diff options
Diffstat (limited to 'Tools/PostProcessing/plot_distribution_mapping.py')
| -rw-r--r-- | Tools/PostProcessing/plot_distribution_mapping.py | 36 |
1 files changed, 22 insertions, 14 deletions
diff --git a/Tools/PostProcessing/plot_distribution_mapping.py b/Tools/PostProcessing/plot_distribution_mapping.py index 94d63e14e..7681abd0c 100644 --- a/Tools/PostProcessing/plot_distribution_mapping.py +++ b/Tools/PostProcessing/plot_distribution_mapping.py @@ -11,10 +11,11 @@ class SimData: """ Structure for easy access to load costs reduced diagnostics """ - def __init__(self, directory, prange): + def __init__(self, directory, prange, is_3D): """ Set data-containing dir, data range; load data """ + self.is_3D = is_3D self._get_costs_reduced_diagnostics(directory, prange) def __call__(self, i): @@ -69,19 +70,22 @@ class SimData: unique_headers=[''.join([l for l in w if not l.isdigit()]) for w in h.split()][2::] - # Either 7 or 8 depending if GPU - n_data_fields = 7 if (len(set(unique_headers)) - 2)%7 == 0 else 8 + # Either 9 or 10 depending if GPU + n_data_fields = 9 if len(set(unique_headers))%9 == 0 else 10 f.close() # From data header, data layout is: # [step, time, # cost_box_0, proc_box_0, lev_box_0, i_low_box_0, j_low_box_0, - # k_low_box_0(, gpu_ID_box_0 if GPU run), hostname_box_0 + # k_low_box_0, num_cells_0, num_macro_particles_0, + # (, gpu_ID_box_0 if GPU run), hostname_box_0, # cost_box_1, proc_box_1, lev_box_1, i_low_box_1, j_low_box_1, - # k_low_box_1(, gpu_ID_box_1 if GPU run), hostname_box_1 + # k_low_box_1, num_cells_1, num_macro_particles_1, + # (, gpu_ID_box_1 if GPU run), hostname_box_1 # ... # cost_box_n, proc_box_n, lev_box_n, i_low_box_n, j_low_box_n, - # k_low_box_n(, gpu_ID_box_n if GPU run), hostname_box_n + # k_low_box_n, num_cells_n, num_macro_particles_n, + # (, gpu_ID_box_n if GPU run), hostname_box_n i, j, k = (data[0,3::n_data_fields], data[0,4::n_data_fields], data[0,5::n_data_fields]) @@ -90,9 +94,14 @@ class SimData: j_blocks = np.diff(np.array(sorted(j.astype(int)))) k_blocks = np.diff(np.array(sorted(k.astype(int)))) - i_blocking_factor = i_blocks[i_blocks != 0].min() - j_blocking_factor = j_blocks[j_blocks != 0].min() - k_blocking_factor = k_blocks[k_blocks != 0].min() + i_non_zero = i_blocks[i_blocks != 0] + j_non_zero = j_blocks[j_blocks != 0] + k_non_zero = k_blocks[k_blocks != 0] + + # only one block in a dir - or smalles block size + i_blocking_factor = 1 if len(i_non_zero) == 0 else i_non_zero.min() + j_blocking_factor = 1 if len(j_non_zero) == 0 else j_non_zero.min() + k_blocking_factor = 1 if len(k_non_zero) == 0 else k_non_zero.min() imax = i.astype(int).max()//i_blocking_factor jmax = j.astype(int).max()//j_blocking_factor @@ -102,8 +111,6 @@ class SimData: j_is_int = all([el.is_integer() for el in j/j_blocking_factor]) k_is_int = all([el.is_integer() for el in k/k_blocking_factor]) - is_3D = i_is_int and j_is_int and k_is_int - for key in self.keys: row = np.where(key == steps)[0][0] costs = data[row, 0::n_data_fields].astype(float) @@ -113,8 +120,8 @@ class SimData: kcoords = k.astype(int)//k_blocking_factor # Fill in cost array - shape = (kmax+1, jmax+1, imax+1)[:2+is_3D] - coords = [coord[:2+is_3D] for coord in zip(kcoords, jcoords, icoords)] + shape = (kmax+1, jmax+1, imax+1)[:2+self.is_3D] + coords = [coord[:2+self.is_3D] for coord in zip(kcoords, jcoords, icoords)] cost_arr = np.full(shape, 0.0) rank_arr = np.full(shape, -1) @@ -131,7 +138,7 @@ class SimData: edges = list(rank_arr[corner[0]:pos[0]+1, pos[1], pos[2]]) \ + list(rank_arr[pos[0], corner[1]:pos[1]+1, pos[2]]) \ + list(rank_arr[pos[0], pos[1], corner[2]:pos[2]+1]) \ - if is_3D else \ + if self.is_3D else \ list(rank_arr[corner[0]:pos[0]+1, pos[1]]) \ + list(rank_arr[pos[0], corner[1]:pos[1]+1]) if visited[pos] or not set(edges).issubset(set([prev, -1])): return @@ -163,3 +170,4 @@ class SimData: self.data_fields[key]['lb_efficiency_min'] = efficiencies.min() self.data_fields[key]['t'] = times[row] self.data_fields[key]['step'] = steps[row] + # ... |