fix dwave in rebin

py/picca/data.py

@@ -958,6 +958,7 @@ class Delta(QSO):
             Neighbouring deltas/quasars
         fname: string or None
             String identifying Delta as part of a group
+        delta_log_lambda
 
     Methods:
         __init__: Initializes class instances.
@@ -1315,17 +1316,16 @@ def project(self):
 
         self.delta -= mean_delta + res
 
-    def rebin(self, factor):
+    def rebin(self, factor, dwave=0.8):
         """Rebin deltas by an integer factor
 
         Args:
             factor: int
                 Factor to rebin deltas (new_bin_size = factor * old_bin_size)
+            dwave: float
+                Delta lambda of original deltas
         """
         wave = 10**np.array(self.log_lambda)
-        dwave = wave[1] - wave[0]
-        if not np.isclose(dwave, wave[-1] - wave[-2]):
-            raise ValueError('Delta rebinning only implemented for linear lambda bins')
 
         start = wave.min() - dwave / 2
         num_bins = np.ceil(((wave[-1] - wave[0]) / dwave + 1) / factor)

py/picca/io.py

@@ -1439,8 +1439,19 @@ def read_delta_file(filename, rebin_factor=None):
 
     # Rebin
     if rebin_factor is not None:
+        if 'LAMBDA' in hdul:
+            card = 'METADATA'
+        else:
+            card = 1
+
+        if hdul[card].read_header()['WAVE_SOLUTION'] != 'lin':
+            raise ValueError('Delta rebinning only implemented for linear \
+                    lambda bins')
+
+        dwave = hdul[card].read_header()['DELTA_LAMBDA']
+
         for i in range(len(deltas)):
-            deltas[i].rebin(rebin_factor)
+            deltas[i].rebin(rebin_factor, dwave=dwave)
 
     return deltas
 
@@ -1513,9 +1524,12 @@ def read_deltas(in_dir,
         userprint(f"Rebinning deltas by a factor of {rebin_factor}\n")
 
     arguments = [(f, rebin_factor) for f in files]
-    pool = Pool(processes=nproc)
-    results = pool.starmap(read_delta_file, arguments)
-    pool.close()
+    results = []
+    for argument in arguments:
+        results.append(read_delta_file(*argument))
+    # pool = Pool(processes=nproc)
+    # results = pool.starmap(read_delta_file, arguments)
+    # pool.close()
 
     deltas = []
     num_data = 0