Working with Scilab

Difficulty level: easy
Time need to lean: 15 minutes or less
Key points:
- There are intuitive corresponding data types between most Python (SoS) and Scilab datatypes

Overview

The convertion of datatype from SoS to Scilab is as followings:

Python	condition	Scilab
`None`		`Nan`
`boolean`		`boolean`
`integer`		`constant`
`float`		`constant`
`complex`		`complex`
`str`		`string`
`char`		`string`
Sequence (`list`, `tuple`, ...)	homogenous type, all numeric	`constant`
Sequence (`list`, `tuple`, ...)	homogenous type, all char	`string`
Sequence (`list`, `tuple`, ...)	multiple types	`list`
`numpy.ndarray`		`constant`
`numpy.matrix`		`constant`

Python objects in other datatypes are transferred as string "Unsupported datatype".

The convertion of datatype from Scilab to SoS is as followings:

Scilab	length (n)	Python
`Nan`		`None`
`boolean`	`1`	`boolean`
`integer`	`1`	`integer`
`constant`	`1`	`double`
`string`	`1`	`string`
`complex`	`1`	`complex`
`boolean`	`n > 1`	`list`
`integer`	`n > 1`	`list`
`complex`	`n > 1`	`list`
`constant`	`n > 1`	`list`
`string`	`n > 1`	`list`
`struct`	`n > 0`	`numpy.ndarray`
`matrix`	`n > 0`	`numpy.array`
`cell`	`n > 0`	`numpy.ndarray`

Simple data types

Most simple Python data types can be converted to Scilab types easily.

  null_var  = 

   Nan

  int_var  = 

   123.

  float_var  = 

   3.1415925

  logic_var  = 

  T

  char_var  = 

  "1"23"

  comp_var  = 

   1. + 2.i

Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"

None

123

3.1415925

True

'1"23'

(1+2j)

However, because Python allows integers of arbitrary precision which is not supported by Scilab, large integers would be presented in Scilab as float point numbers, which might not be able to keep the precision of the original number.

For example, if we put a large integer with 18 significant digits to Scilab

/usr/bin/chcon: failed to change context of '/share/apps/scilab-6.1.1/bin/scilab-bin' to ‘unconfined_u:object_r:execmem_exec_t:s0’: Operation not permitted
/usr/bin/chcon: failed to change context of '/share/apps/scilab-6.1.1/bin/scilab-cli-bin' to ‘unconfined_u:object_r:execmem_exec_t:s0’: Operation not permitted

The integer would be considered a double-precision float number and be presented with a D

  large_int  = 

   1.235D+17

This is not a problem with SoS because you would get the same result if you enter this number in Scilab

  ans  =

   1.235D+17

Consequently, if you send large_int back to SoS, the number would be different

123456789123456784

Array and matrix

The one-dimension (vector) data is converted from SoS to Scilab as follows:

Undefined variable: char_arr_var


Undefined variable: list_var


Undefined variable: recursive_var

 logic_arr_var  = 

  T F T

The multi-dimension data is converted from SoS to Scilab as follows:

  num_arr_var  = 

  1  2
  3  4

  mat_var  = 

  1  2
  3  4

The scalar data is converted from Scilab to SoS as follows:

 null_var  = 

   Nan

 num_var  = 

   123.

 logic_var  = 

  T

 char_var  = 

  "1 23"

 comp_var  = 

   1. + 2.i

Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"

None

Unknown variable num_var

True

'1"23'

(1+2j)

The one-dimension (vector) data is converted from R to SoS as follows:

 num_vector_var  = 

   1.   2.   3.

 logic_vector_var  = 

  T F T

 char_vector_var  = 

  "1"  "2"  "3"

 list_var  = 

  (1) = 1
  (2) = 2
  (3) = "3"


 recursive_var  = 

  (1) = 1
  (2) : list:
      (1) = 3
      (2) = "whatever"

Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"

Unknown variable num_vector_var

Unknown variable logic_vector_var

Unknown variable char_vector_var

[1, 2, '3']

{'a': {'b': 123}, 'c': True}

The multi-dimension data is converted from Scilab to SoS as follows:

 mat_var  = 

   1.   2.
   3.   4.

 arr_var  = 

(:,:,1)

   0.   0.
   0.   0.
(:,:,2)

   0.   0.
   0.   0.
(:,:,3)

   0.   0.
   0.   0.

Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"
Failed to evaluate 'Undefined variable: sos_py_repr':
 Invalid return expresion "Undefined variable: sos_py_repr"

[0]: 
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
script_6617773757429726406 in <module>
----> mat_var
      arr_var
      

NameError: name 'mat_var' is not defined