如何在每次循环迭代时写入文件而不覆盖它们

Question

以下代码是分析FASTA序列（.faa文件）的氨基酸组成

from Bio import SeqIO
from Bio.SeqUtils.ProtParam import ProteinAnalysis
import fastaparser
import pandas as pd
import matplotlib.pyplot as plt
pd.set_option('display.max_columns', None)

filename = input("Please enter the full path of the amino acid sequence file!: ")
pH_input = input("At which pH should the analysis be conducted? ")
flexibility_ynu = input("Do you wish a flexibility analysis?\n   (1) Yes\n   (0) No\n")

if pH_input == "":
    pH= 7.4
elif pH_input != "":
    pH = pH_input

f = open(filename + "_analysis.txt","w+")
for record in SeqIO.parse(filename, 'fasta'):
    X = ProteinAnalysis(str(record.seq))
    print("ANALYSIS OF", record, "\n ----------- \n -----------", file=f)
    #
    pd_count_amino_acids = pd.DataFrame(X.count_amino_acids(), index=[1])
    print("number of amino acids: \n",pd_count_amino_acids , file=f)
    plt_acc = pd_count_amino_acids.plot.bar()
    plt.savefig(filename + "_count_amino_acids_plot.pdf")
    #
    pd_get_amino_acids_percent = pd.DataFrame(X.get_amino_acids_percent(), index=[1])
    print("\n percentage of amino acids: \n", pd_get_amino_acids_percent, file=f)
    plt_acp = pd_get_amino_acids_percent.plot.bar()
    plt.savefig(filename + "amino_acids_percent_plot.pdf")
    #
    print("\n molecular weight: {:.2f}".format(X.molecular_weight()), file=f)
    print("\n aromaticity: {:.2f}".format(X.aromaticity()), file=f)
    print("\n instability index: {:.2f}".format(X.instability_index()), file=f)
    if flexibility_ynu == "1":
        print("\n flexibility: ", X.flexibility(), file=f)
    print("\n IEP: ", X.isoelectric_point(), file=f)
    print("therefore its charge at pH = ",pH," is {:.2f}".format(X.charge_at_pH(pH)), file=f)
    print("secondary structure fraction: (Helix, Turn, Sheet): ", X.secondary_structure_fraction(), "\n\n\n", file=f)
f.close()
print("done")

我现在想要为氨基酸的绝对数量和相对数量绘制条形图，但要为每个 FASTA ID 创建一个独特的图。

例如，NC_011544 有 5 个 ID，所以我想生成 10 个唯一图（每个 ID 2 个，一个用于绝对数字，一个用于相对数字）。

有什么办法吗？

NC_011544.faa

>gi|212671454|ref|YP_002308464.1| replicase [Hosta virus X]
MARLREVFSSFTEPNLKTIVQQETYKLAKAELKTIQTYNPYAQTKDAADLLEDLGINTNPHAVTAHTHAA
AKSIENDLYGITSHYLPKTPITFLFMKRGKLQFFKRGPQHNDLFFYTTHEPKDVIRYQSEDQTADMFRVP
TSTGFIGDTLHFLSLKYLHRLFLKNPNLNTLYATMVLPPEAMYRMASIYPEIYQIQYQEDGFLYIPGGHG
GAAYFHTYDTLTWLRVGQFQAKEFTAHLPKVGDKGANHLFIIQRADLKTPKYRTFVPRRKWVTLPNIFLP
STQANHLFIIQRADLKTPKYRTFVPRRKWVTSNIFLPKHTNARKPILKQTMMQLFLYEKSVKEITFRDVF
AKIRQLIQTKDLEQFDPDELVRLANYVMHTSKLLEKDPYELIEGQGKLQDLVNPIKTWVSEKWQNWFGWK
DYTRLIRALKWVDVDLVLRVMNTRSTPTGIQTSELLPDEAGPPKSKKKRGGKKIPSPEPSRNCRSKSKRT
RGNRAQREKEPHRRKLRWQKENFQRVTVQVHQAPKGDPSPLARFSQSLKELPRRSQPRRLSKFQDFLMSS
TQTRFQIPSSLNRRAGHWRPKQQGTPPTTQEAGTEGPPTTQPGKPTASSPRAAPQPTANAETMEKGSQAS
SATTRGRDPVTDRTREQAPTNLTPEEEALPWKHWLKQLKAVGFKGNETQMDGDGTSISPIEQIKSCPGKP
KSVSKEILETLRSGHAPNFWKPDASRARAYTSDIKNRRTGAAVHMAPQAWKETMDFIAENAERTLHILRH
PWRRRFREEQMSSRDAHKFHFLFDETLVVCPTNELRRDWIDKLPLSEPGSVLTFERALMNPAKGTVIFDD
YTKLPAGFIEAYSICQPNVELVILTGDAKQASHHESNDNAMIAGLDPAAFEFSKFCRYYLNATHRNPRNL
ANALGIYSEKPGNLKVTFTNHLLPEMHILVPSLLKKATLEELGHKCSTYAGCQGVTLSKVQIYLDSNTTL
CSNEVLYTALSRAVEQINFVNSGPFNGPFWAKLEATPYLKTFLRLTREEKINEITPEEPKPKEPEPPKTH
FPVETSAHLYSSITEEMPEKHAREIYNKTHGHTNCVQTDEPLVQMFAHQQAKDEALFWETIEARLRITTS
EANVQELNEKRDIGDLLFHAYHKAMGLPKDPIPFENDLWETCAQEVQQTYLSKPINLIKNGEKRQGPDFD
KNAIMLFLKSQWVKKMEKLGAPTIKPGQTIASFHQITVMLYGTMARYMRRIRDRFCPKHILINCEKTPTQ
ISDFVKAQWDFSDFAYANDFTAFDQSQDGAMLQFEIIKAKFHNIPEDIILGYMDIKTNAKIFLGTLAIMR
LTGEGPTFDANTECNIAYTHLRFNVPENVAQVYAGDDSALSKVCPEKDSFKQFADRLTLKSKPQVFPQTQ
GAWAEFCGLLITPRGIIKDPVKLHASWVLATKLGTLQQIKCVNSYGEDLKLSYDLGDHLQELLSESQCRT
HQVTVRELVKFAGKVEKHQAEIRSVANGNIRQLPFFY
>gi|212671455|ref|YP_002308465.1| 26 kDa protein [Hosta virus X]
MATFASFLSSTRPDFERTNTPLTKPLVIHAVAGAGKTTLLRDFLRANPLTNAQTLGTPDCPTLDGAYIRP
FSGPVANLVNILDEYTAHRHGSWDVLIADPLQHYERAKLPHYICKRSHRLCPATARLLRKLGLDIHSYRE
DESEISFSDIFSGQLEGTVLPLTPLCKDLLERHSCPFKCPSEFIGEQDDIITVVSEIPLSKHPDKTALYR
ALTRHTRRLNVLAPPPYPTP
>gi|212671456|ref|YP_002308466.1| 13 kDa protein [Hosta virus X]
MSSPHRLTPPPNYTPVLLAVVIGVGLAVVTNQLTRSTLPHVGDNIHSLPHGGNYKDGTKSVIYRGPAPFQ
RSHSTAPPFNAVLLLTFAIWFLSCRTRRAAIGIHVCHTCSQTREQQ
>gi|212671457|ref|YP_002308467.1| 8 kDa protein [Hosta virus X]
MQSFCSHLRSGSFPVVLGALLLAFTCATLVLRLGNNNSNNCLIYVDGARAFLEGNCAGISAEVVAALRPH
SHAG
>gi|212671458|ref|YP_002308468.1| coat protein [Hosta virus X]
MASDAPTPPAAPSPVTFTAPTQEQLTSLALPIISTRLPSPDVLNQISVKWQELGVPTASISSTAIALCMA
CYHSGSSGSTLIPGLAPGTTVNYTSLAAAVKSLATLREFARYFAPIIWNYAIEHKIPPANWAAMGYKENT
KYAAFDTFDSILNPAALQPTGGLIRQPTEEELLAHQANSALHIFDSLRNDFASTDGRVTRGHITSNVNSL
NYLPAPEGSS

Answer 1

• 代码已经为每条记录创建了一个图，但是，所有内容都使用相同的文件名，因此每个新图和analysis.txt 都会覆盖之前的图。
• 从record 中提取id 为record_id，并使用它为每个循环创建唯一的文件名。
• 以下代码现在将为每个id 生成一个percent_plot.pdf、count_plot.pdf 和一个analysis.txt
• 使用with open，会自动关闭文件f
• .T 用于在绘图时转置数据框，将氨基酸名称放在轴上，从而使绘图更易于阅读。

import pandas
import matplotlib.pyplot as plt
from Bio import SeqIO
from Bio.SeqUtils.ProtParam import ProteinAnalysis

# set pandas display option
pd.set_option('display.max_columns', None)

# input selections were removed for testing
filename = 'NC_011544.faa'
flexibility_ynu =  '1'
pH = 7.4

for record in SeqIO.parse(filename, 'fasta'):
    # get each record id to be used for unique file names
    record_id = record.id.split('|')[1]
    print(record)
    # open the file and use the record id as part of the name, so there will be a unique file for each id
    with open(f"{filename}_{record_id}_analysis.txt","w+") as f:

        X = ProteinAnalysis(str(record.seq))
        print("ANALYSIS OF", record, "\n ----------- \n -----------", file=f)
        #
        pd_count_amino_acids = pd.DataFrame(X.count_amino_acids(), index=[1])
        display(pd_count_amino_acids)  # display is for jupyter notebook, otherwise use print
        print("number of amino acids: \n",pd_count_amino_acids , file=f)
        plt_acc = pd_count_amino_acids.T.plot.bar(legend=False, figsize=(7, 5))
        plt.title(f'Number of Amino Acids for {record_id} in {filename}')
        plt.xticks(rotation=0)
        # add the record id as part of the file name
        plt.savefig(f'{filename}_{record_id}_count_amino_acids_plot.pdf')
        plt.show()
        #
        pd_get_amino_acids_percent = pd.DataFrame(X.get_amino_acids_percent(), index=[1])
        display(pd_get_amino_acids_percent.round(2))  # display is for jupyter notebook, otherwise use print
        print("\n percentage of amino acids: \n", pd_get_amino_acids_percent, file=f)
        plt_acp = pd_get_amino_acids_percent.T.plot.bar(legend=False, figsize=(7, 5))
        plt.title(f'Percentage of Amino Acids for {record_id} in {filename}')
        plt.xticks(rotation=0)
        # add the record id as part of the file name
        plt.savefig(f'{filename}_{record_id}_amino_acids_percent_plot.pdf')
        plt.show()
        #
        print("\n molecular weight: {:.2f}".format(X.molecular_weight()), file=f)
        print("\n aromaticity: {:.2f}".format(X.aromaticity()), file=f)
        print("\n instability index: {:.2f}".format(X.instability_index()), file=f)

        if flexibility_ynu == "1":
            print("\n flexibility: ", X.flexibility(), file=f)

        print("\n IEP: ", X.isoelectric_point(), file=f)
        print("therefore its charge at pH = ",pH," is {:.2f}".format(X.charge_at_pH(pH)), file=f)
        print("secondary structure fraction: (Helix, Turn, Sheet): ", X.secondary_structure_fraction(), "\n\n\n", file=f)
        print('\n')

第一个 ID

第二个 ID