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diff --git a/doc/nerv_io.md b/doc/nerv_io.md index d452d5d..a417aa8 100644 --- a/doc/nerv_io.md +++ b/doc/nerv_io.md @@ -2,25 +2,108 @@ Part of the [Nerv](../README.md) toolkit. ##Description## -There are four classes in to deal with chunk data, which are __nerv.ChunkFile__, __nerv.ChunkFileHandle__, __nerv.ChunkInfo__, __nerv.ChunkData__. Below is the underlying C structs. +The main class that the user uses to store and read parameter object to and from files is __nerv.ChunkFile__. +In the file, a parameter object will be saved using a standard format. First is the length(in byte) of this object, then a table which includes some meta information of the object, and a data area. Below is an example text file. +``` +[0000000000202] +{type="nerv.ExampleP",info={message="just-a-try"},id="exampleP1"} +3 3 +5.000000 5.000000 5.000000 +5.000000 5.000000 5.000000 +5.000000 5.000000 5.000000 +1 3 +4.000000 4.000000 4.000000 +[0000000000202] +{type="nerv.ExampleP",info={message="just-a-try"},id="exampleP2"} +3 3 +4.000000 4.000000 4.000000 +4.000000 4.000000 4.000000 +4.000000 4.000000 4.000000 +1 3 +3.000000 3.000000 3.000000 +``` + +##Methods## +* __ChunkFile ChunkFile(string fn, string mode)__ +`mode` can be `r` or `w`, for reading or writing a file. The returned __ChunkFile__ will be ready to write or read objects which follows the __nerv.Param__ interface(using `write_chunk` and `read_chunk`). +* __void ChunkFile.write_chunk(ChunkFile self, Param p)__ +Write `p` into the file. `p:write` will be called. +* __Param ChunkFile.read_chunk(ChunkFile self, string id, table global_conf)__ +Read the __Param__ object by id `id` from the file `self`. It will be constructed using `__init(id, global_conf)`. `p:read` will be called. + +##Examples## +* An example showing how to use __ChunkFile__ to store and read parameter objects. +``` +require 'io' +do + local mt, mpt = nerv.class('nerv.ExampleP', 'nerv.Param') + function nerv.ExampleP:__init(id, global_conf) + self.id = id + self.global_conf = global_conf + self.matrix = nerv.MMatrixFloat(3, 3) + for i = 0, 2, 1 do + for j = 0, 2, 1 do + self.matrix[i][j] = 3 + end + end + self.bias = nerv.MMatrixFloat(1, 3) + for i = 0, 2, 1 do + self.bias[i] = 2; + end + self:set_info({message = 'just-a-try'}) + end + function nerv.ExampleP:addOne() + for i = 0, 2, 1 do + for j = 0, 2, 1 do + self.matrix[i][j] = self.matrix[i][j] + 1 + end + end + for i = 0, 2, 1 do + self.bias[i] = self.bias[i] + 1 + end + end + function nerv.ExampleP:read(pcdata) + self.matrix = nerv.MMatrixFloat.load(pcdata) + self.bias = nerv.MMatrixFloat.load(pcdata) + end + function nerv.ExampleP:write(pfhandle) + self.matrix:save(pfhandle) + self.bias:save(pfhandle) + end +end +global_conf = {} +do + local f = nerv.ChunkFile('../tmp', 'w') + local exampleP1 = nerv.ExampleP('exampleP1', global_conf) + local exampleP2 = nerv.ExampleP('exampleP2', global_conf) + exampleP1:addOne() + exampleP1:addOne() + exampleP2:addOne() + + f:write_chunk(exampleP1) + f:write_chunk(exampleP2) +end +do + local f = nerv.ChunkFile('../tmp', 'r') + local exampleP1 = f:read_chunk('exampleP1', global_conf) + local exampleP2 = f:read_chunk('exampleP2', global_conf) + print(exampleP1.matrix) + print(exampleP2.matrix) +end +``` + +##Developer Notes## +* There are four classes in to deal with chunk data, which are __nerv.ChunkFile__, __nerv.ChunkFileHandle__, __nerv.ChunkInfo__, __nerv.ChunkData__. Below is the underlying C structs. ``` typedef struct ChunkFileHandle { FILE *fp; } ChunkFileHandle; - typedef struct ChunkInfo { off_t offset, length; } ChunkInfo; - typedef struct ChunkData { FILE *fp; char *data; } ChunkData; ``` - -##Methods## -* __ChunkFile ChunkFile.\_\_init(string mode, string fn)__ -`mode` can be `r` or `w`, for reading or writing a file. - -##Developer Notes## -In __Nerv.io__, a returned(by `ChunkFile.__init`) __nerv.ChunkFile__ will have a member `handle`, which is a __nerv.ChunkFileHandle__.
\ No newline at end of file +* In __Nerv.io__, a returned(by `ChunkFile.__init`) __nerv.ChunkFile__ will have a member `handle`, which is a __nerv.ChunkFileHandle__.
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