我想生产在Python中使用 matplotlib/pyplot
同时将模块依赖性保持在最低限度。
有没有比以下更简单的事情:
import matplotlib.pyplot as plt
def color_gradient ( val, beg_rgb, end_rgb, val_min = 0, val_max = 1):
val_scale = (1.0 * val - val_min) / (val_max - val_min)
return ( beg_rgb[0] + val_scale * (end_rgb[0] - beg_rgb[0]),
beg_rgb[1] + val_scale * (end_rgb[1] - beg_rgb[1]),
beg_rgb[2] + val_scale * (end_rgb[2] - beg_rgb[2]))
# -----------------------------------------------
x_lbls = [ "09:00", "09:15", "10:10"]
y_vals = [ 7, 9, 5]
plt_idx = np.arange( len( x_lbls))
bar_wd = 0.35
grad_beg, grad_end = ( 0.5, 0.5, 0.5), (1, 1, 0)
col_list = [ color_gradient( val,
grad_beg,
grad_end,
min( y_vals),
max( y_vals)) for val in y_vals]
plt.bar( plt_idx, y_vals, color = col_list)
plt.xticks( plt_idx + bar_wd, x_lbls)
plt.show()
这仍然缺少图例颜色条
我在 R 中的解决方案ggplot将会:
library(ggplot2)
df = data.frame( time = 1:10, vals = abs(rnorm( n = 10)))
ggplot( df, aes( x = time, y = vals, fill = vals)) +
geom_bar(stat = "identity") +
scale_fill_gradient(low="#888888",high="#FFFF00")
and produces the desired output: