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A flat-file database is a database stored in a file called a flat file. Records follow a uniform format, and there are no structures for indexing or recognizing relationships between records. The file is simple. A flat file can be a plain text file (e.g. csv, or tsv), or a . Relationships can be inferred from the data in the database, but the database format itself does not make those relationships explicit. The term has generally implied a small database, but very large databases can also be flat. Plain text files usually contain one record per line. There are different conventions for depicting data. In comma-separated values and delimiter-separated values files, fields can be separated by delimiters such as comma or tab characters. In other cases, each field may have a fixed length; short values may be padded with space characters. Extra formatting may be needed to avoid delimiter collision. Using delimiters incurs some overhead in locating them every time they are processed (unlike fixed-width formatting), which may have performance implications. However, use of character delimiters (especially commas) is also a crude form of data compression which may assist overall performance by reducing data volumes — especially for data transmission purposes. Use of character delimiters which include a length component (Declarative notation) is comparatively rare but vastly reduces the overhead associated with locating the extent of each field. Examples of flat files include /etc/passwd and /etc/group on Unix-like operating systems. Another example of a flat file is a name-and-address list with the fields Name, Address, and Phone Number. A list of names, addresses, and phone numbers written by hand on a sheet of paper is a flat-file database. This can also be done with any typewriter or word processor. A spreadsheet or text editor program may be used to implement a flat-file database, which may then be printed or used online for improved search capabilities.
[2]Paolo Prandoni, [3]LCAV, EPFL
This notebook shows a simple way to process audio files (in WAV format)
in a block-by-block fashion; this is useful in two cases
1. when you want to process a data stream in real time but you can
accept a small processing delay; in this case a buffered approach
can yield computational gains
2. when you need to process a large file that does not fit entirely
into [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will investigate the effect of phase on the
perceptual quality of a sound. It is often said that the human ear is
commercial-grade audio equipment takes place in the magnitude domain
only.
In [1]:
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import IPython
from scipy.io import wavfile
In [2]:
plt.rcParams["figure.fig