xjtu-blacksmith/data.csv

## data.csv

          
            3
            3
            3
            3
            3
            3
            3
            3
            3
            3
            3
            3
            3
            3
            3
            3

            
              3
              2.9
              2.8
              2.71
              2.62
              2.54
              2.49
              2.45
              2.43
              2.41
              2.41
              2.4
              2.4
              2.4
              2.4
              2.4

            
              3
              2.8
              2.61
              2.42
              2.23
              2.07
              1.96
              1.89
              1.85
              1.82
              1.81
              1.81
              1.8
              1.8
              1.8
              1.8

            
              3
              2.71
              2.42
              2.11
              1.81
              1.54
              1.38
              1.3
              1.25
              1.23
              1.21
              1.2
              1.2
              1.2
              1.2
              1.2

            
              3
              2.62
              2.23
              1.81
              1.36
              0.91
              0.74
              0.66
              0.63
              0.61
              0.6
              0.6
              0.6
              0.6
              0.6
              0.6

            
              3
              2.54
              2.07
              1.54
              0.91
              0
              0
              0
              0
              0
              0
              0
              0
              0
              0
              0

            
              3
              2.49
              1.96
              1.38
              0.74
              0

            
              3
              2.45
              1.89
              1.3
              0.66
              0

            
              3
              2.43
              1.85
              1.25
              0.63
              0

            
              3
              2.42
              1.83
              1.23
              0.62
              0

            
              3
              2.41
              1.82
              1.21
              0.61
              0

            
              3
              2.41
              1.81
              1.21
              0.6
              0

## elec-sim-heat.py
# Dealing with data

import csv
import matplotlib.pyplot as plt
import scipy.ndimage
import numpy as np
#import scipy.ndimage
with open('data.csv') as f:
    f_csv = csv.reader(f)
    data = np.array(list(f_csv))
    data[data == ''] = '0'
    data = np.array(data, dtype=float) * 10
    #data = scipy.ndimage.zoom(data, 3)
    plt.matshow(data, interpolation='gaussian', origin='upper', extent=None, cmap='hot')
    plt.colorbar()
    ax = plt.gca()
    ax.set_xlim([0, 15])
    ax.set_ylim([11, 0])
    ax.xaxis.set_minor_locator(plt.MultipleLocator(1))
    ax.yaxis.set_minor_locator(plt.MultipleLocator(1))
    ax.grid(which='minor', color='black', linestyle='-', linewidth=1)
    # plt.contourf(range(0, 16), range(12, 0, -1), data)
    for i in range(12):
        for j in range(16):
            if j < 6 or i < 6:
                plt.text(j, i, "{:.1f}".format(data[i, j]), ha="center", va="center", color="#3333dd", fontsize=16)
    cs = plt.contour(data, antialiased=True, levels=[12, 18, 24], colors=['#66ee66', '#66ee66', '#33dd33'])
    plt.clabel(cs, fmt='%.0fв„ѓ', colors=['#66ee66', '#66ee66', '#33dd33'], fontsize=18)
    plt.show()
3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3
3	2.9	2.8	2.71	2.62	2.54	2.49	2.45	2.43	2.41	2.41	2.4	2.4	2.4	2.4	2.4
3	2.8	2.61	2.42	2.23	2.07	1.96	1.89	1.85	1.82	1.81	1.81	1.8	1.8	1.8	1.8
3	2.71	2.42	2.11	1.81	1.54	1.38	1.3	1.25	1.23	1.21	1.2	1.2	1.2	1.2	1.2
3	2.62	2.23	1.81	1.36	0.91	0.74	0.66	0.63	0.61	0.6	0.6	0.6	0.6	0.6	0.6
3	2.54	2.07	1.54	0.91	0	0	0	0	0	0	0	0	0	0	0
3	2.49	1.96	1.38	0.74	0
3	2.45	1.89	1.3	0.66	0
3	2.43	1.85	1.25	0.63	0
3	2.42	1.83	1.23	0.62	0
3	2.41	1.82	1.21	0.61	0
3	2.41	1.81	1.21	0.6	0
	# Dealing with data

	import csv
	import matplotlib.pyplot as plt
	import scipy.ndimage
	import numpy as np
	#import scipy.ndimage
	with open('data.csv') as f:
	f_csv = csv.reader(f)
	data = np.array(list(f_csv))
	data[data == ''] = '0'
	data = np.array(data, dtype=float) * 10
	#data = scipy.ndimage.zoom(data, 3)
	plt.matshow(data, interpolation='gaussian', origin='upper', extent=None, cmap='hot')
	plt.colorbar()
	ax = plt.gca()
	ax.set_xlim([0, 15])
	ax.set_ylim([11, 0])
	ax.xaxis.set_minor_locator(plt.MultipleLocator(1))
	ax.yaxis.set_minor_locator(plt.MultipleLocator(1))
	ax.grid(which='minor', color='black', linestyle='-', linewidth=1)
	# plt.contourf(range(0, 16), range(12, 0, -1), data)
	for i in range(12):
	for j in range(16):
	if j < 6 or i < 6:
	plt.text(j, i, "{:.1f}".format(data[i, j]), ha="center", va="center", color="#3333dd", fontsize=16)
	cs = plt.contour(data, antialiased=True, levels=[12, 18, 24], colors=['#66ee66', '#66ee66', '#33dd33'])
	plt.clabel(cs, fmt='%.0fв„ѓ', colors=['#66ee66', '#66ee66', '#33dd33'], fontsize=18)
	plt.show()