def analyse_diffusion_rate_and_density(size, number_of_examples=150):
"""
Analiza tocke 1
Kakšen vpliv ima na oscilacije gostota populacije celic, hitrost difuzije in velikost prostora?
D [10^-2, 10^2]
velikost prostora: 10x10
gostota populacije: [0.01, 1]
"""
x = []
y = []
result = []
example_num = 0
"""Vpliv hitrosti difuzije na oscilacije"""
for density in np.linspace(start=.1, stop=1, num=number_of_examples):
tmp = []
for d in np.linspace(start=.01, stop=1,
num=number_of_examples): # .1 1
rep = r.Repressilator_S_PDE()
rep.set_params(D1=d, density=density, size=size)
# check if model oscillates
[osc, freq, period, amplitude, damped] = rep.run()
print(
"#%d | density: %f, | oscillates: %d, frequency: %f, period: %f, amplitude: %f"
% (example_num, density, osc, freq, period, amplitude))
example_num += 1
del rep
y.append(d)
x.append(density)
tmp.append(osc)
result.append(tmp)
result = np.array(result)
print(result)
x = np.unique(x)
x = list(np.around(x, decimals=2))
print(x)
y = np.unique(y)
y = list(np.around(y, decimals=2))
print(y)
# draw heat map
make_heatmap(x, y, result)
def analyse_diffusion_rate(size=10, number_of_examples=150):
"""
Vpliv hitrosti difuzije na oscilacije pri podani velikosti prostora
:return:
"""
example_num = 0
x_per = []
y_per = []
x_amp = []
y_amp = []
for d in np.linspace(start=.01, stop=.8, num=number_of_examples):
rep = r.Repressilator_S_PDE()
rep.set_params(D1=d, density=0.4, size=size)
[osc, freq, period, amplitude, damped] = rep.run()
print(
"#%d | d: %f, | oscillates: %d, frequency: %f, period: %f, amplitude: %f"
% (example_num, d, osc, freq, period, amplitude))
if osc:
# period graph
x_per.append(period)
y_per.append(d)
# amplitude graph
x_amp.append(amplitude)
y_amp.append(d)
example_num += 1
del rep
# draw graph
plt.subplot(2, 1, 1)
plt.title('Vpliv hitrosti difuzije na amplitudo v prostoru %dx%d' %
(size, size))
plt.plot(y_amp, x_amp)
plt.ylabel('Amplituda')
plt.xlabel('Hitrost difuzije')
plt.subplot(2, 1, 2)
plt.title('Vpliv hitrosti difuzije na periodo v prostoru %dx%d' %
(size, size))
plt.plot(y_per, x_per)
plt.ylabel('Perioda')
plt.xlabel('Hitrost difuzije')
plt.show()
def makeHeatmap(numberOfSamples=1):
# merjenje casa
timeMeasure = time.time()
r = rep.Repressilator_S_PDE()
results = []
# numberOfSamples --> USED FOR LOGSPACE function
# GRAF
fig = plt.figure(1)
plt.rcParams.update({'font.size': 10})
plt.rcParams.update({'xtick.major.size': 6})
plt.rcParams.update({'ytick.major.size': 6})
params = ["", "alpha", "beta", "delta_m", "kappa"]
paramsNumbers = [1, 2, 3, 4]
counter = 1
for i in paramsNumbers:
for j in xrange(i, 5):
r.load_params_range()
results = []
ax = plt.subplot(4, 4, counter)
# if i == 1:
# plt.xlabel('Alfa')
# if i == 2:
# plt.xlabel('Beta')
# if i == 3:
# plt.xlabel('Delta_m')
# if i == 4:
# plt.xlabel('Kappa')
# if j == 1:
# plt.ylabel('Alfa')
# if j == 2:
# plt.ylabel('Beta')
# if j == 3:
# plt.ylabel('Delta_m')
# if j == 4:
# plt.ylabel('Kappa')
for FIRST_PARAM in np.logspace(start=-3,
stop=1,
num=numberOfSamples,
base=10.0):
helperArray = []
for SECOND_PARAM in np.logspace(start=-3,
stop=1,
num=numberOfSamples,
base=10.0):
print("%s: %f, %s: %f." %
(params[i], FIRST_PARAM, params[j], SECOND_PARAM))
if i == 1:
r.load_params_range_single(alpha=FIRST_PARAM)
# plt.xlabel('Alfa')
if i == 2:
r.load_params_range_single(beta=FIRST_PARAM)
# plt.xlabel('Beta')
if i == 3:
r.load_params_range_single(delta_m=FIRST_PARAM)
# plt.xlabel('Delta_m')
if i == 4:
r.load_params_range_single(kappa=FIRST_PARAM)
# plt.xlabel('Kappa')
if j == 1:
r.load_params_range_single(alpha=SECOND_PARAM)
# plt.ylabel('Alfa')
if j == 2:
r.load_params_range_single(beta=SECOND_PARAM)
# plt.ylabel('Beta')
if j == 3:
r.load_params_range_single(delta_m=SECOND_PARAM)
# plt.ylabel('Delta_m')
if j == 4:
r.load_params_range_single(kappa=SECOND_PARAM)
# plt.ylabel('Kappa')
helperArray.append(r.run()[0])
results.append(helperArray)
file = open(
"results-k-params/44{}-{}.txt".format(counter,
numberOfSamples), "w")
file.write(str(results))
file.close()
im = ax.imshow(results)
ax.set_xscale('log')
ax.set_yscale('log')
# ax.set_title('Alfa in alfa')
# plt.xlabel('Alfa')
# plt.ylabel('Alfa')
counter = counter + 1
counter = counter + i
plt.subplots_adjust(top=0.92,
bottom=0.08,
left=0.10,
right=0.95,
hspace=0.25,
wspace=0.35)
plt.show()
fig.savefig('results-k-params/final-{}.png'.format(numberOfSamples))
print("Porabljen cas: {} s.".format(time.time() - timeMeasure))
counter = counter + i
plt.subplots_adjust(top=0.92,
bottom=0.08,
left=0.10,
right=0.95,
hspace=0.25,
wspace=0.35)
plt.show()
fig.savefig('results-k-params/final-{}.png'.format(numberOfSamples))
print("Porabljen cas: {} s.".format(time.time() - timeMeasure))
if __name__ == "__main__":
r = rep.Repressilator_S_PDE()
results = []
# IMPORTANT: RUN ONLY 1 of following methods!
# run makeHeatmap for plot with all subplots
# samples = 15 # USED FOR LOGSPACE function
# makeHeatmap(samples)
# run makePlotFromData with filename to draw only 1 heatmap for specific run
# filename = "results-k-params/443-15" #WITHOUT TXT!
# samples = 15
# randomSeed = 1
# labelaX = "Alfa"
# labelaY = "Delta_m"
# makePlotFromData(filename, samples, randomSeed, labelx=labelaX, labely=labelaY)
def analyse_density(size=10, number_of_examples=150):
"""
Vpliv gostote celic na oscilacije pri podani velikosti prostora
:return:
"""
example_num = 0
x_per = []
y_per = []
x_amp = []
y_amp = []
x_freq = []
y_freq = []
for density in np.linspace(start=.1, stop=1, num=number_of_examples):
rep = r.Repressilator_S_PDE()
rep.set_params(density=density, size=size)
[osc, freq, period, amplitude, damped] = rep.run()
print(
"#%d | density: %f, | oscillates: %d, frequency: %f, period: %f, amplitude: %f"
% (example_num, density, osc, freq, period, amplitude))
if osc:
# period graph
x_per.append(period)
y_per.append(density)
# amplitude graph
x_amp.append(amplitude)
y_amp.append(density)
x_freq.append(freq)
y_freq.append(density)
example_num += 1
del rep
plt.subplot(3, 1, 1)
plt.title('Vpliv gostote celic na amplitudo v prostoru %dx%d' %
(size, size))
# x_smooth = np.linspace(np.array(x_amp).max(), np.array(x_amp).min(), number_of_examples)
# y_smooth = spline(x_amp, y_amp, x_smooth)
y_smooth = gaussian_filter1d(y_amp, sigma=2)
plt.plot(y_smooth, x_amp)
plt.ylabel('Amplituda')
plt.xlabel('Gostota')
plt.subplot(3, 1, 2)
plt.title('Vpliv gostote celic na periodo v prostoru %dx%d' % (size, size))
y_smooth = gaussian_filter1d(y_per, sigma=2)
plt.plot(y_smooth, x_per)
plt.ylabel('Perioda')
plt.xlabel('Gostota')
plt.subplot(3, 1, 3)
plt.title('Vpliv gostote celic na frekvenco v prostoru %dx%d' %
(size, size))
y_smooth = gaussian_filter1d(y_freq, sigma=2)
plt.plot(y_smooth, x_freq)
plt.ylabel('Frekvenca')
plt.xlabel('Gostota')
plt.show()