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1 | 1 | .. This file is part of TimeSide |
2 | 2 | @author: Thomas Fillon |
3 | 3 |
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4 | | -======================== |
5 | | -Data management examples |
6 | | -======================== |
| 4 | +=============== |
| 5 | +Data management |
| 6 | +=============== |
7 | 7 |
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8 | 8 | TimeSide offers various ways to access to audio data or metadata. `AnalyzerResult` is the python data structure where TimeSide embeds all the data resulting from a given analyzer processors after a run. It is thus the base object to access the analysis results and all the corresponding metadata. Bellow are some examples of use of the AnalyzerResult object and some of its methods. |
9 | 9 |
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10 | 10 | Usage : AnalyzerResult(data_mode=None, time_mode=None) |
11 | 11 |
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12 | 12 | Four different *time_mode* can be specified : |
13 | 13 |
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14 | | -- 'framewise' : Data are returned on a frame basis (i.e. with specified blocksize, stepsize and framerate) |
15 | | -- 'global' : A global data value is return for the entire audio item |
16 | | -- 'segment' : Data are returned on a segmnet basis (i.e. with specified start time and duration) |
17 | | -- 'event' : Data are returned on a segment basis (i.e. with specified start time) |
| 14 | +- 'framewise' : data are returned on a frame basis (i.e. with specified blocksize, stepsize and framerate) |
| 15 | +- 'global' : a global data value is return for the entire audio item |
| 16 | +- 'segment' : data are returned on a segmnet basis (i.e. with specified start time and duration) |
| 17 | +- 'event' : data are returned on a segment basis (i.e. with specified start time) |
18 | 18 |
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19 | 19 | Two different *data_mode* can be specified : |
20 | 20 |
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21 | | -- 'value' : Data are returned as numpy Array of arbitrary type |
22 | | -- 'label' : Data are returned as label indexes (specified by the label_metadata key) |
| 21 | +- 'value' : data are returned as numpy Array of arbitrary type |
| 22 | +- 'label' : data are returned as label indexes (specified by the label_metadata key) |
23 | 23 |
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24 | 24 | Default values are *time_mode = 'framewise'* and *data_mode = 'value'* |
25 | 25 |
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@@ -50,10 +50,10 @@ Specification of time_mode |
50 | 50 | ========================== |
51 | 51 | Four different time_mode can be specified : |
52 | 52 |
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53 | | -- 'framewise' : Data are returned on a frame basis (i.e. with specified blocksize, stepsize and framerate) |
54 | | -- 'global' : A global data value is return for the entire audio item |
55 | | -- 'segment' : Data are returned on a segmnet basis (i.e. with specified start time and duration) |
56 | | -- 'event' : Data are returned on a segment basis (i.e. with specified start time) |
| 53 | +- 'framewise' : data are returned on a frame basis (i.e. with specified blocksize, stepsize and framerate) |
| 54 | +- 'global' : a global data value is return for the entire audio item |
| 55 | +- 'segment' : data are returned on a segmnet basis (i.e. with specified start time and duration) |
| 56 | +- 'event' : data are returned on a segment basis (i.e. with specified start time) |
57 | 57 |
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58 | 58 |
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59 | 59 | Framewise |
@@ -100,8 +100,8 @@ Specification of data_mode |
100 | 100 | ========================== |
101 | 101 | Two different data_mode can be specified : |
102 | 102 |
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103 | | -- 'value' : Data are returned as numpy Array of arbitrary type |
104 | | -- 'label' : Data are returned as label indexes (specified by the label_metadata key) |
| 103 | +- 'value' : data are returned as numpy Array of arbitrary type |
| 104 | +- 'label' : data are returned as label indexes (specified by the label_metadata key) |
105 | 105 |
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106 | 106 | Value |
107 | 107 | ----- |
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