Merge pull request #1009 from rly/update_readme

Update installation instructions for Macs, min version of rastermap

Author: carsen-stringer

README.md

@@ -15,8 +15,8 @@
 [![GitHub forks](https://img.shields.io/github/forks/MouseLand/suite2p?style=social)](https://github.com/MouseLand/suite2p/)
 
 
-Pipeline for processing two-photon calcium imaging data.  
-Copyright (C) 2018  Howard Hughes Medical Institute Janelia Research Campus  
+Pipeline for processing two-photon calcium imaging data.
+Copyright (C) 2018  Howard Hughes Medical Institute Janelia Research Campus
 
 suite2p includes the following modules:
 
@@ -25,9 +25,9 @@ suite2p includes the following modules:
 * Spike detection
 * Visualization GUI
 
-This code was written by Carsen Stringer and Marius Pachitariu.  
+This code was written by Carsen Stringer and Marius Pachitariu.
 For support, please open an [issue](https://github.com/MouseLand/suite2p/issues).
-The reference paper is [here](https://www.biorxiv.org/content/early/2017/07/20/061507).  
+The reference paper is [here](https://www.biorxiv.org/content/early/2017/07/20/061507).
 The deconvolution algorithm is based on [this paper](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005423), with settings based on [this paper](http://www.jneurosci.org/content/early/2018/08/06/JNEUROSCI.3339-17.2018).
 
 You can now run suite2p in google colab, no need to locally install: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MouseLand/suite2p/blob/main/jupyter/run_suite2p_colab_2021.ipynb). Note you do not have access to the GUI via google colab, but you can download the processed files and view them locally in the GUI.
@@ -54,14 +54,14 @@ Pachitariu, M., Stringer, C., Schröder, S., Dipoppa, M., Rossi, L. F., Carandin
 2. Open an anaconda prompt / command prompt with `conda` for **python 3** in the path
 3. Create a new environment with `conda create --name suite2p python=3.9`.
 4. To activate this new environment, run `conda activate suite2p`
-5. (Option 1) You can install the minimal version of suite2p, run `python -m pip install suite2p`.  
+5. (Option 1) You can install the minimal version of suite2p, run `python -m pip install suite2p`.
 6. (Option 2) You can install the GUI version with `python -m pip install suite2p[gui]`. If you're on a zsh server, you may need to use `' '` around the suite2p[gui] call: `python -m pip install 'suite2p[gui]'`. This also installs the NWB dependencies.
 7. Now run `python -m suite2p` and you're all set.
 8. Running the command `suite2p --version` in the terminal will print the install version of suite2p.
 
 For additional dependencies, like h5py, NWB, Scanbox, and server job support, use the command `python -m pip install suite2p[io]`.
 
-If you are running suite2p on Windows or Linux we recommend installing ScanImage Tiff Reader with `pip install scanimage-tiff-reader` (this package is no longer supported on Mac, but may be supported again in the near future, we will change the instructions accordingly if so).
+We recommend installing ScanImage Tiff Reader with `pip install scanimage-tiff-reader`.
 
 If you have an older `suite2p` environment you can remove it with `conda env remove -n suite2p` before creating a new one.
 
@@ -73,11 +73,9 @@ pip install --upgrade suite2p
 ~~~~
 
 ### Installation for Macs with Apple Silicon chips (e.g., M1)
-1. Download an iTerm2 terminal from this [link](https://iterm2.com/). Install it into your /Applications folder. If you already have downloaded iTerm, duplicate it and give it whatever name you'd like (e.g., "iterm2Rosetta"). 
-2. Navigate to the iTerm app you will use, right click it, and then select "Get Info". Check "Open using Rosetta". 
-3. Open up this iTerm app and follow steps 1 & 2 in the installation section [above](#installation_section) to install anaconda.
-4. Use the following command `CONDA_SUBDIR=osx-64 conda create --name suite2p python=3.9`
-5. Follow steps 4-7 in the installation section [above](#installation_section) to install the `suite2p` package. 
+1. Follow steps 1 & 2 in the installation section [above](#installation_section) to install anaconda.
+2. Use the following command `CONDA_SUBDIR=osx-64 conda create --name suite2p python=3.9`
+3. Follow steps 4-7 in the installation section [above](#installation_section) to install the `suite2p` package.
 
 
 ### Installing the latest github version of the code
@@ -88,7 +86,7 @@ pip install git+https://github.com/MouseLand/suite2p.git
 ~~~
 
 If you want to download and edit the code, and use that version,
-1. Clone the repository with git and `cd suite2p` 
+1. Clone the repository with git and `cd suite2p`
 2. Run `pip install -e .` in that folder
 
 **Common issues**
@@ -148,7 +146,7 @@ The GUI serves two main functions:
 
 Main GUI controls (works in all views):
 
-1. Pan  = Left-Click  + drag  
+1. Pan  = Left-Click  + drag
 2. Zoom = (Scroll wheel) OR (Right-Click + drag)
 3. Full view = Double left-click OR escape key
 4. Swap cell = Right-click on the cell
@@ -174,10 +172,10 @@ See our example jupyter notebook [here](jupyter/run_pipeline_tiffs_or_batch.ipyn
 ## Outputs
 
 ~~~~
-F.npy: array of fluorescence traces (ROIs by timepoints)  
-Fneu.npy: array of neuropil fluorescence traces (ROIs by timepoints)  
-spks.npy: array of deconvolved traces (ROIs by timepoints)  
-stat.npy: array of statistics computed for each cell (ROIs by 1)  
+F.npy: array of fluorescence traces (ROIs by timepoints)
+Fneu.npy: array of neuropil fluorescence traces (ROIs by timepoints)
+spks.npy: array of deconvolved traces (ROIs by timepoints)
+stat.npy: array of statistics computed for each cell (ROIs by 1)
 ops.npy: options and intermediate outputs
 iscell.npy: specifies whether an ROI is a cell, first column is 0/1, and second column is probability that the ROI is a cell based on the default classifier
 ~~~~

setup.py

@@ -2,7 +2,7 @@
 
 install_deps = ["importlib-metadata",
         "natsort",
-        "rastermap>0.1.0",
+        "rastermap>=0.9.0",
         "tifffile",
         "torch>=1.13.1",
         "numpy>=1.24.3",