PDF report for 4D niimage

nilearn_sandbox/plotting/pdf_plotting.py

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+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.backends.backend_pdf import PdfPages
+from nilearn.plotting import plot_stat_map, plot_prob_atlas
+from nilearn._utils import check_niimg_4d
+from nilearn.image import index_img
+
+
+def plot_to_pdf(img, path='output.pdf', vmax=None):
+    """Creates a pdf from a 4D nii-image like
+
+    Parameters
+    ----------
+    img: nii-like image,
+        Image to dump as pdf
+
+    path: str,
+        Path of the output pdf
+
+    vmax: float or 'auto' or None,
+        vmax to use in plot_stat_map. 'auto' will compute it magically
+    """
+    a4_size = (8.27, 11.69)
+    img = check_niimg_4d(img)
+    n_components = img.shape[3]
+
+    if vmax == 'auto':
+        vmax = np.max(np.abs(img.get_data()), axis=3)
+        vmax[vmax >= 0.1] = 0
+        vmax = np.max(vmax)
+    elif vmax is not None:
+        vmax = float(vmax)
+    with PdfPages(path) as pdf:
+        for i in range(-1, n_components, 5):
+            fig, axes = plt.subplots(5, 1, figsize=a4_size, squeeze=False)
+            axes = axes.reshape(-1)
+            for j, ax in enumerate(axes):
+                if i + j < 0:
+                    plot_prob_atlas(img, axes=ax)
+                elif j + i < n_components:
+                    plot_stat_map(index_img(img, j + i), axes=ax, vmax=vmax)
+                else:
+                    ax.axis('off')
+            pdf.savefig(fig)
+            plt.close()

nilearn_sandbox/plotting/tests/test_pdf_plotting.py

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+import os
+from nose.tools import assert_true
+from nilearn.datasets import fetch_atlas_smith_2009
+from nilearn_sandbox.plotting.pdf_plotting import plot_to_pdf
+from tempfile import mkdtemp
+from os.path import join
+
+def test_plot_to_pdf():
+    # Smoke test pdf plotting
+    smith = fetch_atlas_smith_2009()
+    img = smith.rsn10
+    temp_dir = mkdtemp()
+    file_path = join(temp_dir, 'output.pdf')
+    plot_to_pdf(img, path=file_path)
+    assert_true(os.path.exists(file_path))
+    os.remove('output.pdf')
+    os.rmdir(temp_dir)