def test_results2_expvalues():
"""
compares the calculated expected values to already verified reference data
"""
expvals = rd.read_xyformat("test_potentials/test_results2/expvalues.dat")
expvals_reference = rd.read_xyformat(
"test_potentials/test_results2_reference/expvalues.dat")
assert expvals == pytest.approx(expvals_reference)
def test_results2_energies():
"""
compares the calculated eigenvalues to already verified reference data
"""
energies = rd.read_xyformat("test_potentials/test_results2/energies.dat")
energies_reference = rd.read_xyformat(
"test_potentials/test_results2_reference/energies.dat")
assert energies == pytest.approx(energies_reference)
def test_results2_wavefuncs():
"""
compares the calculated eigenstates to already verified reference data
"""
wavefuncs = rd.read_xyformat("test_potentials/test_results2/wavefuncs.dat")
wavefuncs_reference = rd.read_xyformat(
"test_potentials/test_results2_reference/wavefuncs.dat")
assert wavefuncs == pytest.approx(wavefuncs_reference)
def test_results2_potential():
"""
compares the calculated potential to already verified reference data
"""
potential = rd.read_xyformat("test_potentials/test_results2/potential.dat")
potential_reference = rd.read_xyformat(
"test_potentials/test_results2_reference/potential.dat")
assert potential == pytest.approx(potential_reference)
def plot(scalingfactor, changerange, axisrange):
"""
reads the saved files and plots the information
"""
colorcycle = ["b", "g", "r", "c", "m", "y", "k"]
activecolor = "b"
wavefuncs = rd.read_xyformat("wavefuncs.dat")
potential = rd.read_xyformat("potential.dat")
energies = rd.read_xyformat("energies.dat")[0]
expvals = rd.read_xyformat("expvalues.dat")
_, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
for ii in range(int(rd.last_eigenvalue() + 1 - rd.first_eigenvalue())):
scaled_wavefunc = [
element * scalingfactor + energies[ii]
for element in wavefuncs[ii + 1]
]
ax1.plot(wavefuncs[0], scaled_wavefunc, color=activecolor)
ax1.plot(expvals[0][ii], energies[ii], color=activecolor, marker="x")
ax1.axhline(y=energies[ii], alpha=0.2, color="grey", linewidth=1)
ax2.plot(expvals[1][ii], energies[ii], color=activecolor, marker="x")
ax2.axhline(y=energies[ii], alpha=0.2, color="grey", linewidth=1)
index = (colorcycle.index(activecolor) + 1) % len(colorcycle)
activecolor = colorcycle[index]
ax1.plot(potential[0], potential[1])
ax1.set_ylim([
min(energies) - max(abs(energies)) * 0.1,
max(energies) + max(abs(energies)) * 0.1
])
ax2.set_xlim([0, max(expvals[1]) * 1.1])
if changerange:
ax1.set_xlim([axisrange[0], axisrange[1]])
ax1.set_ylim([axisrange[2], axisrange[3]])
ax1.set_title("Potential, Eigenstates, ⟨x⟩")
ax2.set_title("σ\u2093")
ax1.set_ylabel("Energy [Hartree]")
ax1.set_xlabel("x [Bohr]")
ax2.set_xlabel("x [Bohr]")
plt.show()
def plot(inputpath, scalingfactor, changerange, axisrange):
"""
reads the saved files and plots the information
:type inputpath: string
:param inputpath: directory of the calculated .dat files to be plotted
:type scalingfactor: float
:param scalingfactor: amount the eigenstates will be scaled by (for better results)
:type changerange: boolean
:param changerange: if the axis range will be changed or left at the default
:type axisrange: [float]
:param axisrange: has to be a list with 4 entries to specify xmin, xmax, ymin and ymax
"""
colorcycle = ["b", "g", "r", "c", "m", "y", "k"]
activecolor = "b"
#loading information from saved files
if not inputpath.endswith("/"):
inputpath = inputpath + "/"
wavefuncs = rd.read_xyformat(inputpath + "wavefuncs.dat")
potential = rd.read_xyformat(inputpath + "potential.dat")
energies = rd.read_xyformat(inputpath + "energies.dat")[0]
expvals = rd.read_xyformat(inputpath + "expvalues.dat")
_, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
if scalingfactor == 0:
scalingfactor = (max(energies) - min(energies)) / len(energies) / 2
#plotting eigenstates, potential, expected values and uncertainties
for (ii, energy) in enumerate(energies):
scaled_wavefunc = [
element * scalingfactor + energy for element in wavefuncs[ii + 1]
]
ax1.plot(wavefuncs[0], scaled_wavefunc, color=activecolor)
ax1.plot(expvals[0][ii], energy, color=activecolor, marker="x")
ax1.axhline(y=energy, alpha=0.2, color="grey", linewidth=1)
ax2.plot(expvals[1][ii], energy, color=activecolor, marker="x")
ax2.axhline(y=energy, alpha=0.2, color="grey", linewidth=1)
index = (colorcycle.index(activecolor) + 1) % len(colorcycle)
activecolor = colorcycle[index]
#changing plot settings
ax1.plot(potential[0], potential[1], color="black")
ax1.set_ylim([
min(energies) - max(abs(energies)) * 0.1,
max(energies) + max(abs(energies)) * 0.1
])
ax2.set_xlim([0, max(expvals[1]) * 1.1])
if changerange:
ax1.set_xlim([axisrange[0], axisrange[1]])
ax1.set_ylim([axisrange[2], axisrange[3]])
ax1.set_title("Potential, Eigenstates, ⟨x⟩")
ax2.set_title("σ\u2093")
ax1.set_ylabel("Energy [Hartree]")
ax1.set_xlabel("x [Bohr]")
ax2.set_xlabel("x [Bohr]")
print("The Eigenstates are scaled by a factor of " +
str(round(scalingfactor, 4)) + ".")
plt.show()
