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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 <h1><span style="color
Step1:  Simulate example data
Step2:  Input data file
Step3:  Population assignments
Step4:  Filter missing data and convert to genotype frequencies
Step5:  Write data to file
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Python Code:
# conda install ipyrad ipcoal -c conda-forge -c bioconda
import ipyrad.analysis as ipa
import toytree
import ipcoal
print('ipyrad', ipa.__version__)
print('toytree', toytree.__version__)
print('ipcoal', ipcoal.__version__)
Explanation: <h1><span style="color:gray">ipyrad-analysis toolkit:</span> construct </h1>
The program construct is a STRUCTURE-like tool that incorporates expectations of isolation by distance. It is available as an R package. This notebook demonstrates how to convert data to the proper format for use in construct using simulated data as an example. For details on running construct see their documentation. 
Required software
End of explanation
# network model
tree = toytree.rtree.unittree(7, treeheight=3e6, seed=123)
tree.draw(ts='o', admixture_edges=(3, 2));
# simulation model with admixture and missing data
model = ipcoal.Model(tree, Ne=1e4, nsamples=4, admixture_edges=(3, 2, 0.5, 0.1))
model.sim_snps(250)
model.write_snps_to_hdf5(name="test-construct", outdir="/tmp", diploid=True)
Explanation: Simulate example data
End of explanation
# the path to your HDF5 formatted snps file
SNPS = "/tmp/test-construct.snps.hdf5"
Explanation: Input data file
End of explanation
IMAP = {
    "r0": ["r0-0", "r0-1"],
    "r1": ["r1-0", "r1-1"],
    "r2": ["r2-0", "r2-1"],
    "r3": ["r3-0", "r3-1"],
    "r4": ["r4-0", "r4-1"],
    "r5": ["r5-0", "r5-1"],
    "r6": ["r6-0", "r6-1"],
}
Explanation: Population assignments
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# apply filtering to the SNPs file
tool = ipa.snps_extracter(data=SNPS, imap=IMAP, minmap={i:2 for i in IMAP})
tool.parse_genos_from_hdf5();
# convert SNP data to genotype frequencies
df = tool.get_population_geno_frequency()
df.head()
Explanation: Filter missing data and convert to genotype frequencies
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# write to a file
df.to_csv("/tmp/freqs.csv")
Explanation: Write data to file
End of explanation
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