diff --git a/config/calibration/mask_v1.X.7.yaml b/config/calibration/mask_v1.X.7.yaml
new file mode 100644
index 0000000..49325e3
--- /dev/null
+++ b/config/calibration/mask_v1.X.7.yaml
@@ -0,0 +1,115 @@
+# Config file for masking and calibration.
+# Standard cuts without halo masks, type v1.X.7.
+
+# General parameters (can also given on command line)
+params:
+  input_path: unions_shapepipe_comprehensive_struc_2024_v1.X.c.hdf5
+  cmatrices: False
+  sky_regions: False
+  verbose: True
+
+# Masks
+## Using columns in 'dat' group (ShapePipe flags)
+dat:
+  # SExtractor flags
+  - col_name: FLAGS
+    label: SE FLAGS
+    kind: equal
+    value: 0
+
+  # Duplicate objects
+  - col_name: overlap
+    label: tile overlap
+    kind: equal
+    value: True
+
+  # ShapePipe flags
+  - col_name: IMAFLAGS_ISO
+    label: SP mask
+    kind: equal
+    value: 0
+
+  # Number of epochs
+  - col_name: N_EPOCH
+    label: r"$n_{\rm epoch}$"
+    kind: greater_equal
+    value: 2
+
+  # Magnitude range
+  - col_name: mag
+    label: mag range
+    kind: range
+    value: [15, 30]
+
+  # ngmix flags
+  - col_name: NGMIX_MOM_FAIL
+    label: "ngmix moments failure"
+    kind: equal
+    value: 0
+
+  # invalid PSF ellipticities
+  - col_name: NGMIX_ELL_PSFo_NOSHEAR_0
+    label: "bad PSF ellipticity comp 1"
+    kind: not_equal
+    value: -10
+  - col_name: NGMIX_ELL_PSFo_NOSHEAR_1
+    label: "bad PSF ellipticity comp 2"
+    kind: not_equal
+    value: -10
+
+## Using columns in 'dat_ext' group (post-processing flags)
+dat_ext:
+
+  # Bright star halos                                                            
+  - col_name: 2_Bright_star_halos
+    label: "Bright star halos"
+    kind: equal
+    value: False
+  # Stars
+  - col_name: 4_Stars
+    label: "Stars"
+    kind: equal
+    value: False
+
+  # Manual mask
+  - col_name: 8_Manual
+    label: "manual mask"
+    kind: equal
+    value: False
+
+  # r-band footprint
+  - col_name: 64_r
+    label: "r-band imaging"
+    kind: equal
+    value: False
+
+  # Maximask
+  - col_name: 1024_Maximask
+    label: "maximask"
+    kind: equal
+    value: False
+
+  # Rough pointing coverage
+  - col_name: npoint3
+    label: r"$n_{\rm pointing}$"
+    kind: greater_equal
+    value: 3
+
+# Metacal parameters
+metacal:
+  # Ellipticity dispersion
+  sigma_eps_prior: 0.34
+
+  # Signal-to-noise range
+  gal_snr_min: 10
+  gal_snr_max: 500
+
+  # Relative-size (hlr / hlr_psf) range
+  gal_rel_size_min: 0.707
+  gal_rel_size_max: 3
+
+  # Correct relative size for ellipticity?
+  gal_size_corr_ell: False
+
+  # Weight for global response matrix, None for unweighted mean
+  global_R_weight: w
diff --git a/config/calibration/mask_v1.X.8.yaml b/config/calibration/mask_v1.X.8.yaml
new file mode 100644
index 0000000..c346b33
--- /dev/null
+++ b/config/calibration/mask_v1.X.8.yaml
@@ -0,0 +1,121 @@
+# Config file for masking and calibration.
+# Standard cuts without halo masks, type v1.X.7.
+
+# General parameters (can also given on command line)
+params:
+  input_path: unions_shapepipe_comprehensive_struc_2024_v1.X.c.hdf5
+  cmatrices: False
+  sky_regions: False
+  verbose: True
+
+# Masks
+## Using columns in 'dat' group (ShapePipe flags)
+dat:
+  # SExtractor flags
+  - col_name: FLAGS
+    label: SE FLAGS
+    kind: equal
+    value: 0
+
+  # Duplicate objects
+  - col_name: overlap
+    label: tile overlap
+    kind: equal
+    value: True
+
+  # ShapePipe flags
+  - col_name: IMAFLAGS_ISO
+    label: SP mask
+    kind: equal
+    value: 0
+
+  # Number of epochs
+  - col_name: N_EPOCH
+    label: r"$n_{\rm epoch}$"
+    kind: greater_equal
+    value: 2
+
+  # Magnitude range
+  - col_name: mag
+    label: mag range
+    kind: range
+    value: [15, 30]
+
+  # ngmix flags
+  - col_name: NGMIX_MOM_FAIL
+    label: "ngmix moments failure"
+    kind: equal
+    value: 0
+
+  # invalid PSF ellipticities
+  - col_name: NGMIX_ELL_PSFo_NOSHEAR_0
+    label: "bad PSF ellipticity comp 1"
+    kind: not_equal
+    value: -10
+  - col_name: NGMIX_ELL_PSFo_NOSHEAR_1
+    label: "bad PSF ellipticity comp 2"
+    kind: not_equal
+    value: -10
+
+## Using columns in 'dat_ext' group (post-processing flags)
+dat_ext:
+
+  # Faint star halos
+  - col_name: 1_Faint_star_halos
+    label: "Faint star halos"
+    kind: equal
+    value: False
+
+  # Bright star halos                                                            
+  - col_name: 2_Bright_star_halos
+    label: "Bright star halos"
+    kind: equal
+    value: False
+  # Stars
+  - col_name: 4_Stars
+    label: "Stars"
+    kind: equal
+    value: False
+
+  # Manual mask
+  - col_name: 8_Manual
+    label: "manual mask"
+    kind: equal
+    value: False
+
+  # r-band footprint
+  - col_name: 64_r
+    label: "r-band imaging"
+    kind: equal
+    value: False
+
+  # Maximask
+  - col_name: 1024_Maximask
+    label: "maximask"
+    kind: equal
+    value: False
+
+  # Rough pointing coverage
+  - col_name: npoint3
+    label: r"$n_{\rm pointing}$"
+    kind: greater_equal
+    value: 3
+
+# Metacal parameters
+metacal:
+  # Ellipticity dispersion
+  sigma_eps_prior: 0.34
+
+  # Signal-to-noise range
+  gal_snr_min: 10
+  gal_snr_max: 500
+
+  # Relative-size (hlr / hlr_psf) range
+  gal_rel_size_min: 0.707
+  gal_rel_size_max: 3
+
+  # Correct relative size for ellipticity?
+  gal_size_corr_ell: False
+
+  # Weight for global response matrix, None for unweighted mean
+  global_R_weight: w
diff --git a/notebooks/demo_create_footprint_mask.py b/notebooks/demo_create_footprint_mask.py
index 357ecb7..df710c6 100644
--- a/notebooks/demo_create_footprint_mask.py
+++ b/notebooks/demo_create_footprint_mask.py
@@ -39,7 +39,7 @@
 
 # Set parameters
 obj._params["mask_dir"] = f"{os.environ['HOME']}/masks"
-obj._params["aux_mask_files"] = f"{obj._params['mask_dir']}/coverage.hsp"
+obj._params["aux_mask_files"] = f"{obj._params['mask_dir']}/coverage_v1.4.x.hsp"
 obj._params["aux_mask_labels"] = "npoint3"
 obj._params["verbose"] = True
 
@@ -66,9 +66,9 @@
         if mask_params["col_name"] in all_masks_bits:
             bits = bits | all_masks_bits[mask_params["col_name"]]
             
-        # Check auxillary masks
+        # Check auxiliary masks
         if "npoint3" == mask_params["col_name"]:
-            auxiliary_masks.append(f"{obj._params['mask_dir']}/coverage.hsp")
+            auxiliary_masks.append(obj._params["aux_mask_files"])
             auxiliary_labels.append("npoint3")
 
 # Update bits for following function call
diff --git a/notebooks/tests_bump.py b/notebooks/tests_bump.py
index 18e3152..9eca268 100644
--- a/notebooks/tests_bump.py
+++ b/notebooks/tests_bump.py
@@ -1,5 +1,5 @@
 # %%
-# Tests
+# Tests of rhe bump in xi_+
 
 # %%                                                                             
 from IPython import get_ipython                                                  
@@ -14,8 +14,10 @@
     ipython.run_line_magic("matplotlib", "inline")
 
 # %%
+import os
 import numpy as np
 import pandas as pd
+import treecorr
 
 import matplotlib.pyplot as plt
 
@@ -29,159 +31,133 @@
 from sp_validation import plots as sp_plots
 
 # %%
-os.getcwd()
+print("cwd = ", os.getcwd())
 
 # %%
 # Initialize calibration class instance
 obj = sp_joint.CalibrateCat()
-
 config = obj.read_config_set_params("config_minimal.yaml")
 
-
+# %%
 # Get data. Set load_into_memory to False for very large files
 dat, _ = obj.read_cat(load_into_memory=False)
 
 # %%
-#n_test = -1
-n_test = 1_000_000
+n_test = -1
+#n_test = 1_000_000
 if n_test > 0:
     print(f"MKDEBUG testing only first {n_test} objects")
     dat = dat[:n_test]
 
 # %%
-# Use only some columns in dat for efficiency
-use_all_columns = True
-
-if not use_all_columns:
-    
-    required_columns = set()
-    for section, mask_list in config_data.items():
-        for mask_params in mask_list:
-            required_columns.add(mask_params["col_name"])
-
-    #user_columns = ["NGMIX_T_NOSHEAR", "NGMIX_Tpsf_NOSHEAR", "NGMIX_FLUX_NOSHEAR", "NGMIX_FLUX_ERR_NOSHEAR"]      
-    #required_columns.update(user_columns)
-
-    print(f"{len(dat.dtype.names)} -> {len(required_columns)}")
-
-    # Unsolved error here
-    #dat = {col: obj._hd5file['data'][col][:] for col in required_columns if col in obj._hd5file['data']}
-
-# %%
-if "applied_masks" in obj._hd5file:
-    applied_masks = obj._hd5file["applied_masks"]
-    applied_masks["desc"]
-else:
-    applied_masks = None
-
-# ## Masking
-masks_to_apply = [
-    "N_EPOCH",
-    "FLAGS",
-    "4_Stars",
-    "npoint3",
-]
-
-# Check that mask has not already been applied
-for mask in masks_to_apply:
-    if applied_masks and mask in applied_masks["desc"]:
-        print(f"Warning: Mask {mask} has already been applied")
-    else:
-        pass
-
-# Gather mask information for above list from config
-masks, labels = sp_joint.get_masks_from_config(config, dat, dat, masks_to_apply=masks_to_apply, verbose=obj._params["verbose"])
-
-# Initialise combined mask
-label = "comb"
-my_mask = sp_joint.Mask(label, label, kind="combined", value=None)
-
-# Combine masks
-mask_combined = sp_joint.Mask.from_list(
-    masks,
-    label="combined",
-    verbose=obj._params["verbose"],
-)
-
-# Output some mask statistics
-sp_joint.print_mask_stats(dat.shape[0], masks, mask_combined)
-
-# %%
-# Call metacal
-cm = config["metacal"]
-gal_metacal = metacal(
-    dat,
-    mask_combined._mask,
-    snr_min=cm["gal_snr_min"],
-    snr_max=cm["gal_snr_max"],
-    rel_size_min=cm["gal_rel_size_min"],
-    rel_size_max=cm["gal_rel_size_max"],
-    size_corr_ell=cm["gal_size_corr_ell"],
-    sigma_eps=cm["sigma_eps_prior"],
-    global_R_weight=cm["global_R_weight"],
-    col_2d=False,
-    verbose=True,
-)
-
-# %%
-
-# Get metacal outputs; here mask is needed
-g_corr_mc, g_uncorr, w, mask_metacal, c, c_err = (
-    calibration.get_calibrated_m_c(gal_metacal)
-)
-
-# %%
-# Compute DES weights
-
-cat_gal = {}
-
-sp_joint.compute_weights_gatti(
-    cat_gal,
-    g_uncorr,
-    gal_metacal,
-    dat,
-    mask_combined,
-    mask_metacal,
-    num_bins=20,
-)
-
-# %%
-# Correct for PSF leakage
-
-alpha_1, alpha_2 = sp_joint.compute_PSF_leakage(
-    cat_gal,
-    g_corr_mc,
-    dat,
-    mask_combined,
-    mask_metacal,
-    num_bins=20,    
-)
-
-# Compute leakage-corrected ellipticities
-e1_leak_corrected = g_corr_mc[0] - alpha_1 * cat_gal["e1_PSF"]
-e2_leak_corrected = g_corr_mc[1] - alpha_2 * cat_gal["e2_PSF"]
-
-# %%
-# Get some memory back
-for mask in masks:
-    del mask
-    
-    
-# %%
-ra = cat.get_col(dat, "RA", mask_combined._mask, mask_metacal)
-dec = cat.get_col(dat, "Dec", mask_combined._mask, mask_metacal)
-
-    
-# %%
-# Correlation function
-import treecorr
+def get_combined_mask(config, dat, masks_to_apply, verbose=False):
+
+    # Gather mask information for above list from config
+    masks, labels = sp_joint.get_masks_from_config(
+        config,
+        dat,
+        dat,
+        masks_to_apply=masks_to_apply,
+        verbose=verbose,
+    )
+
+    # Initialise combined mask
+    label = "comb"
+    my_mask = sp_joint.Mask(label, label, kind="combined", value=None)
+
+    # Combine masks
+    mask_combined = sp_joint.Mask.from_list(
+        masks,
+        label="combined",
+        verbose=verbose,
+    )
+
+    if True or verbose:
+        # Output some mask statistics
+        sp_joint.print_mask_stats(dat.shape[0], masks, mask_combined)
+
+    return mask_combined
+
+# %%
+def xi_from_dat(dat, mask_combined, cm, config_treecorr, n_cpu):
+
+    # Call metacal
+    gal_metacal = metacal(
+        dat,
+        mask_combined._mask,
+        snr_min=cm["gal_snr_min"],
+        snr_max=cm["gal_snr_max"],
+        rel_size_min=cm["gal_rel_size_min"],
+        rel_size_max=cm["gal_rel_size_max"],
+        size_corr_ell=cm["gal_size_corr_ell"],
+        sigma_eps=cm["sigma_eps_prior"],
+        global_R_weight=cm["global_R_weight"],
+        col_2d=False,
+        verbose=True,
+    )
+
+    # Get metacal outputs; here mask is needed
+    g_corr_mc, g_uncorr, w, mask_metacal, c, c_err = (
+        calibration.get_calibrated_m_c(gal_metacal)
+    )
+
+    # Compute DES weights
+    cat_gal = {}
+
+    sp_joint.compute_weights_gatti(
+        cat_gal,
+        g_uncorr,
+        gal_metacal,
+        dat,
+        mask_combined,
+        mask_metacal,
+        num_bins=20,
+    )
+
+    # Correct for PSF leakage
+    alpha_1, alpha_2 = sp_joint.compute_PSF_leakage(
+        cat_gal,
+        g_corr_mc,
+        dat,
+        mask_combined,
+        mask_metacal,
+        num_bins=20,    
+    )
+
+    # Compute leakage-corrected ellipticities
+    e1_leak_corrected = g_corr_mc[0] - alpha_1 * cat_gal["e1_PSF"]
+    e2_leak_corrected = g_corr_mc[1] - alpha_2 * cat_gal["e2_PSF"]
+
+
+    ra = cat.get_col(dat, "RA", mask_combined._mask, mask_metacal)
+    dec = cat.get_col(dat, "Dec", mask_combined._mask, mask_metacal)
+
+    gg = treecorr.GGCorrelation(config_treecorr, var_method='jackknife')
+
+    npatch = 20
+    catalog = treecorr.Catalog(                                                         
+        ra=ra,                                               
+        dec=dec,                                                    
+        g1=e1_leak_corrected,                                                              
+        g2=e2_leak_corrected,                                                       
+        w=cat_gal["w_des"],                                                           
+        ra_units="deg",                                        
+        dec_units="deg",
+        npatch=npatch,                                
+    )
+
+    gg.process(catalog, catalog, num_threads=n_cpu)
+
+    return gg
+
+# %%
+# Set up correlation
 # %%
 minsep = 1
 maxsep = 50
 nbins = 10
-npatch = 20
 n_cpu = 24
-config = {
+config_treecorr = {
     "ra_units": "deg",
     "dec_units": "deg",
     "min_sep": minsep,
@@ -192,28 +168,44 @@
     "var_method": "jackknife",
     "bin_type": "Log",
 }
-gg = treecorr.GGCorrelation(config, var_method='jackknife')
+cm = config["metacal"]
 
-# %%
-catalog = treecorr.Catalog(                                                         
-    ra=ra,                                               
-    dec=dec,                                                    
-    g1=e1_leak_corrected,                                                              
-    g2=e2_leak_corrected,                                                       
-    w=cat_gal["w_des"],                                                           
-    ra_units="deg",                                        
-    dec_units="deg",
-    npatch=npatch,                                
-)
 
 # %%
-gg.process(catalog, catalog, num_threads=n_cpu)
+# Basic masking
+masks_to_apply = []
+
+masks_to_add = [
+    "4_Stars",
+    "1024_Maximask",
+    "N_EPOCH",
+    "2_Bright_star_halos",
+    "1_Faint_star_halos",
+    "npoint3",
+]
+
 # %%
-x = gg.rnom
-y = x * gg.xip
-dy = x * np.sqrt(gg.varxip)
-plt.errorbar(x, y, yerr=dy, marker="o", linestyle="")
-plt.xlabel(r"$\theta$ [arcmin]")
-plt.ylabel(r"$\theta \xi_+(\theta)$ [arcmin]")
-plt.show()
+# Main loop
+ggs = []
+for mask in masks_to_add:
+    
+    print(f"Adding mask {mask}...")
+    
+    masks_to_apply.append(mask)
+
+    # Get combined mask
+    mask_combined = get_combined_mask(
+        config,
+        dat,
+        masks_to_apply,
+        verbose=obj._params["verbose"],
+    )
+
+    # Compute xi_+ from data
+    print("Compute xi")
+    gg = xi_from_dat(dat, mask_combined, cm, config_treecorr, n_cpu)
+    
+    xi_out_name = f"xi_{mask}.txt"
+    gg.write(xi_out_name)
+    ggs.append(gg)
 # %%