removed deprecated np.int

LucaMalavolta · Apr 30, 2024 · 64e1598 · 64e1598
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commit 64e1598
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diff --git a/README.md b/README.md
@@ -16,20 +16,18 @@ Fro **Technical problems and software maintenance** please contact Luca Malavolt
 
 
 **News**
-In version 1.1 it is much easier to add new instruments
+Version 1.3 now satisfies the new FITS requirements of `molecfit` version 4.3.1 (as for 30th of April 2024) 
+Starting from version 1.1, it is much easier to add new instruments
 
-Paper accepted, repository now publicly available, documentation and examples coming online in a few days.
-
-Basic [documentation available here](https://sloppy.readthedocs.io/en/latest/), updates will follow in the upcoming weeks.
+Basic [documentation is available here](https://sloppy.readthedocs.io/en/latest/).
 
 Most of the information can be found in Sicilia et al. (2022) [A&A link](https://doi.org/10.1051/0004-6361/202244055) [ADS link](https://ui.adsabs.harvard.edu/abs/2022arXiv220813045S/abstract) [arXiv link](https://arxiv.org/abs/2208.13045)
 
+**Note on the use of `molecfitv**
 
-**Note on the use of molecfit**
-
-`SLOPpy` supports both the old version `1.5.x` (available as a stand-alone program) and the latest version `>4` through ESO esorex.
+`SLOPpy` supports both the old version `1.5.x` (available as a stand-alone program) and the latest version `>4` through ESO `esorex`.
 
-To use version 1.5.x, you have to use the molecfit modules marked with `v1`, and specify the installation path under the `molecfit` section:
+To use version 1.5.x, you have to use the `molecfit` modules marked with `v1`, and specify the installation path under the `molecfit` section:
 
 ```bash
 pipeline:

diff --git a/SLOPpy/quick_transmission.py b/SLOPpy/quick_transmission.py
@@ -28,7 +28,7 @@ def compute_quick_transmission(config_in, lines_label):
         'subroutine': subroutine_name,
         'binned_wave': shared_data['binned']['wave'][binned_selection],
         'binned_step': shared_data['binned']['step'][binned_selection],
-        'binned_size': np.int(np.sum(binned_selection))
+        'binned_size': int(np.sum(binned_selection))
     }
 
     import matplotlib.pyplot as plt

diff --git a/SLOPpy/spectra_lightcurve.py b/SLOPpy/spectra_lightcurve.py
@@ -63,7 +63,7 @@ def compute_spectra_lightcurve(config_in, lines_label):
         'range': lines_dict['range'],
         'wave': shared_data['coadd']['wave'][shared_selection],
         'step': shared_data['coadd']['step'][shared_selection],
-        'size': np.int(np.sum(shared_selection)),
+        'size': int(np.sum(shared_selection)),
     }
 
     if 'full_transit_duration' in planet_dict:

diff --git a/SLOPpy/spectra_lightcurve_bkp.py b/SLOPpy/spectra_lightcurve_bkp.py
@@ -56,7 +56,7 @@ def compute_spectra_lightcurve(config_in, lines_label):
         'range': lines_dict['range'],
         'wave': shared_data['coadd']['wave'][shared_selection],
         'step': shared_data['coadd']['step'][shared_selection],
-        'size': np.int(np.sum(shared_selection)),
+        'size': int(np.sum(shared_selection)),
     }
 
 

diff --git a/SLOPpy/subroutines/mcmc_fit_functions.py b/SLOPpy/subroutines/mcmc_fit_functions.py
@@ -65,7 +65,7 @@ def logprob_case00(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -147,7 +147,7 @@ def logprob_case01(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -228,7 +228,7 @@ def logprob_case02(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -295,7 +295,7 @@ def logprob_case03(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -363,7 +363,7 @@ def logprob_case10(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -455,7 +455,7 @@ def logprob_case11(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -546,7 +546,7 @@ def logprob_case12(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
 
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
@@ -639,7 +639,7 @@ def logprob_case13(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -729,7 +729,7 @@ def logprob_case14(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -820,7 +820,7 @@ def logprob_case15(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -913,7 +913,7 @@ def logprob_case20(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -999,7 +999,7 @@ def logprob_case21(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -1084,7 +1084,7 @@ def logprob_case22(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -1169,7 +1169,7 @@ def logprob_case23(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -1254,7 +1254,7 @@ def logprob_case24(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)
@@ -1339,7 +1339,7 @@ def logprob_case25(theta,
         jitter_pams = 0.
     elif len(jitter_index) > 0:
         jitter_array = jitter_index * 0.
-        n_jitter = np.int(np.amax(jitter_index) + 1)
+        n_jitter = int(np.amax(jitter_index) + 1)
         jitter_pams = np.empty(n_jitter)
         for i_j in range(0, n_jitter):
             sel = (jitter_index == i_j)

diff --git a/SLOPpy/transmission_lightcurve_average.py b/SLOPpy/transmission_lightcurve_average.py
@@ -77,10 +77,10 @@ def compute_transmission_lightcurve_average(config_in, lines_label, reference='p
         'range': lines_dict['range'],
         'wave': shared_data['coadd']['wave'][shared_selection],
         'step': shared_data['coadd']['step'][shared_selection],
-        'size': np.int(np.sum(shared_selection)),
+        'size': int(np.sum(shared_selection)),
         'binned_wave': shared_data['binned']['wave'][binned_selection],
         'binned_step': shared_data['binned']['step'][binned_selection],
-        'binned_size': np.int(np.sum(binned_selection))
+        'binned_size': int(np.sum(binned_selection))
     }
 
     for output_selection in output_list:

diff --git a/SLOPpy/transmission_spectrum.py b/SLOPpy/transmission_spectrum.py
@@ -65,10 +65,10 @@ def compute_transmission_spectrum(config_in, lines_label, reference='planetRF',
         'range': lines_dict['range'],
         'wave': shared_data['coadd']['wave'][shared_selection],
         'step': shared_data['coadd']['step'][shared_selection],
-        'size': np.int(np.sum(shared_selection)),
+        'size': int(np.sum(shared_selection)),
         'binned_wave': shared_data['binned']['wave'][binned_selection],
         'binned_step': shared_data['binned']['step'][binned_selection],
-        'binned_size': np.int(np.sum(binned_selection))
+        'binned_size': int(np.sum(binned_selection))
     }
 
     for night in night_dict:

diff --git a/SLOPpy/transmission_spectrum_average.py b/SLOPpy/transmission_spectrum_average.py
@@ -45,10 +45,10 @@ def compute_transmission_spectrum_average(config_in, lines_label, reference='pla
         'range': line_iter_dict['range'],
         'wave': shared_data['coadd']['wave'][shared_selection],
         'step': shared_data['coadd']['step'][shared_selection],
-        'size': np.int(np.sum(shared_selection)),
+        'size': int(np.sum(shared_selection)),
         'binned_wave': shared_data['binned']['wave'][binned_selection],
         'binned_step': shared_data['binned']['step'][binned_selection],
-        'binned_size': np.int(np.sum(binned_selection))
+        'binned_size': int(np.sum(binned_selection))
     }
 
     results_list = ['user',

diff --git a/SLOPpy/write_output_transmission.py b/SLOPpy/write_output_transmission.py
@@ -90,10 +90,10 @@ def write_output_transmission(config_in, reference='planetRF', night_input='', p
             'range': range_temp,
             'wave': shared_data['coadd']['wave'][shared_selection],
             'step': shared_data['coadd']['step'][shared_selection],
-            'size': np.int(np.sum(shared_selection)),
+            'size': int(np.sum(shared_selection)),
             'binned_wave': shared_data['binned']['wave'][binned_selection],
             'binned_step': shared_data['binned']['step'][binned_selection],
-            'binned_size': np.int(np.sum(binned_selection))
+            'binned_size': int(np.sum(binned_selection))
         }
 
     else:

diff --git a/setup.py b/setup.py
@@ -37,8 +37,8 @@
     },
     zip_safe=False,
     install_requires=[
-        'numpy>=1.22',
-        'numba>=0.55.2',
+        'numpy>=1.26.4',
+        'numba>=0.59.1',
         'scipy>=1.8.1',
         'matplotlib>=3.5.2',
         'astropy>=5.1',