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Finish method and results, and add script for including all colormaps in one figure.

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This commit is contained in:
Janita Willumsen
2023-12-31 18:49:06 +01:00
parent 36b91e5206
commit e9ad99210a
19 changed files with 180 additions and 41 deletions
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26
python_scripts/colormap.py
View File

@@ -19,6 +19,7 @@ plt.rcParams.update(params)
def plot():
ticks = [0, 0.25, 0.5, 0.75, 1.0]
with open("data/color_map.txt") as f:
lines = f.readlines()
size = int(lines[0])
@@ -38,16 +39,19 @@ def plot():
np.multiply(arr, arr.conj()).real,
interpolation="nearest",
cmap=sns.color_palette("mako", as_cmap=True),
extent=[0, 1.0, 0, 1.0]
)
color_map2 = ax2.imshow(
arr.real,
interpolation="nearest",
cmap=sns.color_palette("mako", as_cmap=True),
extent=[0, 1.0, 0, 1.0]
)
color_map3 = ax3.imshow(
arr.imag,
interpolation="nearest",
cmap=sns.color_palette("mako", as_cmap=True),
extent=[0, 1.0, 0, 1.0]
)
# Create color bar
@@ -60,10 +64,26 @@ def plot():
ax2.grid(False)
ax3.grid(False)
# Set custom ticks
ax1.set_xticks(ticks)
ax1.set_yticks(ticks)
ax2.set_xticks(ticks)
ax2.set_yticks(ticks)
ax3.set_xticks(ticks)
ax3.set_yticks(ticks)
# Set labels
ax1.set_xlabel("x-axis")
ax1.set_ylabel("y-axis")
ax2.set_xlabel("x-axis")
ax2.set_ylabel("y-axis")
ax3.set_xlabel("x-axis")
ax3.set_ylabel("y-axis")
# Save the figures
fig1.savefig(f"latex/images/color_map_{i}_prob.pdf")
fig2.savefig(f"latex/images/color_map_{i}_real.pdf")
fig3.savefig(f"latex/images/color_map_{i}_imag.pdf")
fig1.savefig(f"latex/images/color_map_{i}_prob.pdf", bbox_inches="tight")
fig2.savefig(f"latex/images/color_map_{i}_real.pdf", bbox_inches="tight")
fig3.savefig(f"latex/images/color_map_{i}_imag.pdf", bbox_inches="tight")
# Close figures
plt.close(fig1)

93
python_scripts/colormap_all.py Normal file
View File

@@ -0,0 +1,93 @@
import ast
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
sns.set_theme()
params = {
"font.family": "Serif",
"font.serif": "Roman",
"text.usetex": True,
"axes.titlesize": "large",
"axes.labelsize": "large",
"xtick.labelsize": "large",
"ytick.labelsize": "large",
"legend.fontsize": "medium",
}
plt.rcParams.update(params)
def plot():
fig, axes = plt.subplots(nrows=3, ncols=3)
with open("data/color_map.txt") as f:
lines = f.readlines()
size = int(lines[0])
for i, line in enumerate(lines[1:]):
# Create figures for each plot
# fig1, ax1 = plt.subplots()
# fig2, ax2 = plt.subplots()
# fig3, ax3 = plt.subplots()
arr = line.strip().split("\t")
arr = np.asarray(list(map(lambda x: complex(*ast.literal_eval(x)), arr)))
# Reshape and transpose array
arr = arr.reshape(size, size).T
# Plot color maps
color_map1 = axes[i,0].imshow(
np.multiply(arr, arr.conj()).real,
interpolation="nearest",
cmap=sns.color_palette("mako", as_cmap=True)
)
color_map2 = axes[i,1].imshow(
arr.real,
interpolation="nearest",
cmap=sns.color_palette("mako", as_cmap=True)
)
color_map3 = axes[i,2].imshow(
arr.imag,
interpolation="nearest",
cmap=sns.color_palette("mako", as_cmap=True)
)
# Create color bar
fig.colorbar(color_map1, ax=axes)
# fig2.colorbar(color_map2, ax=ax2)
# fig3.colorbar(color_map3, ax=ax3)
# # Remove grids
axes.grid(False)
# ax2.grid(False)
# ax3.grid(False)
# # Set custom ticks
# ax1.set_xticks(ticks)
# ax1.set_yticks(ticks)
# ax2.set_xticks(ticks)
# ax2.set_yticks(ticks)
# ax3.set_xticks(ticks)
# ax3.set_yticks(ticks)
# # Set labels
# ax1.set_xlabel("x-axis")
# ax1.set_ylabel("y-axis")
# ax2.set_xlabel("x-axis")
# ax2.set_ylabel("y-axis")
# ax3.set_xlabel("x-axis")
# ax3.set_ylabel("y-axis")
# # Save the figures
fig.savefig(f"latex/images/color_map_all.pdf", bbox_inches="tight")
# fig2.savefig(f"latex/images/color_map_{i}_real.pdf", bbox_inches="tight")
# fig3.savefig(f"latex/images/color_map_{i}_imag.pdf", bbox_inches="tight")
# # Close figures
# plt.close(fig1)
# plt.close(fig2)
# plt.close(fig3)
if __name__ == "__main__":
plot()

7
python_scripts/detector.py
View File

@@ -27,6 +27,7 @@ def plot():
"latex/images/double_slit_detector.pdf",
"latex/images/triple_slit_detector.pdf",
]
colors = sns.color_palette("mako", n_colors=2)
for file, output in zip(files, outputs):
with open(file) as f:
lines = f.readlines();
@@ -43,8 +44,10 @@ def plot():
slice *= norm
slice = np.asarray([i * i.conjugate() for i in slice])
ax.plot(x, slice)
plt.savefig(output)
ax.plot(x, slice, color=colors[0])
ax.set_xlabel("Detector screen (y-axis)")
ax.set_ylabel("Detection probability")
fig.savefig(output, bbox_inches="tight")
plt.close(fig)