我有以下使用基因组数据创建数据框的策略:
from hypothesis.extra.pandas import columns, data_frames, column
import hypothesis.strategies as st
def mysort(tp):
key = [-1, tp[1], tp[2], int(1e10)]
return [x for _, x in sorted(zip(key, tp))]
positions = st.integers(min_value=0, max_value=int(1e7))
strands = st.sampled_from("+ -".split())
chromosomes = st.sampled_from(elements=["chr{}".format(str(e)) for e in list(range(1, 23)) + "X Y M".split()])
genomics_data = data_frames(columns=columns(["Chromosome", "Start", "End", "Strand"], dtype=int),
rows=st.tuples(chromosomes, positions, positions, strands).map(mysort))
Run Code Online (Sandbox Code Playgroud)
我对空数据帧并不真正感兴趣,因为它们是无效的,而且我还想生成一些非常长的 dfs。如何更改为测试用例创建的数据帧的大小?即最小尺寸为 1,平均尺寸为大?
您可以为 data_frames 构造函数提供一个索引参数,其中包含 min_size 和 max_size 选项:
from hypothesis.extra.pandas import data_frames, columns, range_indexes
import hypothesis.strategies as st
def mysort(tp):
key = [-1, tp[1], tp[2], int(1e10)]
return [x for _, x in sorted(zip(key, tp))]
chromosomes = st.sampled_from(["chr{}".format(str(e)) for e in list(range(1, 23)) + "X Y M".split()])
positions = st.integers(min_value=0, max_value=int(1e7))
strands = st.sampled_from("+ -".split())
dfs = data_frames(index=range_indexes(min_size=5), columns=columns("Chromosome Start End Strand".split(), dtype=int), rows=st.tuples(chromosomes, positions, positions, strands).map(mysort))
Run Code Online (Sandbox Code Playgroud)
生成 dfs 如下:
Chromosome Start End Strand
0 chr11 1411202 8025685 +
1 chr18 902289 5026205 -
2 chr12 5343877 9282475 +
3 chr16 2279196 8294893 -
4 chr14 1365623 6192931 -
5 chr12 4602782 9424442 +
6 chr10 136262 1739408 +
7 chr15 521644 4861939 +
Run Code Online (Sandbox Code Playgroud)
| 归档时间: |
|
| 查看次数: |
443 次 |
| 最近记录: |