[PYTHON] Draw heat map SEABORN.HEATMAP

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1. Detailed explanation of parameters

seaborn.heatmap（）

seaborn.heatmap(data, vmin=None, vmax=None, cmap=None, center=None, robust=False, annot=None, fmt=‘.2g’, annotkws=None, linewidths=0, linecolor=‘white’, cbar=True, cbarkws=None, cbar_ax=None, square=False, ax=None, xticklabels=True, yticklabels=True, mask=None, **kwargs)

data：矩阵数据集，可以使numpy的数组（array），如果是pandas的dataframe，则df的index/column信息会分别对应到heatmap的columns和rows
vmax,vmin, 图例中最大值和最小值的显示值，没有该参数时默认不显示
linewidths,热力图矩阵之间的间隔大小
cmap，热力图颜色
ax，绘制图的坐标轴，否则使用当前活动的坐标轴。
annot，annotate的缩写，annot默认为False，当annot为True时，在heatmap中每个方格写入数据。
annot_kws，当annot为True时，可设置各个参数，包括大小，颜色，加粗，斜体字等：
sns.heatmap(x, annot=True, ax=ax2, annot_kws={
    
    'size':9,'weight':'bold', 'color':'blue'}) 
fmt，格式设置，决定annot注释的数字格式，小数点后几位等；
cbar : 是否画一个颜色条
cbar_kws : 颜色条的参数，关键字同 fig.colorbar，可以参考：matplotlib自定义colorbar颜色条-以及matplotlib中的内置色条。

mask，遮罩

1. First use sns.set(font_scale) to modify the font scale:

sns.set(font_scale=1.5)

2. Then use plt.rc to uniformly modify the font of the whole picture:

plt.rc('font',family='Times New Roman',size=12)

2. Color parameter -cmap

The parameters of cmap are as follows:

Accent, accent_r, blues_r, brbg, bug_r, bugn_r, bupu_r, cmrmap, cmrmap_r, DARK2_r, gnbu(绿到, Greys, Green, Green, Green, Greys, Greys, Greys, Greys, Greys, Grey色到Description), OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Pur place_r , RdBu , RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Wistia(interpretation).黄), Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd(红橙黄), YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm(copper), coolwarm_r, copper(copper), copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r,gist_gray, gist_gray_r, gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r（红黄）, hsv, hsv_r, icefire, icefire_r, inferno, inferno_r, jet, jet_r, magma, magma_r, mako, mako_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, rocket, rocket_r, seismic, seismic_r, spring, spring_r, summer (黄到绿), summer_r (绿到黄), tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, twilight, twilight_r, twilight_shifted, twilight_shifted_r, viridis, viridis_r,vlag, vlag_r, winter, winter_rgist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r（红黄）, hsv, hsv_r, icefire, icefire_r, inferno, inferno_r, jet, jet_r, magma, magma_r, mako, mako_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, rocket, rocket_r, seismic, seismic_r, spring, spring_r, summer (黄到绿), summer_r (绿到黄), tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, twilight, twilight_r, twilight_shifted, twilight_shifted_r, viridis, viridis_r,vlag, vlag_r, winter, winter_rgist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r（红黄）, hsv, hsv_r, icefire, icefire_r, inferno, inferno_r, jet, jet_r, magma, magma_r, mako, mako_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, rocket, rocket_r, seismic, seismic_r, spring, spring_r, summer (黄到绿), summer_r (绿到黄), tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, twilight, twilight_r, twilight_shifted, twilight_shifted_r, viridis, viridis_r,vlag, vlag_r, winter, winter_rrainbow_r, rocket, rocket_r, seismic, seismic_r, spring, spring_r, summer (黄到绿), summer_r (绿到黄), tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, twilight, twilight_r, twilight_shifted, twilight_shifted_r, viridis, viridis_r,vlag, vlag_r, winter, winter_rrainbow_r, rocket, rocket_r, seismic, seismic_r, spring, spring_r, summer (黄到绿), summer_r (绿到黄), tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, twilight, twilight_r, twilight_shifted, twilight_shifted_r, viridis, viridis_r,vlag, vlag_r, winter, winter_r

The demonstration is as follows:
cmap="hot": yellow to red, the larger the number, the lighter the color

cmap="OrRd": deep red to light red, similar to "Oranges".

cmap="greys": gray

cmap="gist_rainbow": rainbow color

Center the colormap at a specific value (reference link):

>>> ax = sns.heatmap(flights, center=flights.loc["January", 1955])

Draw a portion of a matrix using a mask

>>> corr = np.corrcoef(np.random.randn(10, 200))

>>> mask = np.zeros_like(corr)

>>> mask[np.triu_indices_from(mask)] = True

>>> with sns.axes_style("white"):

... ax = sns.heatmap(corr, mask=mask, vmax=.3, square=True)

np.zeros_like() returns an array of zeros with the same shape and type as the given array;

np.triu_indices_from(mask) Returns the indices of the triangles on the array.

The following are some good-looking pictures of color matching found on the Internet:

# cmap用cubehelix map颜色

cmap = sns.cubehelix_palette(start = 1.5, rot = 3, gamma=0.8, as_cmap = True)

sns.heatmap(pt, linewidths = 0.05, ax = ax1, vmax=900, vmin=0, cmap=cmap)

# cmap用matplotlib colormap

sns.heatmap(pt, linewidths = 0.05, ax = ax2, vmax=900, vmin=0, cmap='rainbow')

#center的用法(颜色)

f, (ax1,ax2) = plt.subplots(figsize = (6, 4),nrows=2)

cmap = sns.cubehelix_palette(start = 1.5, rot = 3, gamma=0.8, as_cmap = True)

sns.heatmap(pt, linewidths = 0.05, ax = ax1, cmap=cmap, center=None )

#设置x轴图例为空值ax1.set_ylabel('kind')

# 当center设置小于数据的均值时，生成的图片颜色要向0值代表的颜色一段偏移

sns.heatmap(pt, linewidths = 0.05, ax = ax2, cmap=cmap, center=200)  

#robust的用法(颜色)

f, (ax1,ax2) = plt.subplots(figsize = (6,4),nrows=2)

cmap = sns.cubehelix_palette(start = 1.5, rot = 3, gamma=0.8, as_cmap = True)

sns.heatmap(pt, linewidths = 0.05, ax = ax1, cmap=cmap, center=None, robust=False )

sns.heatmap(pt, linewidths = 0.05, ax = ax2, cmap=cmap, center=None, robust=True ) 

#mask对某些矩阵块的显示进行覆盖

p2 = sns.heatmap(pt, ax=ax2, cmap=cmap, xticklabels=True, mask=(pt<800))  

#mask对pt进行布尔型转化,结果为True的位置用白色覆盖

Realize with mask: highlight some data
sns.heatmap(x, mask=x < 1, ax=ax2, annot=True, annot_kws={“weight”: “bold”}) #cover the area less than 1

3. Personalized settings

Several ways to place the x-axis scale at the top position

# 将x轴刻度放置在top位置的几种方法

# ax.xaxis.set_ticks_position(‘top‘)

ax.xaxis.tick_top()

# ax.tick_params(axis=‘x‘,labelsize=6, colors=‘b‘, labeltop=True, labelbottom=False)

Set the scale parameters of the coordinate axis. When "axis" is not written, the default is to adjust the parameters of the x-axis and y-axis at the same time.

# 设置坐标轴刻度的字体大小

# matplotlib.axes.Axes.tick_params

ax.tick_params(axis=‘y‘,labelsize=8) # y轴

Two methods of text direction on rotation axis scale

# 旋转轴刻度上文字方向的两种方法

ax.set_xticklabels(ax.get_xticklabels(), rotation=-90)

# ax.set_xticklabels(corr.index, rotation=90)

4. Code

'''
深入挖掘
'''
font = {
    
    'family': 'Times New Roman',
        'size': 12,
        }
sns.set(font_scale=1.2)
plt.rc('font',family='Times New Roman')
 
 
fig = plt.figure(figsize = (16, 12))
ax1=fig.add_subplot(2,1,1)
cor = SubShowFeatures01.corr()
mask = np.zeros_like(cor)
for i in range(len(mask)):
    for j in range(i+1, len(mask[0])):
        mask[i][j] = True
 
sns.heatmap(cor,linewidths = 0.05, ax=ax1, mask=mask, annot=True, annot_kws=font, vmax=1.0, vmin=-1.0, cmap='YlGnBu', center=0.5, 
            cbar=True, robust=False)
ax1.set_title('User metric features', fontdict=font)
 
ax2=fig.add_subplot(2,1,2)
SubShowFeatures02 = pd.DataFrame({
    
    "Label":FerFeatures.Label, "PEM":FerFeatures.PEM, "PVAL":FerFeatures.PVAL, "NVAL":FerFeatures.NVAL, 
                            "NEM":FerFeatures.NEM, "DEP":FerFeatures.DEP, "AGR":FerFeatures.AGR, "CONV":FerFeatures.CONV,
                            "Cold":FerFeatures.Cold, "Warm":FerFeatures.Warm, "Pleasure":FerFeatures.Pleasure, 
                            "Arousal":FerFeatures.Arousal, "Dominance":FerFeatures.Dominance                         
                           })
cor = SubShowFeatures02.corr()
mask = np.zeros_like(cor)
for i in range(len(mask)):
    for j in range(i+1, len(mask[0])):
        mask[i][j] = True
sns.heatmap(cor,linewidths = 0.05, ax=ax2, mask=mask, annot=True, annot_kws=font, vmax=1.0, vmin=-1.0, cmap='YlOrRd', center=0)
ax2.set_title('User personality features', fontdict=font)
 
plt.show()