Merge pull request #84 from syasini/develop

Develop

.github/workflows/python-package.yml

@@ -0,0 +1,39 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: Python package
+
+on:
+  push:
+    branches: [ develop, master ]
+  pull_request:
+    branches: [ develop, master ]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.6, 3.7, 3.8]
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install flake8 pytest
+        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      run: |
+        pytest

README.md

@@ -5,7 +5,7 @@ _A python package for painting the sky_
 
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/syasini/AstroPaint/master?filepath=tutorial.ipynb)
 [![Documentation Status](https://readthedocs.org/projects/astropaint/badge/?version=master)](https://astropaint.readthedocs.io/en/master/?badge=master)
-
+![Python package](https://github.com/syasini/AstroPaint/workflows/Python%20package/badge.svg?branch=develop&event=push)
 
 You can install **AstroPaint** by running the following in the command line:
 
@@ -126,7 +126,7 @@ canvas.show_map("cartview", lonra=[0,10], latra=[0,10])
 _Voila!_
 
 You can use the `n_cpus` argument in the spray function to paint in parallel and speed things up! 
-The default value `n_cpus=-1` uses all the available cpus.   
+Setting `n_cpus=-1` uses all the available cpus.   
 
 <p align="center">
 <img src="images/parallel.gif" alt="parallel" width="450"/>
@@ -236,7 +236,7 @@ Let's paint this on a 5x5 sqr deg patch of the WebSky catalog with a mass
  cut of 8E13 M_sun. 
 
  ```python
-catalog = Catalog("websky_lite_redshift")
+catalog = Catalog("WebSky_lite")
 catalog.cut_lon_lat(lon_range=[5,10], lat_range=[5,10])
 catalog.cut_M_200c(8E13)
 

astropaint/lib/datasets.py

@@ -0,0 +1,86 @@
+# @purpose: Get the necessary DataSets
+
+__author__ = "Siavash Yasini, Shobeir K. S. Mazinani"
+__email__ = "yasini@usc.edu , shobeir.mazinani@gmail.com"
+__credits__ = ['Siavash Yasini', 'Shobeir K. S. Mazinani']
+
+
+import requests
+from tqdm import tqdm
+import os
+
+
+
+#########################################################
+#           Get the necessary datasets
+#########################################################
+
+
+def _get_dataset(file_location, ds_url, dataset_name=None):
+    """
+        @purpose: Connect and Download the necessary files and show progressbar
+        @input:
+            file_location: str: file location to download dataset
+            ds_url: str: link to the datasets
+            dataset_name: str: name of the dataset
+
+    """
+
+    response = requests.get(ds_url, stream=True)
+
+    if dataset_name is None:
+        dataset_name = file_location
+
+    # Download and write the file in chuncks and show progressbar
+    with tqdm.wrapattr(open(file_location, "wb"), "write", miniters=1,
+                       total=int(response.headers.get('content-length', 0)),
+                       desc=dataset_name) as fout:
+        for chunk in response.iter_content(chunk_size=4096):
+            fout.write(chunk)
+
+
+def download(dataset_name:str='All', overwrite = True):
+    """
+        @purpose: Download datasets mannualy if not exists into data folder.
+        @Input: Input a string:
+                "All" : Downloads all the relevant datasets.
+                "WebSky_lite" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/WebSky_lite.csv', 
+                "WebSky_2x2" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/WebSky_2x2.csv',
+                "Sehgal" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/Sehgal.csv',
+                "MICE" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/MICE.csv'
+
+    
+    """
+    datasets_url_dict = {
+        "WebSky_lite" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/WebSky_lite.csv', 
+        "WebSky_2x2" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/WebSky_2x2.csv',
+        "Sehgal" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/Sehgal.csv',
+        "MICE" : 'https://media.githubusercontent.com/media/syasini/AstroPaint/master/astropaint/data/MICE.csv',
+    }
+
+    # make a list of all the datasets to be downloaded
+    download_list = []
+
+    # Generate a list of datasets that needs to be downloaded
+
+    if dataset_name == 'All':
+        download_list = [ds_name for ds_name in datasets_url_dict.keys()]
+    elif type(dataset_name) == list:
+        download_list = dataset_name
+    elif type(dataset_name) == str:
+        download_list.append(dataset_name)
+    else:
+        print("Please check the list of available options and try again")
+        raise NameError(f'{dataset_name} is not valid!')
+
+    for dataset in download_list:
+        file_location = os.path.join(os.path.dirname(__file__), os.path.pardir,'data',f'{dataset}.csv')
+        if overwrite:
+            _get_dataset(file_location, datasets_url_dict[dataset], dataset)
+        else:
+            if os.path.getsize(file_location) >= 1000000:
+                _get_dataset(file_location, datasets_url_dict[dataset], dataset)
+
+
+    print('Done!')
+

astropaint/paint_bucket.py

@@ -1174,7 +1174,7 @@ def find_discs_2center_vec(self):
 
         def gen_center_ipix(self, halo_list="All"):
             """generate ipix of the halo centers"""
-            if halo_list is "All":
+            if halo_list =="All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1188,7 +1188,7 @@ def gen_center_ang(self, halo_list="All", snap2pixel=False):
             """generate the angle (theta, phi) of the halo centers
             if snap2pixel is True, the angular coordinate of the halo center pixel will be
             returned"""
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1203,7 +1203,7 @@ def gen_center_ang(self, halo_list="All", snap2pixel=False):
                            self.catalog.data.phi[halo])
 
         def gen_center_vec(self, halo_list="All"):
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1213,7 +1213,7 @@ def gen_center_vec(self, halo_list="All"):
                                  self.catalog.data.phi[halo])
 
         def gen_pixel_index(self, halo_list="All"):
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1229,7 +1229,7 @@ def gen_pixel_index(self, halo_list="All"):
                               )
 
         def gen_pixel_ang(self, halo_list="All"):
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1245,7 +1245,7 @@ def gen_pixel_vec(self, halo_list="All"):
             -------
             None
             """
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1254,7 +1254,7 @@ def gen_pixel_vec(self, halo_list="All"):
                 yield np.asarray(hp.pix2vec(self.nside, index)).T
 
         def gen_cent2pix_rad(self, halo_list="All"):
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1264,7 +1264,7 @@ def gen_cent2pix_rad(self, halo_list="All"):
                 yield hp.rotator.angdist(np.squeeze(pixel_ang), center_ang)
 
         def gen_cent2pix_mpc(self, halo_list="All"):
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             assert hasattr(halo_list, '__iter__')
@@ -1273,15 +1273,15 @@ def gen_cent2pix_mpc(self, halo_list="All"):
                 yield self.center_D_a[halo] * pix2cent_rad
 
         def gen_cent2pix_hat(self, halo_list="All"):
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             for (pix_vec, cent_vec) in zip(self.gen_pixel_vec(halo_list),
                                            self.gen_center_vec(halo_list)):
                 yield Canvas._normalize_vec(pix_vec - cent_vec)
 
         def gen_cent2pix_mpc_vec(self, halo_list="All"):
-            if halo_list is "All":
+            if halo_list == "All":
                 halo_list = range(self.catalog.size)
 
             for (halo, pix_vec, cent_vec) in zip(halo_list,
@@ -1446,7 +1446,8 @@ def set_to_1(disc):
 
         [set_to_1(disc) for disc in self.discs.gen_pixel_index()]
 
-        if graticule: hp.graticule()
+        if graticule:
+            hp.graticule()
 
         self._viewer(junk_pixels,
                      projection=projection,
@@ -1662,8 +1663,11 @@ def linear_transform(patch, slope, intercept):
 
         if lat_range is None:
             lat_range = lon_range
-        if halo_list is "all":
-            halo_list = range(self.catalog.size)
+        try:
+            if halo_list == "all":
+                halo_list = range(self.catalog.size)
+        except ValueError:
+            ...
         #pdb.set_trace()
 
         # make sure that apply func and func_kwargs are lists for consistency
@@ -1813,7 +1817,7 @@ def linear_transform(patch, slope, intercept):
 
         # None values of lat_range  will be fixed in cutouts()
 
-        if halo_list is "all":
+        if halo_list == "all":
             halo_list = range(self.catalog.size)
 
         if ypix is None:
@@ -2014,7 +2018,7 @@ def add_cmb(self,
 
         if lmax is None:
             lmax = 3 * self.nside -1
-        if Cl is "LCDM":
+        if Cl == "LCDM":
             # TODO: add lmax implementation
             Cl_file = utils.get_CMB_Cl(lmax=lmax, mode=mode)
             Cl = Cl_file
@@ -2292,7 +2296,7 @@ def template(self, val):
     def spray(self,
               canvas,
               distance_units="Mpc",
-              n_cpus=-1,
+              n_cpus=1,
               cache=False,
               lazy=False,
               lazy_grid=None,
@@ -2339,14 +2343,14 @@ def spray(self,
 
         R_mode = self.template_args_list[self.R_arg_indx]
 
-        if R_mode is "R":
+        if R_mode == "R":
             R_pix2cent = canvas.discs.gen_cent2pix_mpc
-        if R_mode is "R_vec":
+        if R_mode == "R_vec":
             R_pix2cent = canvas.discs.gen_cent2pix_mpc_vec
 
 
         if cache:
-            assert R_mode is "R", "cache method is not available for profiles that " \
+            assert R_mode == "R", "cache method is not available for profiles that " \
                                   "use 'R_vec'"
 
             from joblib import Memory
@@ -2369,9 +2373,9 @@ def snap2grid(array, grid):
 
                 spray_df.loc[:, column] = snap2grid(data, column_grid)
 
-        if n_cpus is 0:
+        if n_cpus == 0:
             raise ValueError(f"n_cpus = {n_cpus} is not valid. Please enter a value > 0 for n_cpus or -1 to run on all cores.")
-        if n_cpus is 1:
+        if n_cpus == 1:
 
             for halo, R, pixel_index in tqdm(zip(range(canvas.catalog.size),
                                                   R_pix2cent(),
@@ -2395,7 +2399,7 @@ def snap2grid(array, grid):
             print("Spraying in parallel...")
 
             # count the number of available cpus
-            if n_cpus is -1 or n_cpus>(os.cpu_count()):
+            if n_cpus == -1 or n_cpus > (os.cpu_count()):
                 n_cpus = (os.cpu_count())
 
             canvas_memory_size = getsizeof(canvas.pixels)

docs/index.rst

@@ -148,7 +148,7 @@ with. Let's spray ths canvas now:
 *Voila!*
 
 You can use the `n_cpus` argument in the spray function to paint in parallel and speed things up!
-The default value `n_cpus=-1` uses all the available cpus.
+Setting `n_cpus=-1` uses all the available cpus.
 
 
 
@@ -281,7 +281,7 @@ cut of 8E13 M_sun.
 
 .. code-block:: python
 
-   catalog = Catalog("websky_lite_redshift")
+   catalog = Catalog("WebSky_lite")
    catalog.cut_lon_lat(lon_range=[5,10], lat_range=[5,10])
    catalog.cut_M_200c(8E13)
 

requirements.txt

@@ -1,14 +1,16 @@
-astropy==4.0.0
-matplotlib==3.1.2
-numpy==1.19.1
-pytest==5.3.1
-scipy==1.3.0
-pandas==1.0.1
-tqdm==4.48.0
-pyyaml==5.1.2
-decorator==4.4.1
-seaborn==0.9.0
-joblib==0.14.0
-requests==2.24.0
+astropy>=4.0.0
+matplotlib>=3.1.2
+numpy>=1.19.1
+pytest>=5.3.1
+scipy>=1.3.0
+pandas>=1.0.1
+tqdm>=4.48.0
+pyyaml>=5.1.2
+decorator>=4.4.1
+seaborn>=0.9.0
+joblib>=0.14.0
+requests>=2.24.0
 jupyter
-healpy==1.13.0
+requests>=2.24.0
+healpy==1.13.0
+