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128 lines (99 loc) · 3.46 KB
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import pdb
import numpy as np
import matplotlib.pyplot as plt
RAW_SPECTRUM_LENGTH = 16314
PROCESSED_SPECTRUM_LENGTH = 8172
MIN_PPM = -2
MAX_PPM = 12
def find_ppm_value(idx):
return round((14 * (idx) / RAW_SPECTRUM_LENGTH -2), 2)
def plot_all_shap_values(shap_values, spectrum, save_name):
# take absolute value
# shap_values = np.absolute(shap_values)
# normalize each ppm
spectrum = spectrum / np.amax(spectrum,axis=0,keepdims=True)
# # prepare scatter plot entries
xs = []
ys = []
vals = []
sizes = []
for i in range(shap_values.shape[1]):
for j in range(shap_values.shape[0]):
xs.append((i+1))
ys.append(shap_values[j,i])
vals.append(spectrum[j,i])
sizes.append(1)
plt.figure()
res = plt.scatter(xs,ys,c=vals,s=sizes,marker='o',cmap="cool",alpha=0.3)
cbar = plt.colorbar()
cbar.ax.set_ylabel('Signal Amplitude', rotation=90)
cbar.set_ticks([])
cbar.set_ticklabels([])
cbar.ax.text(0.5, -0.01, 'Low', transform=cbar.ax.transAxes,
va='top', ha='center')
cbar.ax.text(0.5, 1.01, 'High', transform=cbar.ax.transAxes,
va='bottom', ha='center')
# change x axis scale
locs, labels = plt.xticks()
locs = np.arange(-1000, 9000, 500)
labels = [find_ppm_value(float(item)) for item in locs]
plt.xticks(locs, labels,rotation = (45), fontsize = 10, va='top', ha='center')
# set axis labels
plt.xlabel("ppm")
plt.ylabel("SHAP Value")
plt.tight_layout()
plt.savefig(save_name+".pdf")
plt.close()
def plot_top_k_shap_values(shap_values, spectrum, k, save_name):
# take absolute value
abs_shap_values = np.absolute(shap_values)
max_abs_shap_values = np.amax(abs_shap_values, axis=0)
top_k_ind = max_abs_shap_values.argsort()[(-1)*k:][::-1]
print("Indices with top " + str(k) +" maximum shap value:")
temp = [find_ppm_value(x) for x in top_k_ind]
temp.sort()
print(temp)
# normalize each ppm
spectrum = spectrum / np.amax(spectrum,axis=0,keepdims=True)
# # prepare scatter plot entries
xs = []
ys = []
vals = []
sizes = []
xs_ = []
ys_ = []
sizes_ = []
for i in range(shap_values.shape[1]):
if i in top_k_ind:
for j in range(shap_values.shape[0]):
xs.append((i+1))
ys.append(shap_values[j,i])
vals.append(spectrum[j,i])
sizes.append(1)
else:
xs_.append((i+1))
ys_.append(0)
# vals.append(0)
sizes_.append(1)
plt.figure()
res = plt.scatter(xs,ys,c=vals,s=sizes,marker='o',cmap="cool",alpha=0.3)
cbar = plt.colorbar()
cbar.ax.set_ylabel('Signal Amplitude', rotation=90)
cbar.set_ticks([])
cbar.set_ticklabels([])
cbar.ax.text(0.5, -0.01, 'Low', transform=cbar.ax.transAxes,
va='top', ha='center')
cbar.ax.text(0.5, 1.01, 'High', transform=cbar.ax.transAxes,
va='bottom', ha='center')
res = plt.scatter(xs_,ys_,c='k',s=sizes_,marker='o',alpha=0.3)
# change x axis scale
locs, labels = plt.xticks()
locs = np.arange(-1000, 9000, 500)
labels = [find_ppm_value(float(item)) for item in locs]
plt.xticks(locs, labels,rotation = (45), fontsize = 10, va='top', ha='center')
# set axis labels
plt.xlabel("ppm")
plt.ylabel("SHAP Value")
plt.tight_layout()
plt.savefig(save_name+".pdf")
plt.close()