mbergmann/gpgrewe2024
1
1
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Changes integral function

Browse Source
This commit is contained in:
Diana 2024-10-25 17:09:29 +02:00
parent 3a1d7748ba
commit 423fe451be
1 changed files with 23 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

42
code/plot_functions.py
View File

@ -72,14 +72,16 @@ functions_path = r"C:\Users\diana\OneDrive - UT Cloud\Master\GPs\GP1_Grewe\Proje
sys.path.append(functions_path)
import useful_functions as u
import matplotlib.ticker as ticker
import matplotlib.patches as mpatches
def float_formatter(x, _):
"""Format the y-axis values as floats with a specified precision."""
return f'{x:.5f}'
def plot_highlighted_integrals(ax, frequency, power, points, color_mapping, points_categories, delta=2.5):
"""
Highlight integrals on the existing axes of the power spectrum.
Highlights integrals on the existing axes of the power spectrum for a given dataset.
Parameters
----------
@ -102,38 +104,40 @@ def plot_highlighted_integrals(ax, frequency, power, points, color_mapping, poin
-------
None
"""
ax.plot(frequency, power, color = "k") # Plot power spectrum on the existing axes
_, _, AM, df, eodf, nyquist, stim_freq = u.sam_data(sam)
# Plot the power spectrum on the provided axes
ax.plot(frequency, power, color="k")
for point in points:
# Calculate the integral and local mean
integral, local_mean = u.calculate_integral_2(frequency, power, point)
# Identify the category for the current point
point_category = next((cat for cat, pts in points_categories.items() if point in pts), "Unknown")
# Check if the point is valid
# Assign color based on category, or default to grey if unknown
color = color_mapping.get(point_category, 'gray')
# Calculate the integral and check validity
integral, local_mean = u.calculate_integral_2(frequency, power, point)
valid = u.valid_integrals(integral, local_mean, point)
if valid:
# Define color based on the category of the point
point_category = next((cat for cat, pts in points_categories.items() if point in pts), "Unknown")
color = next((c for cat, c in color_mapping.items() if point in points_categories[cat]), 'gray')
# Shade the region around the point where the integral was calculated
if valid:
# Highlight valid points with a shaded region
ax.axvspan(point - delta, point + delta, color=color, alpha=0.2, label=f'{point_category}')
# Text with categories and colors
ax.text(1000, 5.8e-5, "AM", fontsize=10, color="green", alpha=0.2)
ax.text(1000, 5.6e-5, "Nyquist", fontsize=10, color="blue", alpha=0.2)
ax.text(1000, 5.4e-5, "EODf", fontsize=10, color="red", alpha=0.2)
ax.text(1000, 5.2e-5, "Stimulus frequency", fontsize=10, color="orange", alpha=0.2)
ax.text(1000, 5.0e-5, "EODf of awake fish", fontsize=10, color="purple", alpha=0.2)
# Set plot limits and labels
ax.set_xlim([0, 1200])
ax.set_ylim([0, 6e-5])
ax.axvline(nyquist, color = "k", linestyle = "--")
ax.set_xlabel('Frequency (Hz)')
ax.set_ylabel('Power')
ax.set_title('Power Spectrum with highlighted Integrals')
ax.set_title('Power Spectrum with Highlighted Integrals')
# Apply float formatting to the y-axis
ax.yaxis.set_major_formatter(ticker.FuncFormatter(float_formatter))
ax.legend(loc="upper right")