x = np.arange(over)
时间: 2024-06-15 14:05:16 浏览: 10
x = np.arange(over)是一个使用NumPy库创建一个数组的代码。其中,np是NumPy库的别名,arange()函数用于创建一个按指定范围和步长递增的数组。
具体来说,x = np.arange(over)会创建一个从0开始,以步长为1递增的数组,直到达到over-1为止。这个数组的元素个数为over。
例如,如果over的值为5,那么x = np.arange(5)将创建一个包含元素[0, 1, 2, 3, 4]的数组。
相关问题
x = np.array([123,172,76,161,314,77,226,330,202,321,260,155,120,163,221,400,45,106,296,125,210,66,131,242,372]) x.sort() w = int(input("请输入等宽分箱的宽度:")) max = x.max() min = x.min() m = int(math.ceil((max - min)/w)) bins = [min+k*w for k in range(0,m+1)] x_cuts = pd.cut(x, bins, right=False) number = pd.value_counts(x_cuts) rows = number.max() width = np.full([m, rows], 0) size = x.size a = 0 for j in range(0, m-1): for i in range(0, number[j]): width[j][i] = x[a] a = a + 1 print(width) Traceback (most recent call last):KeyError: 0
The error "KeyError: 0" is raised because the code is trying to access an index that does not exist in a dictionary or a list.
In this case, it is likely that the error is caused by the line "for i in range(0, number[j]):", where "number" is a dictionary generated by "pd.value_counts(x_cuts)". The loop is trying to access the index "0", which may not exist in the dictionary.
To fix this error, you can modify the loop to iterate over the keys and values of the dictionary, like this:
for bin, count in number.items():
for i in range(count):
width[j][i] = x[a]
a += 1
This will iterate over the keys (i.e., the bins) and values (i.e., the counts) in the dictionary, and then iterate over the range of the count to fill in the corresponding values in the "width" array. The variable "a" is incremented each time to keep track of the index in the sorted array "x".
shp_path = r'C:\Program Files\SPEI\DM.shp' # 确定shp文件地址 proj = ccrs.PlateCarree() # 简写投影 extent = [88, 144, -14, 30.01] # 限定绘图范围 reader = Reader(shp_path) enshicity = cfeat.ShapelyFeature(reader.geometries(), proj, edgecolor='k', facecolor='none') ##黑边无填充 # -------------设置经纬度范围------------- lons = np.arange(92, 141, 0.5) lats = np.arange(-10.5, 28.5, 0.5) lons, lats = np.meshgrid(lons, lats) p = 2 if p == 1: out_fig = ".tif" elif p == 2: out_fig = ".svg" # print (p) # colorn = 'gist_heat_r' # colorn = 'hot_r' colorn = 'bwr' leveln = [-2.5, -1.5, -0.5, 0.5, 1.5, 2.5] leveln1 = [-2, -1, 0, 1, 2] leveln2 = ['显著下降', '不显著下降', '无变化', '不显著上升', '显著上升'] # filen = 'delta.flt' # titlen = "Resistance" titlen = "1970-2015年SPEI空间演变格局" # labeln = "天(day)" # labeln = "摄氏度(℃)" extendn = 'neither' out_filen = 'delta.png' colorbar_label_font = colorbar_label_font_C cm = mpl.cm.get_cmap(colorn, 20) # 分为7级 num:Spectral_r 2:CMRmap_r 1:gist_heat_r cm.set_bad("w") # 设置背景色 cm.set_over("darkslategray") cm.set_under("darkslategray") levels = leveln norm = BoundaryNorm(levels, ncolors=cm.N, clip=True)
这段代码是用来设置地图绘制的一些参数和样式。首先,确定了shp文件的地址,并使用ccrs.PlateCarree()设置了投影方式。然后,限定了绘图范围。接下来,使用Reader读取shp文件的几何信息,并使用cfeat.ShapelyFeature创建了一个ShapelyFeature对象,该对象用于绘制地图的边界线。然后,定义了经纬度范围,并使用np.meshgrid生成经纬度网格。根据变量p的值,确定了输出文件的格式。然后,设置了颜色映射、等级、标题、标签等参数。最后,使用mpl.cm.get_cmap获取颜色映射对象,并进行一些设置。
需要注意的是,这段代码中有一些变量和函数的定义是缺失的,比如colorbar_label_font_C和BoundaryNorm函数,可能需要根据上下文补充或者自行定义。
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