Differences

This shows you the differences between two versions of the page.

--- eman2:install:condainstall [2025/06/19 21:40] – steveludtke
+++ eman2:install:condainstall [2025/08/22 20:21] (current) – steveludtke
@@ Line 2: / Line 2: @@
 For up-to-date binary installations you must use the instructions on this page. The old binary installation images were retired in late 2023. They are still available for historical purposes, but are no longer updated.
-While the binaries on this page are fine, if you [[EMAN2:Install:SourceInstall|install from source]], then you can rapidly update when we make small patches to the code. Code is being developed continuously, and binaries are built only every few months.
+While the installation method on this page is fine, if you [[EMAN2:Install:SourceInstall|install from source]], then you can rapidly update when we make small patches to the code. Code is being developed continuously, and binaries are often built only every few months.
 ====== Install binary into Anaconda/MiniForge environment (all platforms) ======
+<note>If you are installing EMAN2 on a Windows 11 machine, you __must__ install and set up [[https://learn.microsoft.com/en-us/windows/wsl/install|WSL2]] first! EMAN2 is installed from the WSL2 terminal once WSL2 is set up. Setting up WSL2 is not part of these instructions and this same WSL2 can be used to install other Linux software on your Win 11 machine once set up.</note>
 . **Install Anaconda or [[https://github.com/conda-forge/miniforge/releases|MiniForge]]** (for your platform)
-    * On that page, scroll down to the Latest Release, then download the appropriate file, for example: Miniforge3-Linux-x86_64.sh
+    * Note: If you already have Anaconda installed in your account, you should generally skip this step and move on to step 2
+    * On the MiniForge page above, scroll down to the Latest Release, then download the appropriate file, for example: Miniforge3-Linux-x86_64.sh
     * Run the installer, for example: bash Miniforge3-Linux-x86_64.sh
-    * //On M1/M2 Macs:// make sure you have the ARM64 !MiniForge, not Intel.
+    * //On M1/M2 Macs:// make sure you have the ARM64 MiniForge, not Intel.
-    * //On Windows 11:// the native Windows !MiniForge will not work, you must use the Linux !MiniForge within a [[https://learn.microsoft.com/en-us/windows/wsl/install|WSL2]] environment!
+    * //On Windows 11:// the native Windows MiniForge will not work, you must use the __Linux__ MiniForge within a [[https://learn.microsoft.com/en-us/windows/wsl/install|WSL2]] environment!
-    * We suggest !MiniForge to avoid licensing issues with Anaconda, but if your institution subscribes to Anaconda, that's fine too. If you use Anaconda, you may need to install Mamba manually below.
+    * //For Linux running on ARM processors:// See the relevant section further down on this page.
+    * We suggest MiniForge to avoid licensing issues with Anaconda, but if your institution subscribes to Anaconda, that's fine too. If you use Anaconda, you may need to install Mamba manually below.
-. **Install mamba (only if necessary):**
+. **Install mamba (skip with MiniForge):**
     * if you just installed MiniForge above, you will already have mamba. If you have your own Anaconda installation, you may need this step
  <code>
@@ Line 54: / Line 58: @@
 </code>
-<<Anchor(GPU)>>
 ===== GPU Aceleration & Deep Learning =====
 Older EMAN2 programs make use of Tensorflow for Deep Learning/GPU support, but we have been gradually migrating to the new JAX library, so having both installed is strongly suggested.
@@ Line 60: / Line 63: @@
   * Tensorflow
     * Should be installed automatically as part of the EMAN2 environment setup above
-    * You can check to see what version of Tensorflow and whether it is GPU accelerated with: "conda list|grep tensorflow". On a machine with an NVIDIA GPU and properly configured drivers, you should see a tensorflow version like "2.17.0    cuda120py312h02ad488_203". This says that you are using the CUDA 12.0, Python 3.12 version of tensorflow 2.17.0. If you see "cpu" instead of "cuda" then you do not have GPU acceleration, and you will need to sort that out.
+    * You can check to see what version of Tensorflow and whether it is GPU accelerated with: //conda list|grep tensorflow//. On a machine with an NVIDIA GPU and properly configured drivers, you should see a tensorflow version like **2.17.0    cuda120py312h02ad488_203**. This says that you are using the CUDA 12.0, Python 3.12 version of tensorflow 2.17.0. If you see "cpu" instead of "cuda" then you do not have GPU acceleration, and you will need to sort that out.
     * You can test tensorflow with: //$CONDA_PREFIX/examples/test_tensorflow_basic.py//
@@ Line 66: / Line 69: @@
     * While it is possible to install JAX using conda/mamba, it can be difficult to find a version of GPU JAX and a version of GPU Tensorflow which will install properly together this way.
     * Instead, we strongly suggest just installing JAX using pip:
-      * conda activate eman2
+      <code>
-      * Linux (NVIDIA): //pip install jax[cuda12] optax//
+conda activate eman2
-      * Other (cpu): //pip install jax optax//
+# Linux (NVIDIA):
+pip install "jax[cuda12]" optax
+#Other (cpu):
+pip install jax optax
+      </code>
     * see [[https://pypi.org/project/jax/]] for up to date JAX instructions, this may change more frequently than this page is updated
     * You can test after installation with: //$CONDA_PREFIX/examples/test_jax_basic.py//