I have data that has a total of 118750 samples, and each sample dimension is 79. To analyze my data, I am visualizing it. Here is the visualization image that is currently being generated:
You can see that figure is not clear. Is there any way to visualize this large dimension data in a better way.
Here is my code of the above given image:
x, y = test_data["x"], test_data["y"]
# determine the total number of plots
n, off = x.shape[1] + 1, 0
plt.rcParams["figure.figsize"] = (120, 100)
count_mk_ind = 0
for i in range(79):
plt.subplot(n, 1, off + 1)
for j in np.unique(y):
my_pl = plt.plot(
# np.ma.masked_where(y != j, y[:]), markers[count_mk_ind]
np.ma.masked_where(y != j, x[:, i])
)
plt.setp(my_pl, linewidth=1.0)
count_mk_ind += 1
count_mk_ind = 0
plt.title('Sensor Channel: '
+ str(i), y=0, loc='left', fontsize=18)
off += 1
# plt.plot(x)
markers = ['o', '+', '<', '*', '^', "D",
'>', "v", ">", "H", "4", "s",
"p", "3", "x", "_", "X", "|",
]
plt.subplot(n, 1, n)
count_marker_ind = 0
for j in np.unique(y):
plt.plot(np.ma.masked_where(y != j, y[:]),
markers[count_marker_ind],
label=class_map[count_marker_ind])
count_marker_ind += 1
plt.legend(bbox_to_anchor=(1.05, 1),
loc='upper left',
borderpad=2,
markerscale=4.,
fontsize=25)
plt.plot(y)
plt.title('Label', y=0, loc='left', fontsize=18)
plt.savefig(save_file_name, bbox_inches="tight")
plt.close()