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#84 MAJOR: Refactor start. Moved logic from TileLayout to DataSource
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,123 @@ | ||
| from DNASkittleUtils.Contigs import Contig, write_contigs_to_file, read_contigs | ||
| import os | ||
| from DDVUtils import write_contigs_to_chunks_dir, filter_by_contigs | ||
| from DDV.DDVUtils import multi_line_height, copy_to_sources | ||
| from Layouts import LayoutFrame | ||
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| class DataSource: | ||
| def __init__(self, fasta_name: str, sort_contigs: bool, extract_contigs: bool, layouframe: LayoutFrame): | ||
| self.coords = layouframe # LayoutFrame | ||
| self.contigs = [] # List[Contig] | ||
| self.fasta_name = fasta_name # str | ||
| self.spacing_memory = '' | ||
| self.layout_algorithm = "0" # rastered tile layout | ||
| self.protein_palette = False | ||
| self.using_spectrum = False | ||
| self.skip_small_titles = False | ||
| self.sort_contigs = sort_contigs | ||
| self.extract_contigs = extract_contigs | ||
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| def __getitem__(self, index): | ||
| return self.coords[index] | ||
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| @property | ||
| def base_width(self): | ||
| """Shorthand for the column width value that is used often. This can change | ||
| based on the current self.i_layout.""" | ||
| return self.coords.base_width | ||
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| @property | ||
| def origin(self): | ||
| return self.coords.origin | ||
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| def relative_position(self, progress): # Alias for layout: Optimize? | ||
| return self.coords.relative_position(progress) | ||
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| def position_on_screen(self, progress): # Alias for layout: Optimize? | ||
| return self.coords.position_on_screen(progress) | ||
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| def output_fasta(self, output_folder, fasta, no_webpage, extract_contigs, | ||
| append_fasta_sources=True): | ||
| bare_file = os.path.basename(fasta) | ||
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| # also make single file | ||
| if not no_webpage: | ||
| write_contigs_to_chunks_dir(output_folder, bare_file, self.contigs) | ||
| fasta_destination = os.path.join(output_folder, 'sources', bare_file) | ||
| if self.extract_contigs or self.sort_contigs: # customized_fasta | ||
| length_sum = sum([len(c.seq) for c in self.contigs]) | ||
| fasta_destination = '%s__%ibp.fa' % (os.path.splitext(fasta_destination)[0], length_sum) | ||
| write_contigs_to_file(fasta_destination, self.contigs) # shortened fasta | ||
| else: | ||
| copy_to_sources(output_folder, fasta) | ||
| print("Sequence saved in:", fasta_destination) | ||
| self.clear_sequences() | ||
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| def clear_sequences(self): | ||
| self.spacing_memory = self.contig_struct() | ||
| self.contigs = [] | ||
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| def contig_struct(self): | ||
| if not self.contigs and self.spacing_memory: | ||
| return self.spacing_memory # original value was already cached | ||
| json = [] | ||
| xy_seq_start = 0 | ||
| for index, contig in enumerate(self.contigs): | ||
| if index > 1000: | ||
| break # I don't want to use a slice operator on the for loop because that will copy it | ||
| xy_seq_start += contig.reset_padding + contig.title_padding | ||
| xy_seq_end = xy_seq_start + len(contig.seq) | ||
| json.append( | ||
| {"name": contig.name.replace("'", ""), "xy_seq_start": xy_seq_start, "xy_seq_end": xy_seq_end, | ||
| "title_padding": contig.title_padding, "tail_padding": contig.tail_padding, | ||
| "xy_title_start": xy_seq_start - contig.title_padding, | ||
| "nuc_title_start": contig.nuc_title_start, "nuc_seq_start": contig.nuc_seq_start}) | ||
| xy_seq_start += len(contig.seq) + contig.tail_padding | ||
| return json | ||
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| def read_contigs_and_calc_padding(self, input_file_path, extract_contigs=None): | ||
| self.extract_contigs = extract_contigs | ||
| self.fasta_name = os.path.basename(input_file_path) | ||
| try: | ||
| self.contigs = read_contigs(input_file_path) # TODO:, extract_contigs) | ||
| except UnicodeDecodeError as e: | ||
| print(e) | ||
| print("Important: Non-standard characters detected. Switching to 256 colormap for bytes") | ||
| self.using_spectrum = True | ||
| self.contigs = [Contig(input_file_path, open(input_file_path, 'rb').read())] | ||
| self.contigs = filter_by_contigs(self.contigs, extract_contigs) | ||
| self.protein_palette = is_protein_sequence(self.contigs[0]) | ||
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| # if len(self.levels) >= 5 and len(self.contigs[0].seq) > self.levels[4].chunk_size and multipart_file: | ||
| # self.enable_fat_headers() # first contig is huge and there's more contigs coming | ||
| if len(self.contigs) > 10000: | ||
| print("Over 10,000 scaffolds detected! Titles for entries less than 10,000bp will not be drawn.") | ||
| self.skip_small_titles = True | ||
| # Important! Skipping isn't valid unless they're sorted | ||
| if not self.sort_contigs: | ||
| self.sort_contigs = True | ||
| print("Scaffolds are being sorted by length.") | ||
| # Best to bring the largest contigs to the forefront | ||
| self.contigs.sort(key=lambda fragment: -len(fragment.seq)) | ||
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| class PaddedContig(Contig): | ||
| def __init__(self, name, seq): | ||
| super(PaddedContig, self).__init__(name, seq) | ||
| self.reset_padding = 0 | ||
| self.title_padding = 0 | ||
| self.tail_padding = 0 | ||
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| def is_protein_sequence(contig): | ||
| """Checks if there are any peptide characters in the first 100 of the first contig""" | ||
| peptides = {'D', 'E', 'F', 'H', 'I', 'K', 'L', 'M', 'P', 'Q', 'R', 'S', 'V', 'W', 'X', 'Y'} | ||
| matches = set(contig.seq[:100]).intersection(peptides) | ||
| print("Found matches", matches) | ||
| return len(matches) > 0 | ||
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