Bio.phenotype package
Submodules
- Bio.phenotype.phen_micro module
PlateRecord
PlateRecord.__init__()
PlateRecord.__getitem__()
PlateRecord.__setitem__()
PlateRecord.__delitem__()
PlateRecord.__iter__()
PlateRecord.__contains__()
PlateRecord.__len__()
PlateRecord.__eq__()
PlateRecord.__add__()
PlateRecord.__sub__()
PlateRecord.get_row()
PlateRecord.get_column()
PlateRecord.subtract_control()
PlateRecord.__repr__()
PlateRecord.__str__()
PlateRecord.__hash__
WellRecord
WellRecord.__init__()
WellRecord.__setitem__()
WellRecord.__getitem__()
WellRecord.__iter__()
WellRecord.__eq__()
WellRecord.__add__()
WellRecord.__sub__()
WellRecord.__len__()
WellRecord.__repr__()
WellRecord.__str__()
WellRecord.get_raw()
WellRecord.get_times()
WellRecord.get_signals()
WellRecord.fit()
WellRecord.__hash__
JsonIterator()
CsvIterator()
JsonWriter
- Bio.phenotype.pm_fitting module
Module contents
phenotype data input/output.
Input
The main function is Bio.phenotype.parse(…) which takes an input file, and format string. This returns an iterator giving PlateRecord objects:
>>> from Bio import phenotype
>>> for record in phenotype.parse("phenotype/Plates.csv", "pm-csv"):
... print("%s %i" % (record.id, len(record)))
...
PM01 96
PM09 96
Note that the parse() function will invoke the relevant parser for the format with its default settings. You may want more control, in which case you need to create a format specific sequence iterator directly.
Input - Single Records
If you expect your file to contain one-and-only-one record, then we provide the following ‘helper’ function which will return a single PlateRecord, or raise an exception if there are no records or more than one record:
>>> from Bio import phenotype
>>> record = phenotype.read("phenotype/Plate.json", "pm-json")
>>> print("%s %i" % (record.id, len(record)))
PM01 96
This style is useful when you expect a single record only (and would consider multiple records an error). For example, when dealing with PM JSON files saved by the opm library.
However, if you just want the first record from a file containing multiple record, use the next() function on the iterator:
>>> from Bio import phenotype
>>> record = next(phenotype.parse("phenotype/Plates.csv", "pm-csv"))
>>> print("%s %i" % (record.id, len(record)))
PM01 96
The above code will work as long as the file contains at least one record. Note that if there is more than one record, the remaining records will be silently ignored.
Output
Use the function Bio.phenotype.write(…), which takes a complete set of PlateRecord objects (either as a list, or an iterator), an output file handle (or in recent versions of Biopython an output filename as a string) and of course the file format:
from Bio import phenotype
records = ...
phenotype.write(records, "example.json", "pm-json")
Or, using a handle:
from Bio import phenotype
records = ...
with open("example.json", "w") as handle:
phenotype.write(records, handle, "pm-json")
You are expected to call this function once (with all your records) and if using a handle, make sure you close it to flush the data to the hard disk.
File Formats
When specifying the file format, use lowercase strings.
pm-json - Phenotype Microarray plates in JSON format.
- pm-csv - Phenotype Microarray plates in CSV format, which is the
machine vendor format
Note that while Bio.phenotype can read the above file formats, it can only write in JSON format.
- Bio.phenotype.write(plates, handle, format)
Write complete set of PlateRecords to a file.
plates - A list (or iterator) of PlateRecord objects.
- handle - File handle object to write to, or filename as string
(note older versions of Biopython only took a handle).
format - lower case string describing the file format to write.
You should close the handle after calling this function.
Returns the number of records written (as an integer).
- Bio.phenotype.parse(handle, format)
Turn a phenotype file into an iterator returning PlateRecords.
- handle - handle to the file, or the filename as a string
(note older versions of Biopython only took a handle).
format - lower case string describing the file format.
Typical usage, opening a file to read in, and looping over the record(s):
>>> from Bio import phenotype >>> filename = "phenotype/Plates.csv" >>> for record in phenotype.parse(filename, "pm-csv"): ... print("ID %s" % record.id) ... print("Number of wells %i" % len(record)) ... ID PM01 Number of wells 96 ID PM09 Number of wells 96
Use the Bio.phenotype.read(…) function when you expect a single record only.
- Bio.phenotype.read(handle, format)
Turn a phenotype file into a single PlateRecord.
- handle - handle to the file, or the filename as a string
(note older versions of Biopython only took a handle).
format - string describing the file format.
This function is for use parsing phenotype files containing exactly one record. For example, reading a PM JSON file:
>>> from Bio import phenotype >>> record = phenotype.read("phenotype/Plate.json", "pm-json") >>> print("ID %s" % record.id) ID PM01 >>> print("Number of wells %i" % len(record)) Number of wells 96
If the handle contains no records, or more than one record, an exception is raised. For example:
from Bio import phenotype record = phenotype.read("plates.csv", "pm-csv") Traceback (most recent call last): ... ValueError: More than one record found in handle
If however you want the first record from a file containing multiple records this function would raise an exception (as shown in the example above). Instead use:
>>> from Bio import phenotype >>> record = next(phenotype.parse("phenotype/Plates.csv", "pm-csv")) >>> print("First record's ID %s" % record.id) First record's ID PM01
Use the Bio.phenotype.parse(handle, format) function if you want to read multiple records from the handle.