Merge pull request #202 from kaeldai/release/v1.0.3

Release/v1.0.3

bmtk/__init__.py

@@ -20,4 +20,4 @@
 # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 #
-__version__ = '1.0.2'
+__version__ = '1.0.3'

bmtk/analyzer/compartment.py

@@ -65,7 +65,7 @@ def _find_nodes(population, config=None, nodes_file=None, node_types_file=None):
 def plot_traces(config_file=None, report_name=None, population=None, report_path=None, group_by=None,
                 group_excludes=None, nodes_file=None, node_types_file=None,
                 node_ids=None, sections='origin', average=False, times=None, title=None,
-                show_legend=None, show=True):
+                show_legend=None, show=True, save_as=None):
     """Plot compartment variables (eg Membrane Voltage, Calcium conc.) traces from the output of simulation. Will
     attempt to look in the SONATA simulation configuration json "reports" sections for any matching "membrane_report"
     outputs with a matching report_name::
@@ -115,6 +115,8 @@ def plot_traces(config_file=None, report_name=None, population=None, report_path
     :param show_legend: Set True or False to determine if legend should be displayed on the plot. The default (None)
            function itself will guess if legend should be shown.
     :param show: bool to display or not display plot. default True.
+    :param save_as: None or str: file-name/path to save the plot as a png/jpeg/etc. If None or empty string will not
+        save plot.
     :return: matplotlib figure.Figure object
     """
 
@@ -176,5 +178,6 @@ def plot_traces(config_file=None, report_name=None, population=None, report_path
         times=times,
         title=title,
         show_legend=show_legend,
-        show=show
+        show=show,
+        save_as=save_as
     )

bmtk/analyzer/spike_trains.py

@@ -94,7 +94,7 @@ def _find_nodes(population, config=None, nodes_file=None, node_types_file=None):
     raise ValueError('Could not find nodes file with node population "{}".'.format(population))
 
 
-def _plot_helper(plot_fnc, config_file=None, population=None, times=None, title=None, show=True,
+def _plot_helper(plot_fnc, config_file=None, population=None, times=None, title=None, show=True, save_as=None,
                  group_by=None, group_excludes=None,
                  spikes_file=None, nodes_file=None, node_types_file=None):
     sonata_config = SonataConfig.from_json(config_file) if config_file else None
@@ -136,11 +136,14 @@ def _plot_helper(plot_fnc, config_file=None, population=None, times=None, title=
     else:
         node_groups = None
 
-    return plot_fnc(spike_trains=spike_trains, node_groups=node_groups, population=pop, times=times, title=title, show=show)
+    return plot_fnc(
+        spike_trains=spike_trains, node_groups=node_groups, population=pop, times=times, title=title, show=show,
+        save_as=save_as
+    )
 
 
 def plot_raster(config_file=None, population=None, with_histogram=True, times=None, title=None, show=True,
-                group_by=None, group_excludes=None,
+                save_as=None, group_by=None, group_excludes=None,
                 spikes_file=None, nodes_file=None, node_types_file=None):
     """Create a raster plot (plus optional histogram) from the results of the simulation.
 
@@ -170,6 +173,8 @@ def plot_raster(config_file=None, population=None, with_histogram=True, times=No
     :param title: str, adds a title to the plot. If None (default) then name will be automatically generated using the
         report_name.
     :param show: bool to display or not display plot. default True.
+    :param save_as: None or str: file-name/path to save the plot as a png/jpeg/etc. If None or empty string will not
+        save plot.
     :param group_by: Attribute of the "nodes" file used to group and average subsets of nodes.
     :param group_excludes: list of strings or None. When using the "group_by", allows users to exclude certain groupings
         based on the attribute value.
@@ -181,15 +186,17 @@ def plot_raster(config_file=None, population=None, with_histogram=True, times=No
     :return: matplotlib figure.Figure object
     """
     plot_fnc = partial(plotting.plot_raster, with_histogram=with_histogram)
-    return _plot_helper(plot_fnc,
-                        config_file=config_file, population=population, times=times, title=title, show=show,
-                        group_by=group_by, group_excludes=group_excludes,
-                        spikes_file=spikes_file, nodes_file=nodes_file, node_types_file=node_types_file
+    return _plot_helper(
+        plot_fnc,
+        config_file=config_file, population=population, times=times, title=title, show=show, save_as=save_as,
+        group_by=group_by, group_excludes=group_excludes,
+        spikes_file=spikes_file, nodes_file=nodes_file, node_types_file=node_types_file
     )
 
 
 def plot_rates(config_file=None, population=None, smoothing=False, smoothing_params=None, times=None, title=None,
-               show=True, group_by=None, group_excludes=None, spikes_file=None, nodes_file=None, node_types_file=None):
+               show=True, save_as=None, group_by=None, group_excludes=None, spikes_file=None, nodes_file=None,
+               node_types_file=None):
     """Calculate and plot the rates of each node recorded during the simulation - averaged across the entirety of the
     simulation.
 
@@ -221,6 +228,8 @@ def plot_rates(config_file=None, population=None, smoothing=False, smoothing_par
     :param title: str, adds a title to the plot. If None (default) then name will be automatically generated using the
         report_name.
     :param show: bool to display or not display plot. default True.
+    :param save_as: None or str: file-name/path to save the plot as a png/jpeg/etc. If None or empty string will not
+        save plot.
     :param group_by: Attribute of the "nodes" file used to group and average subsets of nodes.
     :param group_excludes: list of strings or None. When using the "group_by", allows users to exclude certain groupings
         based on the attribute value.
@@ -232,14 +241,15 @@ def plot_rates(config_file=None, population=None, smoothing=False, smoothing_par
     :return: matplotlib figure.Figure object
     """
     plot_fnc = partial(plotting.plot_rates, smoothing=smoothing, smoothing_params=smoothing_params)
-    return _plot_helper(plot_fnc,
-                        config_file=config_file, population=population, times=times, title=title, show=show,
-                        group_by=group_by, group_excludes=group_excludes,
-                        spikes_file=spikes_file, nodes_file=nodes_file, node_types_file=node_types_file
+    return _plot_helper(
+        plot_fnc,
+        config_file=config_file, population=population, times=times, title=title, show=show, save_as=save_as,
+        group_by=group_by, group_excludes=group_excludes,
+        spikes_file=spikes_file, nodes_file=nodes_file, node_types_file=node_types_file
     )
 
 
-def plot_rates_boxplot(config_file=None, population=None, times=None, title=None, show=True,
+def plot_rates_boxplot(config_file=None, population=None, times=None, title=None, show=True, save_as=None,
                        group_by=None, group_excludes=None,
                        spikes_file=None, nodes_file=None, node_types_file=None):
     """Creates a box plot of the firing rates taken from nodes recorded during the simulation.
@@ -268,6 +278,8 @@ def plot_rates_boxplot(config_file=None, population=None, times=None, title=None
     :param title: str, adds a title to the plot. If None (default) then name will be automatically generated using the
         report_name.
     :param show: bool to display or not display plot. default True.
+    :param save_as: None or str: file-name/path to save the plot as a png/jpeg/etc. If None or empty string will not
+        save plot.
     :param group_by: Attribute of the "nodes" file used to group and average subsets of nodes.
     :param group_excludes: list of strings or None. When using the "group_by", allows users to exclude certain groupings
         based on the attribute value.
@@ -279,8 +291,9 @@ def plot_rates_boxplot(config_file=None, population=None, times=None, title=None
     :return: matplotlib figure.Figure object
     """
     plot_fnc = partial(plotting.plot_rates_boxplot)
-    return _plot_helper(plot_fnc,
-        config_file=config_file, population=population, times=times, title=title, show=show,
+    return _plot_helper(
+        plot_fnc,
+        config_file=config_file, population=population, times=times, title=title, show=show, save_as=save_as,
         group_by=group_by, group_excludes=group_excludes,
         spikes_file=spikes_file, nodes_file=nodes_file, node_types_file=node_types_file
     )
@@ -344,8 +357,6 @@ def to_dataframe(config_file, spikes_file=None, population=None):
     :param population:
     :return:
     """
-
-
     # _, spike_trains = _find_spikes(config_file=config_file, spikes_file=spikes_file, population=population)
     pop, spike_trains = _find_spikes(config_file=config_file, spikes_file=spikes_file, population=population)
 

bmtk/simulator/bionet/modules/xstim.py

@@ -26,8 +26,8 @@ def __init__(self, positions_file, waveform, mesh_files_dir=None, cells=None, se
         self._local_gids = []
         self._fih = None
 
-    #def __set_extracellular_mechanism(self):
-    #    for gid in self._local_gids:
+    # def __set_extracellular_mechanism(self):
+    #     for gid in self._local_gids:
 
     def initialize(self, sim):
         if self._cells is None:
@@ -47,7 +47,7 @@ def initialize(self, sim):
         def set_pointers():
             for gid in self._local_gids:
                 cell = sim.net.get_cell_gid(gid)
-                #cell = sim.net.get_local_cell(gid)
+                # cell = sim.net.get_local_cell(gid)
                 cell.set_ptr2e_extracellular()
 
         self._fih = sim.h.FInitializeHandler(0, set_pointers)
@@ -72,7 +72,10 @@ def __init__(self, positions_file, waveform, mesh_files_dir, dt):
 
         stimelectrode_position_df = pd.read_csv(positions_file, sep=' ')
 
-        self.elmesh_files = stimelectrode_position_df['electrode_mesh_file']
+        if 'electrode_mesh_file' in stimelectrode_position_df.columns:
+            self.elmesh_files = stimelectrode_position_df['electrode_mesh_file']
+        else:
+            self.elmesh_files = None
         self.elpos = stimelectrode_position_df[['pos_x', 'pos_y', 'pos_z']].T.values
         self.elrot = stimelectrode_position_df[['rotation_x', 'rotation_y', 'rotation_z']].values
         self.elnsites = self.elpos.shape[1]  # Number of electrodes in electrode file
@@ -88,23 +91,30 @@ def __init__(self, positions_file, waveform, mesh_files_dir, dt):
         self.place_the_electrodes()
 
     def read_electrode_mesh(self):
-        el_counter = 0
-        for mesh_file in self.elmesh_files:
-            file_path = mesh_file if os.path.isabs(mesh_file) else os.path.join(self._mesh_files_dir, mesh_file)
-            mesh = pd.read_csv(file_path, sep=" ")
-            mesh_size = mesh.shape[0]
-            self.el_mesh_size.append(mesh_size)
-
-            self.el_mesh[el_counter] = np.zeros((3, mesh_size))
-            self.el_mesh[el_counter][0] = mesh['x_pos']
-            self.el_mesh[el_counter][1] = mesh['y_pos']
-            self.el_mesh[el_counter][2] = mesh['z_pos']
-            el_counter += 1
+        if self.elmesh_files is None:
+            # if electrode_mesh_file is missing then we still treat the electrode as a mesh on a grid of size 1 with
+            # single point at the (0, 0, 0) relative to electrode position
+            for el_counter in range(self.elnsites):
+                self.el_mesh_size.append(1)
+                self.el_mesh[el_counter] = np.zeros((3, 1))
 
-    def place_the_electrodes(self):
+        else:
+            # Each electrode has an associate mesh file
+            el_counter = 0
+            for mesh_file in self.elmesh_files:
+                file_path = mesh_file if os.path.isabs(mesh_file) else os.path.join(self._mesh_files_dir, mesh_file)
+                mesh = pd.read_csv(file_path, sep=" ")
+                mesh_size = mesh.shape[0]
+                self.el_mesh_size.append(mesh_size)
+
+                self.el_mesh[el_counter] = np.zeros((3, mesh_size))
+                self.el_mesh[el_counter][0] = mesh['x_pos']
+                self.el_mesh[el_counter][1] = mesh['y_pos']
+                self.el_mesh[el_counter][2] = mesh['z_pos']
+                el_counter += 1
 
+    def place_the_electrodes(self):
         transfer_vector = np.zeros((self.elnsites, 3))
-
         for el in range(self.elnsites):
             mesh_mean = np.mean(self.el_mesh[el], axis=1)
             transfer_vector[el] = self.elpos[:, el] - mesh_mean[:]
@@ -128,17 +138,13 @@ def rotate_the_electrodes(self):
             self.el_mesh[el] = new_mesh
 
     def set_transfer_resistance(self, gid, seg_coords):
-
         rho = 300.0  # ohm cm
         r05 = seg_coords['p05']
         nseg = r05.shape[1]
         cell_map = np.zeros((self.elnsites, nseg))
         for el in six.moves.range(self.elnsites):
-
             mesh_size = self.el_mesh_size[el]
-
             for k in range(mesh_size):
-
                 rel = np.expand_dims(self.el_mesh[el][:, k], axis=1)
                 rel_05 = rel - r05
                 r2 = np.einsum('ij,ij->j', rel_05, rel_05)

bmtk/utils/reports/compartment/plotting.py

@@ -43,7 +43,7 @@ def __get_node_groups(report, node_groups, population):
 
 
 def plot_traces(report, population=None, node_ids=None, sections='origin', average=False, node_groups=None, times=None,
-                title=None, show_legend=None, show=True):
+                title=None, show_legend=None, show=True, save_as=None):
     """Displays the time trace of one or more nodes from a SONATA CompartmentReport file.
 
     To plot a group of individual variable traces (based on their soma)::
@@ -79,6 +79,8 @@ def plot_traces(report, population=None, node_ids=None, sections='origin', avera
     :param show_legend: Set True or False to determine if legend should be displayed on the plot. The default (None)
            function itself will guess if legend should be shown.
     :param show: bool to display or not display plot. default True.
+    :param save_as: None or str: file-name/path to save the plot as a png/jpeg/etc. If None or empty string will not
+        save plot.
     :return: matplotlib figure.Figure object
     """
     if node_groups is not None and node_ids is not None:
@@ -89,26 +91,26 @@ def plot_traces(report, population=None, node_ids=None, sections='origin', avera
             node_groups = {'node_ids': node_ids, 'label': average}
             return plot_traces_averaged(report=report, population=population, sections=sections,
                                         node_groups=node_groups, times=times, title=title, show_legend=show_legend,
-                                        show=show)
+                                        show=show, save_as=save_as)
 
         return plot_traces_individual(report=report, population=population, node_ids=node_ids, sections=sections,
-                                      times=times, title=title, show_legend=show_legend, show=show)
+                                      times=times, title=title, show_legend=show_legend, show=show, save_as=save_as)
 
     elif node_groups is not None:
         return plot_traces_averaged(report=report, population=population, sections=sections, node_groups=node_groups,
-                                    times=times, title=title, show_legend=show_legend, show=show)
+                                    times=times, title=title, show_legend=show_legend, show=show, save_as=save_as)
 
     elif average is not None:
         return plot_traces_averaged(report=report, population=population, sections=sections, times=times, title=title,
-                                    show_legend=show_legend, show=show)
+                                    show_legend=show_legend, show=show, save_as=save_as)
 
     else:
         return plot_traces_individual(report=report, population=population, sections=sections, times=times, title=title,
-                                      show_legend=show_legend, show=show)
+                                      show_legend=show_legend, show=show, save_as=save_as)
 
 
 def plot_traces_individual(report, population=None, node_ids=None, sections='origin', times=None, title=None,
-                show_legend=None, show=True):
+                           show_legend=None, show=True, save_as=None):
     """Used the plot time traces of individual nodes from a SONATA compartment report file.
 
     Recommended use plot_traces instead, which will call this function if necessarcy.
@@ -124,6 +126,8 @@ def plot_traces_individual(report, population=None, node_ids=None, sections='ori
     :param show_legend: Set True or False to determine if legend should be displayed on the plot. The default (None)
            function itself will guess if legend should be shown.
     :param show: bool to display or not display plot. default True.
+    :param save_as: None or str: file-name/path to save the plot as a png/jpeg/etc. If None or empty string will not
+        save plot.
     :return: matplotlib figure.Figure object
     """
 
@@ -157,14 +161,17 @@ def plot_traces_individual(report, population=None, node_ids=None, sections='ori
     if title:
         axes.set_title(title)
 
+    if save_as:
+        plt.savefig(save_as)
+
     if show:
         plt.show()
 
     return fig
 
 
 def plot_traces_averaged(report, population=None, sections='origin', node_groups=None, times=None, title=None,
-                         show_background=True, show_legend=None, show=True):
+                         show_background=True, show_legend=None, show=True, save_as=None):
     """Used to plot averages across multiple nodes in a SONATA Compartment Report file.
 
     Recommended that you use "plot_traces" function.
@@ -192,6 +199,8 @@ def plot_traces_averaged(report, population=None, sections='origin', node_groups
     :param show_legend: Set True or False to determine if legend should be displayed on the plot. The default (None)
            function itself will guess if legend should be shown.
     :param show: bool to display or not display plot. default True.
+    :param save_as: None or str: file-name/path to save the plot as a png/jpeg/etc. If None or empty string will not
+        save plot.
     :return: matplotlib figure.Figure object
     """
     cr = CompartmentReport.load(report)
@@ -220,7 +229,6 @@ def plot_traces_averaged(report, population=None, sections='origin', node_groups
         background_data = traces_data[:, nodes_indx]
         axes.plot(trace_times, background_data, c='lightgray')
 
-
     for node_grp in node_groups:
         grp_ids = node_grp.pop('node_ids')
         has_labels = has_labels or 'label' in node_grp
@@ -248,6 +256,9 @@ def plot_traces_averaged(report, population=None, sections='origin', node_groups
     if (show_legend is None or show_legend) and has_labels:
         axes.legend()
 
+    if save_as:
+        plt.savefig(save_as)
+
     if show:
         plt.show()