EasyMachineLearningDemo / visualization /draw_data_fit_total.py
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2024/02/20/14:15
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import numpy as np
from matplotlib import pyplot as plt
from static.new_class import PaintObject
from static.config import Config
def draw_data_fit_total(input_dict, paint_object: PaintObject):
plt.figure(figsize=(10, 6), dpi=300)
for i, input_dict_items in enumerate(input_dict.items()):
name, cur_list = input_dict_items
if i == len(input_dict.keys())-1:
final_list = cur_list
plt.plot(
np.array([x for x in range(len(cur_list[0]))]),
cur_list[0],
"-",
color=paint_object.get_color_cur_list()[i],
alpha=0.9,
label=paint_object.get_label_cur_list()[i]
)
plt.plot(
np.array([x for x in range(len(final_list[1]))]),
final_list[1],
"--",
color=paint_object.get_color_cur_list()[len(input_dict.keys())],
alpha=0.9,
label=paint_object.get_label_cur_list()[len(input_dict.keys())]
)
plt.title(paint_object.get_name())
plt.xlabel(paint_object.get_x_cur_label())
plt.ylabel(paint_object.get_y_cur_label())
plt.legend()
# plt.savefig("./diagram/{}.png".format(title), dpi=300)
# plt.show()
paint_object.set_color_cur_num(len(input_dict.values())+1)
paint_object.set_label_cur_num(len(input_dict.values())+1)
return plt, paint_object