Source code for utils.hom_coupler_orientation

import numpy as np
import matplotlib.pyplot as plt

from scipy import interpolate
from utils.file_reader import FileReader
import matplotlib as mpl
import seaborn as sns
fr = FileReader()

[docs]def plot_settings(): mpl.rcParams['xtick.labelsize'] = 18 mpl.rcParams['ytick.labelsize'] = 18 mpl.rcParams['axes.labelsize'] = 20 mpl.rcParams['axes.titlesize'] = 20 mpl.rcParams['legend.fontsize'] = 20 mpl.rcParams['legend.title_fontsize'] = 20 mpl.rcParams['figure.figsize'] = [10, 6] mpl.rcParams['figure.dpi'] = 100
# file = fr.excel_reader(r"D:\Dropbox\HC_FPC_Configs.xlsx") # print(file["2hc_2fpc"]["angle_corr"].to_list()) # categories = file["2hc_2fpc"]["angle_corr"].to_list() # # angle = file["2hc_2fpc"]["angle_corr"].to_list() # hc2_fpc1 = file["2hc_1fpc"]["Z"].to_list() # hc2_fpc2 = file["2hc_2fpc"]["Z"].to_list() # # plt.rcParams.update({ # "figure.facecolor": (1.0, 1.0, 1.0, 0.0), # red with alpha = 30% # "axes.facecolor": (1.0, 1.0, 1.0, 0.0), # green with alpha = 50% # "savefig.facecolor": (1.0, 1.0, 1.0, 0.0), # blue with alpha = 20% # }) # fig, ax = plt.subplots(figsize=(9.8, 6)) #, subplot_kw = dict(polar = True) # ax.plot(angle, hc2_fpc1, label='2HC1FPC', marker='o', lw=3) # ax.plot(angle, hc2_fpc2, label='2HC2FPC', marker='o', lw=3) # ax.set_xlabel(r"$\alpha$") # ax.set_ylabel(r"Z_$_{\mathrm{T, TM_{110}}} \mathrm{k\Omega/m}$") # ax.legend() # plt.tight_layout() # plt.show() if __name__ == '__main__': plot_settings() ##################### from matplotlib import ticker, cm, colors # surface plot file = fr.excel_reader(r"D:\Dropbox\HC_FPC_Configs.xlsx") sheet = "4hc_1fpc_2angles" ang = (file[sheet]["angle"]).to_list() ang_fpc = file[sheet]["angle_fpc"].to_list() X = np.reshape(ang, (10, 14)) Y = np.reshape(ang_fpc, (10, 14)) Z = file[sheet]["ZT"].to_list() Z2 = np.reshape(Z, np.shape(X)) xnew, ynew, znew = X, Y, Z2 print(xnew) print(ynew) fig = plt.figure(figsize=(18, 4)) ax = fig.gca() xticks, yticks = xnew[0], ynew.T[0] g = sns.heatmap(znew, cmap=cm.Pastel1, annot=True, norm=colors.LogNorm(vmin=10, vmax=25), linewidths=.5, ax=ax, xticklabels=xticks, yticklabels=yticks, cbar_kws=dict(pad=0.01), annot_kws={"size": 14}) ax.xaxis.set_ticks_position('top') ax.xaxis.set_label_position('top') plt.xlabel(r"$\beta [\mathrm{^\circ}]$") plt.ylabel(r"$\alpha [\mathrm{^\circ}]$") fig.tight_layout() plt.show()