Merge pull request #332 from david-castillo/master

Fix write_matrix only yielding diagonal

_pytadbit/modelling/structuralmodels.py

@@ -18,7 +18,7 @@
 from itertools                        import combinations
 from uuid                             import uuid5, UUID
 from hashlib                          import md5
-from copy                             import deepcopy
+from copy                             import deepcopy, copy
 
 from numpy                            import exp as np_exp
 from numpy                            import median as np_median
@@ -1644,7 +1644,7 @@ def zscore_plot(self, axe=None, savefig=None, do_normaltest=False):
             masked_array, mask=masked_array < self._config['upfreq'])
         masked_array_bot = ma.array (
             masked_array, mask=self._config['lowfreq'] < masked_array)
-        cmap = viridis
+        cmap = copy(viridis)
         cmap.set_bad('w', 1.)
         if not axe:
             fig = plt.figure(figsize=(25, 5.5))
@@ -1656,7 +1656,7 @@ def zscore_plot(self, axe=None, savefig=None, do_normaltest=False):
         ax.set_ylabel('Particles')
         ax.set_xlabel('Particles')
         ax.set_title('Z-scores of the normalized Hi-C count')
-        cbar = ax.figure.colorbar(ims, cmap=cmap)
+        cbar = ax.figure.colorbar(ims)
         cbar.ax.set_ylabel('Z-score value')
 
         ax = plt.axes([.38, 0.11, .28, .61])
@@ -1825,7 +1825,7 @@ def correlate_with_real_data(self, models=None, cluster=None, cutoff=None,
                      size='x-large')
         ax = fig.add_subplot(131)
         # imshow of the modeled data
-        cmap = plt.get_cmap('viridis')
+        cmap = copy(plt.get_cmap('viridis'))
         cmap.set_bad('darkgrey', 1)
         ims = ax.imshow(model_matrix, origin='lower', interpolation="nearest",
                          vmin=0, vmax=1, cmap=cmap,
@@ -1910,7 +1910,7 @@ def correlate_with_real_data(self, models=None, cluster=None, cutoff=None,
             # axmidl.patch.set_visible(False)
         ax.set_title('Real versus modelled data')
         ax = fig.add_subplot(133)
-        cmap = plt.get_cmap('viridis')
+        cmap = copy(plt.get_cmap('viridis'))
         cmap.set_bad('darkgrey', 1)
         with errstate(divide='ignore'):
             ims = ax.imshow(log2(self._original_data), origin='lower',

_pytadbit/parsers/hic_bam_parser.py

@@ -1188,32 +1188,18 @@ def get_bin_name(a, b):
     if 'raw&decay' in normalizations and not cooler:
         write = write_raw_and_expc(write)
 
-    # pull all sub-matrices and write full matrix
-    if region2 is not None:  # already half-matrix in this case
-        half_matrix = False
-
     if cooler:
         for ichunk, c, j, k, v in _iter_matrix_frags(chunks, tmpdir, rand_hash,
                                                      verbose=verbose, clean=clean,
                                                      include_chunk_count=True):
-            if j > k:
-                continue
             if j not in bads1 and k not in bads2:
                 out_raw.write_iter(ichunk, j, k, v)
         out_raw.close()
     else:
-        if half_matrix:
-            for c, j, k, v in _iter_matrix_frags(chunks, tmpdir, rand_hash,
-                                                 verbose=verbose, clean=clean):
-                if k > j:
-                    continue
-                if j not in bads1 and k not in bads2:
-                    write(c, j, k, v)
-        else:
-            for c, j, k, v in _iter_matrix_frags(chunks, tmpdir, rand_hash,
-                                                 verbose=verbose, clean=clean):
-                if j not in bads1 and k not in bads2:
-                    write(c, j, k, v)
+        for c, j, k, v in _iter_matrix_frags(chunks, tmpdir, rand_hash,
+                                             verbose=verbose, clean=clean):
+            if j not in bads1 and k not in bads2:
+                write(c, j, k, v)
 
     fnames = {}
     if append_to_tar:

_pytadbit/utils/extraviews.py

@@ -9,13 +9,17 @@
 from itertools  import product
 
 import numpy as np
+import copy
 from scipy      import interpolate
 
 try:
     from matplotlib.ticker    import MultipleLocator
     from matplotlib           import pyplot as plt
     from mpl_toolkits.mplot3d import Axes3D
     from matplotlib.ticker    import FuncFormatter
+
+    if "mpl_toolkits.legacy_colorbar" in plt.rcParams:
+        plt.rcParams["mpl_toolkits.legacy_colorbar"] = False
 except ImportError:
     warn('matplotlib not found\n')
 
@@ -717,7 +721,7 @@ def plot_2d_optimization_result(result,
     result = result.transpose(trans)
     # set NaNs
     result = np.ma.array(result, mask=np.isnan(result))
-    cmap = plt.get_cmap(cmap)
+    cmap = copy.copy(plt.get_cmap(cmap))
     cmap.set_bad('w', 1.)
 
     # defines axes
@@ -1314,7 +1318,7 @@ def plot_HiC_matrix(matrix, bad_color=None, triangular=False, axe=None,
        the second to the color bar
     """
     if bad_color is not None:
-        kwargs['cmap'] = plt.get_cmap(kwargs.get('cmap', None))
+        kwargs['cmap'] = copy.copy(plt.get_cmap(kwargs.get('cmap', None)))
         kwargs['cmap'].set_bad(bad_color, 1.)
 
     if not isinstance(matrix, (np.ndarray, np.generic)):