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ClickRepair 3.9 & ClickRepairRT 1.3 User`s Manual

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  • 15 ClickRepair has one other dialog related to file-length issues, shown here
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  • ClickRepair is described as 'mature, well-tested, application for declicking and decrackling audio in uncompressed audio files
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Download Audio Restoration ClickRepair V3.9.8 …

  • ClickRepair is a program for locating and repairing damage due to scratches, dust specks, etc
  • It is equally useable by Apple Mac or Windows users
  • It is not a plug-in, so it’s use does not require an editor which supports plug-ins…
  • ClickRepair is an application that can assist you in restoring the sound archived from old records (vinyl or

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ClickRepair Test Steve Hoffman Music Forums

  • It is a 24/96 flac clip of Radiohead's Exit Music (For a Film) where I alternated between ClickRepair on and off every ten seconds
  • I'd appreciate any thoughts regarding noticeable artifacts introduced in the ClickRepair sections as well as the general sound quality of the transfer
  • Using ClickRepair v3.5.3 with the following settings:

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Clickrepair Settings Vinyl To Digits.com

  • (see the manual): ”DeCrackle” – for 78 rpm records
  • Not designed for EP/LP so I haven’t tried
  • ”DeClick” – the sensitivity for ClickRepair to find a ”click”
  • I chose a low value for instance 14 for a good record, and a higher value for a …

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Do You Lose Fidelity Using Click Repair

  • In my experience with 24/96 in ClickRepair, a couple times it will change clicks such that a loud click is added - hard to explain, but just comparing waveforms, just today I did a side of vinyl set pretty low, at 12, and afterwards there were 2 large spikes that hadn't been there before

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  • There is a RT (realtime) version of Click Repair which is designed to be stuck inline
  • That, the talk of wavelets and then the 'negative' where only the pops are output are all features of ClickRepair which is why I strongly suspect the SugarCube guys are licensing it from Brian Davies
  • Also, the cost per license for an individual is $40.

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  • Click Repair is my go to choice for declick
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  • For acoustic music I think auto declick is OK.

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  • For example many of the jazz recordings from the 1950s and 1960s have boosted upper mids / lower treble, making them sound edgy or crisp
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Top

Numeric types consist of two-, four-, and eight-byte integers, four- and eight-byte floating-point numbers, and selectable-precision decimals. Table 8-2 lists the available types.

Table 8-2. Numeric Types

NameStorage SizeDescriptionRange
smallint2 bytessmall-range integer-32768 to +32767
integer4 bytesusual choice for integer-2147483648 to +2147483647
bigint8 byteslarge-range integer-9223372036854775808 to 9223372036854775807
decimalvariableuser-specified precision, exactno limit
numericvariableuser-specified precision, exactno limit
real4 bytesvariable-precision, inexact6 decimal digits precision
double precision8 bytesvariable-precision, inexact15 decimal digits precision
serial4 bytesautoincrementing integer1 to 2147483647
bigserial8 byteslarge autoincrementing integer1 to 9223372036854775807

The syntax of constants for the numeric types is described in Section 4.1.2. The numeric types have a full set of corresponding arithmetic operators and functions. Refer to Chapter 9 for more information. The following sections describe the types in detail.

8.1.1. Integer Types

The types smallint, integer, and bigint store whole numbers, that is, numbers without fractional components, of various ranges. Attempts to store values outside of the allowed range will result in an error.

The type integer is the usual choice, as it offers the best balance between range, storage size, and performance. The smallint type is generally only used if disk space is at a premium. The bigint type should only be used if the integer range is not sufficient, because the latter is definitely faster.

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The bigint type might not function correctly on all platforms, since it relies on compiler support for eight-byte integers. On a machine without such support, bigint acts the same as integer (but still takes up eight bytes of storage). However, we are not aware of any reasonable platform where this is actually the case.

SQL only specifies the integer types integer (or int), smallint, and bigint. The type names int2, int4, and int8 are extensions, which are shared with various other SQL database systems.

8.1.2. Arbitrary Precision Numbers

The type numeric can store numbers with up to 1000 digits of precision and perform calculations exactly. It is especially recommended for storing monetary amounts and other quantities where exactness is required. However, arithmetic on numeric values is very slow compared to the integer types, or to the floating-point types described in the next section.

In what follows we use these terms: The scale of a numeric is the count of decimal digits in the fractional part, to the right of the decimal point. The precision of a numeric is the total count of significant digits in the whole number, that is, the number of digits to both sides of the decimal point. So the number 23.5141 has a precision of 6 and a scale of 4. Integers can be considered to have a scale of zero.

Both the maximum precision and the maximum scale of a numeric column can be configured. To declare a column of type numeric use the syntax:

The precision must be positive, the scale zero or positive. Alternatively:

selects a scale of 0. Specifying:

without any precision or scale creates a column in which numeric values of any precision and scale can be stored, up to the implementation limit on precision. A column of this kind will not coerce input values to any particular scale, whereas numeric columns with a declared scale will coerce input values to that scale. (The SQL standard requires a default scale of 0, i.e., coercion to integer precision. We find this a bit useless. If you're concerned about portability, always specify the precision and scale explicitly.)

If the scale of a value to be stored is greater than the declared scale of the column, the system will round the value to the specified number of fractional digits. Then, if the number of digits to the left of the decimal point exceeds the declared precision minus the declared scale, an error is raised.

Numeric values are physically stored without any extra leading or trailing zeroes. Thus, the declared precision and scale of a column are maximums, not fixed allocations. (In this sense the numeric type is more akin to varchar(n) than to char(n).) The actual storage requirement is two bytes for each group of four decimal digits, plus five to eight bytes overhead.

In addition to ordinary numeric values, the numeric type allows the special value NaN, meaning 'not-a-number'. Any operation on NaN yields another NaN. When writing this value as a constant in a SQL command, you must put quotes around it, for example UPDATE table SET x = 'NaN'. On input, the string NaN is recognized in a case-insensitive manner.

Note: In most implementations of the 'not-a-number' concept, NaN is not considered equal to any other numeric value (including NaN). In order to allow numeric values to be sorted and used in tree-based indexes, PostgreSQL treats NaN values as equal, and greater than all non-NaN values.

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The types decimal and numeric are equivalent. Both types are part of the SQL standard.

Serial

8.1.3. Floating-Point Types

The data types real and double precision are inexact, variable-precision numeric types. In practice, these types are usually implementations of IEEE Standard 754 for Binary Floating-Point Arithmetic (single and double precision, respectively), to the extent that the underlying processor, operating system, and compiler support it.

Inexact means that some values cannot be converted exactly to the internal format and are stored as approximations, so that storing and printing back out a value might show slight discrepancies. Managing these errors and how they propagate through calculations is the subject of an entire branch of mathematics and computer science and will not be discussed further here, except for the following points:

  • If you require exact storage and calculations (such as for monetary amounts), use the numeric type instead.

  • If you want to do complicated calculations with these types for anything important, especially if you rely on certain behavior in boundary cases (infinity, underflow), you should evaluate the implementation carefully.

  • Comparing two floating-point values for equality might or might not work as expected.

On most platforms, the real type has a range of at least 1E-37 to 1E+37 with a precision of at least 6 decimal digits. The double precision type typically has a range of around 1E-307 to 1E+308 with a precision of at least 15 digits. Values that are too large or too small will cause an error. Rounding might take place if the precision of an input number is too high. Numbers too close to zero that are not representable as distinct from zero will cause an underflow error.

In addition to ordinary numeric values, the floating-point types have several special values:

Infinity
-Infinity
NaN

These represent the IEEE 754 special values 'infinity', 'negative infinity', and

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'not-a-number'

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, respectively. (On a machine whose floating-point arithmetic does not follow IEEE 754, these values will probably not work as expected.) When writing these values as constants in a SQL command, you must put quotes around them, for example UPDATE table SET x = 'Infinity'. On input, these strings are recognized in a case-insensitive manner.

Note: IEEE754 specifies that NaN should not compare equal to any other floating-point value (including NaN). In order to allow floating-point values to be sorted and used in tree-based indexes, PostgreSQL treats NaN values as equal, and greater than all non-NaN values.

PostgreSQL also supports the SQL-standard notations float and float(p) for specifying inexact numeric types. Here, p specifies the minimum acceptable precision in binary digits. PostgreSQL accepts float(1) to float(24) as selecting the real type, while float(25) to float(53) select double precision. Values of p outside the allowed range draw an error. float with no precision specified is taken to mean double precision.

Note: Prior to PostgreSQL 7.4, the precision in float(p) was taken to mean so many decimal digits. This has been corrected to match the SQL standard, which specifies that the precision is measured in binary digits. The assumption that real and double precision have exactly 24 and 53 bits in the mantissa respectively is correct for IEEE-standard floating point implementations. On non-IEEE platforms it might be off a little, but for simplicity the same ranges of p are used on all platforms.

8.1.4. Serial Types

The data types serial and bigserial are not true types, but merely a notational convenience for setting up unique identifier columns (similar to the AUTO_INCREMENT property supported by some other databases). In the current implementation, specifying:

is equivalent to specifying:

Thus, we have created an integer column and arranged for its default values to be assigned from a sequence generator. A NOT NULL constraint is applied to ensure that a null value cannot be explicitly inserted, either. (In most cases you would also want to attach a UNIQUE or PRIMARY KEY constraint to prevent duplicate values from being inserted by accident, but this is not automatic.) Lastly, the sequence is marked as 'owned by' the column, so that it will be dropped if the column or table is dropped.

Note: Prior to PostgreSQL 7.3, serial implied UNIQUE. This is no longer automatic. If you wish a serial column to be in a unique constraint or a primary key, it must now be specified, same as with any other data type.

To insert the next value of the sequence into the serial column, specify that the serial column should be assigned its default value. This can be done either by excluding the column from the list of columns in the INSERT statement, or through the use of the DEFAULT key word.

The type names serial and serial4 are equivalent: both create integer columns. The type names bigserial and serial8 work just the same way, except that they create a bigint column. bigserial should be used if you anticipate the use of more than 231 identifiers over the lifetime of the table.

The sequence created for a serial column is automatically dropped when the owning column is dropped. You can drop the sequence without dropping the column, but this will force removal of the column default expression.

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