups
width = 0.35 # the width of the bars
ax.bar(ind, np.asanyarray(mt) / np.asanyarray(s), width)
ax.set_xticks(ind)
plt.axhline(1, linestyle="--")
# plt.yscale("log")
nm = [L_PMPI, L_PI4P, L_PIP2, L_DAG, L_PMPA, L_ERPA, L_CDPDAG,
L_ERPI, "PA", "PI"]
ax.set_xticklabels(nm)
if self.mutant_enzyme != E_NONE:
self.base.enz[self.mutant_enzyme].v /= MUTANT_DEPLETION
def standard_plot(self):
s = [x for x in self.base.steady_state]
self.base.enz[E_DAGK].v *= MUTANT_DEPLETION
self.base.attain_steady_state()
mt_rdga = [x for x in self.base.steady_state]
self.base.enz[E_DAGK].v /= MUTANT_DEPLETION
self.base.enz[E_LAZA].v *= MUTANT_DEPLETION
self.base.attain_steady_state()
mt_laza = [x for x in self.base.steady_state]
self.base.enz[E_LAZA].v /= MUTANT_DEPLETION
ax = self.figure.add_subplot(111)
ind = np.arange(4) # the x locations for the groups
width = 0.35 # the width of the bars
exp_observations = [1, 1, 1, 2.5]
val1 = get_ratios(s, mt_rdga)
val2 = get_ratios(s, mt_laza)
vals = val1[0], val1[1], val2[0], val2[1]
legends = ["DAG/PI\n(rdga3)", "PA/PI\n(rdga3)", "DAG/PI\n(laza22)",
"PA/PI\n(laza22)"]
ax.bar(ind, exp_observations, width, color='#3c6df0', label="WT")
ax.bar(ind + width, vals, width, color='#fe6100', label="MT")
ax.set_xticks(ind + width / 2)
plt.axhline(1, linestyle="--")
plt.axhline(2.5, linestyle="--")
ax.set_xticklabels(legends)
plt.legend(loc=0)
def set_layout(self):
btn_layout = QVBoxLayout()
btn_layout.addWidget(self.reset_btn)
btn_layout.addWidget(self.print_btn)
btn_layout.addWidget(self.toggle_plot)
self.grid.addWidget(self.ss_label, 2, 1)
self.grid.addWidget(self.toolbar, 1, 0)
self.grid.addWidget(self.canvas, 2, 0)
self.grid.addLayout(self.mutant_list, 3, 1)
self.grid.addLayout(self.enzyme_parameters, 4, 0)
self.grid.addLayout(btn_layout, 4, 1)
self.setLayout(self.grid)