Technologie Informacyjne i Komunikacyjne R 2024/2025

#%%
from matplotlib import pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
#%%
def blackbody(X, a, b):
    return a*X**3/(np.exp(b*X) +1)
#%%
X = np.linspace(0,10,1000)
a=10
b=1.5
Y = blackbody(X, a, b)
plt.plot(X, Y)
# %%
#sigma=0.1
#noise = np.random.normal(0,sigma,size=len(X))
Y = np.random.poisson(blackbody(X,a,b))
plt.plot(X, Y)
# %%
p0 = [a, b]
popt, pcov, = curve_fit(blackbody, X, Y, p0=p0)
#%%
plt.plot(X, Y, 'o')
plt.plot(X, blackbody(X, *popt))
#%%
psigma = np.sqrt(np.diag(pcov))
for i, parameter in enumerate(popt):
    print(f'parameter #{i} = {parameter:.2f}\
+/- {psigma[i]:.2f}')
#%%
plt.imshow(pcov, cmap='viridis_r')
plt.colorbar()
#%%

#%%
from matplotlib import pyplot as plt
import numpy as np
#%%
x = np.linspace(-1,1,100)
y = np.linspace(-1,1,100)
X, Y = np.meshgrid(x,y)
#%%
plt.imshow(Y)
#%%
Z = np.exp(-X**2-Y**2)*(X-Y+X**2-Y**3)
#%%
plt.imshow(Z)
#%%
plt.contourf(X, Y, Z, levels=15)
plt.colorbar()
plt.xlabel('X')
plt.ylabel('Y')
#%%
plt.pcolor(X, Y, Z)
#%%
plt.plot(x, Z[50,:])
#%%
plt.plot(x, np.sum(Z, axis=(0,1)))
#%%
np.save('file.npy', Z)
Zfile = np.load('file.npy')

#%%
from matplotlib import pyplot as plt
import numpy as np
#%%
X = np.linspace(-1,1,1000)
n =3
Y = np.exp(X**n)
#%%
ax1 = plt.subplot(1, 2, 1)
plt.title('Wykres')
plt.plot(X, Y, '--')
#plt.xlabel('t (μs)')
plt.xlabel('$t\ (\mu s)$')
plt.ylabel('h (m)')
plt.grid()

ax2 = plt.subplot(1, 2, 2, sharey = ax1)
plt.plot(X, Y**2, '-')

plt.sca(ax1) # set current axes
#plt.gca() # get current axes
plt.plot(X, np.sin(X))
#%%
from scipy.special import hermite
nrows = 4
ncols = 4
fig, axs = plt.subplots(nrows=nrows, ncols=ncols)
for i in range(nrows):
    for j in range(ncols):
        plt.sca(axs[i,j])
        plt.plot(X, hermite(i+j)(X*2)*np.exp(-5*X**2)/2**(i+j))
        if i != nrows - 1:
            plt.gca().set_xticklabels([])
        if j != 0:
            plt.gca().set_yticklabels([])
        plt.xlim(-1.15,1.15)
        plt.ylim(-1.8,1.8)
plt.subplots_adjust(wspace=0.0, hspace=0.0)
plt.savefig('wykres.pdf')
#%%
for ax in axs:
# %%
get_ipython().run_line_magic('matplotlib', 'qt')