Anaconda Installation Instructions and Bug Fix

Install-conda.md

@@ -0,0 +1,79 @@
+## Installation Guide for Priism in Conda Environments
+
+### Notes
+
+- This installation process has been tested on Linux (Archlinux and OpenSUSE), and it should also work for other Linux distributions. However, it has **not** been tested on macOS.
+- We recommend using **Miniforge** or **Miniconda** for this installation, as they are free and open-source. However, please note that access to **Anaconda’s public repository** of packages is only free for individuals and small organizations (fewer than 200 employees). A paid license is required for larger organizations or those embedding/mirroring Anaconda’s repository. For more details, refer to [Anaconda's terms of service](https://www.anaconda.com/terms-of-service).
+- Using **Miniforge**, which is configured to use the **conda-forge** channel by default, is a good alternative if you want to avoid licensing concerns related to Anaconda’s repository.
+- Ensure you have the appropriate permissions for copying files and modifying your environment.
+
+
+### Step-by-Step Installation Instructions 
+
+1. **Create a new conda environment:**
+    ```bash
+    conda create -n priism python=3.10
+    ```
+
+2. **Activate the environment:**
+    ```bash
+    conda activate priism
+    ```
+
+3. **Install Jupyter and necessary dependencies:**
+    ```bash
+    conda install conda-forge::jupyter
+    conda install conda-forge::astropy
+    ```
+
+
+4. **Clone the PRIISM repository from GitHub:**
+    ```bash
+    git clone https://github.com/tnakazato/priism.git
+    ```
+
+5. **Navigate into the project directory and update the repository:**
+    ```bash
+    cd priism
+    git pull
+    ```
+
+6. **Install required Python packages:**
+    - This will install all necessary dependencies, including `casatasks` and `casatools` 
+    ```bash
+    python -m pip install -r requirements.txt
+    ```
+
+7. **Install the newest version of GCC (Optinal):**
+    - If you encounter an error like "GLIBCXX_x.x.xx' not found" during the build process, install the latest version of GCC via:
+    ```bash
+    conda install conda-forge::gcc
+    ```
+
+8. **Manually copy the Python library (`libpython3.10.a`):**
+    - Download the latest CASA package from the official website, locate the `libpython3.10.a` file (typically found in `/your_casa_folder/lib/py/lib`).
+    - Copy the file to the `lib` folder of your `priism` environment (typically `/your_conda_folder/envs/priism/lib/`).
+
+9. **Ensure that the `~/.casa/data` folder exists:**
+    - If it doesn’t exist, create the folder:
+    ```bash
+    mkdir -p ~/.casa/data
+    ```
+
+10. **Build the project:**
+    ```bash
+    python setup.py build
+    ```
+
+11. **Install the project:**
+    ```bash
+    python setup.py install
+    ```
+
+12. **Installation Complete!**
+    - The Priism package should now be installed and ready to use in the `priism` environment. You can start exploring the tutorials to get familiar with its functionalities.
+
+
+---
+
+Feel free to add any more instructions or troubleshooting tips as needed.

python/priism/core/imager.py

@@ -732,10 +732,19 @@ def __init__(self, nv, nh, L1_list, Ltsv_list):
         self.axes_list = collections.defaultdict(dict)
 
     def plotimage(self, L1, Ltsv, data, mse):
-        assert L1 in self.L1_list
-        assert Ltsv in self.Ltsv_list
-        row = np.where(self.L1_list == L1)[0][0]
-        column = np.where(self.Ltsv_list == Ltsv)[0][0]
+
+        # Use np.isclose for tolerance-based comparisons
+        # assert L1 in self.L1_list
+        # assert Ltsv in self.Ltsv_list
+        assert any(np.isclose(L1, val) for val in self.L1_list), f"L1: {L1} not found in L1_list"
+        assert any(np.isclose(Ltsv, val) for val in self.Ltsv_list), f"Ltsv: {Ltsv} not found in Ltsv_list"
+
+        # Find the index using np.isclose for tolerance-based matching
+        # row = np.where(self.L1_list == L1)[0][0]
+        # column = np.where(self.Ltsv_list == Ltsv)[0][0]
+        row = np.where(np.isclose(self.L1_list, L1))[0][0]
+        column = np.where(np.isclose(self.Ltsv_list, Ltsv))[0][0]
+
         cx = self.outer_frame.left_margin + (column + 0.5) * self.outer_frame.dx
         cy = self.outer_frame.bottom_margin + (row + 0.5) * self.outer_frame.dy
         left = cx - self.image_width / 2
@@ -751,10 +760,19 @@ def plotimage(self, L1, Ltsv, data, mse):
         self.axes_list[row][column] = a
 
     def mark_bestimage(self, L1, Ltsv):
-        assert L1 in self.L1_list
-        assert Ltsv in self.Ltsv_list
-        row = np.where(self.L1_list == L1)[0][0]
-        column = np.where(self.Ltsv_list == Ltsv)[0][0]
+
+        # Use np.isclose for tolerance-based comparisons
+        # assert L1 in self.L1_list
+        # assert Ltsv in self.Ltsv_list
+        assert any(np.isclose(L1, val) for val in self.L1_list), f"L1: {L1} not found in L1_list"
+        assert any(np.isclose(Ltsv, val) for val in self.Ltsv_list), f"Ltsv: {Ltsv} not found in Ltsv_list"
+
+        # Find the index using np.isclose for tolerance-based matching
+        # row = np.where(self.L1_list == L1)[0][0]
+        # column = np.where(self.Ltsv_list == Ltsv)[0][0]
+        row = np.where(np.isclose(self.L1_list, L1))[0][0]
+        column = np.where(np.isclose(self.Ltsv_list, Ltsv))[0][0]
+
         best_axes = self.axes_list[row][column]
         bbox = best_axes.get_position()
         if int(matplotlib.__version__.split('.')[0]) > 1:

setup.py

@@ -165,14 +165,21 @@ def get_python_library(include_dir):
         libnames.append(libname2)
 
     libpath = sysconfig.get_config_var('LIBDIR')
+    print(f"Trying library names: {libnames}")
+    print(f"Checking in libpath: {libpath}")
+
     for libname in libnames:
         pylib = os.path.join(libpath, libname)
+        print(f"Checking {pylib}")
         if os.path.exists(pylib):
             return pylib
 
     libpath2 = os.path.join(libpath, sysconfig.get_config_var('MULTIARCH'))
+    print(f"Checking in libpath2: {libpath2}")
+
     for libname in libnames:
         pylib = os.path.join(libpath2, libname)
+        print(f"Checking {pylib}")
         if os.path.exists(pylib):
             return pylib
 
@@ -184,17 +191,23 @@ def get_python_library(include_dir):
 
     for l in ['lib', 'lib64']:
         libpath = os.path.join(prefix, l)
+        print(f"Checking in {libpath}")
+
         for libname in libnames:
             pylib = os.path.join(libpath, libname)
+            print(f"Checking {pylib}")
             if os.path.exists(pylib):
                 return pylib
 
         libpath2 = os.path.join(libpath, sysconfig.get_config_var('MULTIARCH'))
         for libname in libnames:
             pylib = os.path.join(libpath2, libname)
+            print(f"Checking {pylib}")
             if os.path.exists(pylib):
                 return pylib
 
+    # Print out a helpful error message instead of just failing
+    print(f"Failed to find Python library in {libnames}")
     assert False
 
 

tutorial_hltau.ipynb

@@ -94,7 +94,7 @@
    "source": [
     "Sample data for the tutorial is the protoplanetary disk \"**HL Tau**\" observed at Band 6 with long baselines of ALMA 12m array as part of [science verification](https://almascience.nao.ac.jp/alma-data/science-verification). The calibration information can be obtained from [CASA Guide](https://casaguides.nrao.edu/index.php?title=ALMA2014_LBC_SVDATA#HL_Tau_-_Protoplanetary_Disk), and the data can be downloaded from the link below: \n",
     "\n",
-    "https://alma-dl.mtk.nao.ac.jp/ftp/alma/sciver/HLTauBand6/HLTau_Band6_CalibratedData.tgz\n",
+    "https://almascience.nao.ac.jp/almadata/sciver/HLTauBand6/HLTau_Band6_CalibratedData.tgz\n",
     "\n",
     "After you download the data, you should extract the MS from the file. You may run the following cell to obtain the dataset."
    ]
@@ -111,7 +111,7 @@
     "%%bash\n",
     "\n",
     "# download if necessary\n",
-    "[ -e HLTau_Band6_CalibratedData.tgz ] || wget -nv https://alma-dl.mtk.nao.ac.jp/ftp/alma/sciver/HLTauBand6/HLTau_Band6_CalibratedData.tgz\n",
+    "[ -e HLTau_Band6_CalibratedData.tgz ] || wget -nv https://almascience.nao.ac.jp/almadata/sciver/HLTauBand6/HLTau_Band6_CalibratedData.tgz\n",
     "\n",
     "# extract data from tar-ball\n",
     "[ -e HLTau_Band6_CalibratedData ] || tar xf HLTau_Band6_CalibratedData.tgz"