Merge pull request #68 from dkazanc/envupd

updates to conda env

.github/workflows/ubuntu.yml

@@ -1,10 +1,6 @@
 name: linux
 
-on:
-  pull_request:
-    # Sequence of patterns matched against refs/heads
-    branches:
-      - main
+on: [push]
 
 jobs:
   build-linux:

INSTALLATION

@@ -1,4 +1,4 @@
-** INSTALLATION of dependencies **
+** INSTALLATION of dependencies for Matlab **
 Here we provide detailed installation information for the following dependencies: 
 
  ## ASTRA-toolbox 

Readme.md

@@ -47,9 +47,9 @@
  * See [INSTALLATION](https://github.com/dkazanc/TomoRec/blob/master/INSTALLATION) for detailed information
 
 ### Python conda:
-Install ToMoBAR and basic dependencies into a new environment using the provided [file](https://github.com/dkazanc/ToMoBAR/blob/master/conda-recipe/tomobar_env.txt):
+Install ToMoBAR and its basic dependencies into a new environment using the provided [file](https://github.com/dkazanc/ToMoBAR/blob/master/conda-recipe/tomobar_env_20_06_22.txt):
 ```
-conda create --name tomobar --file conda-recipe/tomobar_env.txt
+conda create --name tomobar --file conda-recipe/tomobar_env_20_06_22.txt
 ```
 
 Install the ToMoBAR package from one of conda channels bellow:
@@ -72,19 +72,19 @@ For building on Linux, modify and run the following [script](https://github.com/
 ### MultiGPU capability
 ToMoBAR can be used by running in parallel across multiple GPU devices on a PC or a compute node of a cluster. In order to initiate a parallel run on multiple GPUs you will need an MPI library, such as, [mpi4py](https://mpi4py.readthedocs.io/en/stable/). See this [demo](https://github.com/dkazanc/ToMoBAR/blob/master/Demos/Python/MultiGPU_demo.py).
 
-### Matlab (is not currently supported)
+### Matlab (is not currently actively supported)
 Use available m-functions, see [Demos](https://github.com/dkazanc/ToMoBAR/tree/master/Demos/Matlab).
 
-### How to use ToMoBAR in Python:
-Detailed information about methods and parameters can be obtained with:
+## How to use ToMoBAR in Python:
+Detailed information about the methods and its parameters can be obtained with:
 ```
 from tomobar.methodsIR import RecToolsIR
 help(RecToolsIR)
 from tomobar.methodsDIR import RecToolsDIR
 help(RecToolsIR)
 ```
 
-A typical setup for iterative reconstruction would include three dictionaries: `_data_`, `_algorithm_` and `_regularisation_`
+A typical setup for iterative reconstruction would include building three dictionaries: `_data_`, `_algorithm_` and `_regularisation_`
 <div align="left">
   <img src="docs/images/tomobar_pres.png" width="620">  
 </div>

conda-recipe/tomobar_env_20_06_22.txt

@@ -0,0 +1,43 @@
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+@EXPLICIT
+https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/blas-1.0-mkl.conda
+https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2022.6.15-ha878542_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/intel-openmp-2021.4.0-h06a4308_3561.conda
+https://repo.anaconda.com/pkgs/main/linux-64/ld_impl_linux-64-2.38-h1181459_1.conda
+https://repo.anaconda.com/pkgs/main/linux-64/libgfortran4-7.5.0-ha8ba4b0_17.conda
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-12.1.0-ha89aaad_16.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/libgfortran-ng-7.5.0-ha8ba4b0_17.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgomp-12.1.0-h8d9b700_16.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/mkl-2021.4.0-h06a4308_640.conda
+https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-12.1.0-h8d9b700_16.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/libastra-2.1.0-hefdcf68_4.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/libffi-3.3-he6710b0_2.conda
+https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.3-h7f8727e_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/openssl-1.1.1o-h166bdaf_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.5-h7f8727e_1.conda
+https://repo.anaconda.com/pkgs/main/linux-64/zlib-1.2.12-h7f8727e_2.conda
+https://repo.anaconda.com/pkgs/main/linux-64/readline-8.1.2-h7f8727e_1.conda
+https://repo.anaconda.com/pkgs/main/linux-64/tk-8.6.12-h1ccaba5_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/sqlite-3.38.3-hc218d9a_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/python-3.7.13-h12debd9_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.7-2_cp37m.tar.bz2
+https://repo.anaconda.com/pkgs/main/noarch/six-1.16.0-pyhd3eb1b0_1.conda
+https://repo.anaconda.com/pkgs/main/noarch/wheel-0.37.1-pyhd3eb1b0_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/certifi-2022.6.15-py37h89c1867_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/mkl-service-2.4.0-py37h7f8727e_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/numpy-base-1.21.5-py37ha15fc14_3.conda
+https://repo.anaconda.com/pkgs/main/linux-64/setuptools-61.2.0-py37h06a4308_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/pip-21.2.2-py37h06a4308_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/mkl_fft-1.3.1-py37hd3c417c_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/mkl_random-1.2.2-py37h51133e4_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/numpy-1.21.5-py37h6c91a56_3.conda
+https://conda.anaconda.org/savu-dep/linux-64/ccpi-regulariser-2022.06-np121py37_0.tar.bz2
+https://conda.anaconda.org/savu-dep/linux-64/pypwt-0.9_10.2-py37hadde398_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/scipy-1.7.3-py37hc147768_0.conda
+https://conda.anaconda.org/savu-dep/linux-64/tomophantom-2022.05-np121py37_0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/astra-toolbox-2.1.0-py37hb9c9857_0.tar.bz2
+https://conda.anaconda.org/savu-dep/linux-64/tomobar-2022.06-py37he0f2a6c_0.tar.bz2

scripts/conda_upload.sh

@@ -15,6 +15,7 @@ conda build . --numpy=1.15 --python=3.6
 conda build . --numpy=1.15 --python=3.7
 conda build . --numpy=1.21 --python=3.7
 conda build . --numpy=1.18 --python=3.8
+conda build . --numpy=1.21 --python=3.9
 
 # upload packages to conda
 find $CONDA_BLD_PATH/$OS -name *.tar.bz2 | while read file