Author: bugman
Date: Wed Apr 10 17:29:36 2013
New Revision: 19434
URL: http://svn.gna.org/viewcvs/relax?rev=19434&view=rev
Log:
Created the pipe_control.plotting.assemble_data_seq_series() function.
This is to allow the residue or spin numbering to be plotted against any
series type data (lists or
dictionaries), or vice versa.
Modified:
trunk/pipe_control/plotting.py
Modified: trunk/pipe_control/plotting.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/pipe_control/plotting.py?rev=19434&r1=19433&r2=19434&view=diff
==============================================================================
--- trunk/pipe_control/plotting.py (original)
+++ trunk/pipe_control/plotting.py Wed Apr 10 17:29:36 2013
@@ -64,6 +64,8 @@
data, set_labels, x_err_flag, y_err_flag =
assemble_data_seq_value(x_data_name=x_data_name, y_data_name=y_data_name,
plot_data=plot_data)
elif graph_type == 'value-value':
data, set_labels, x_err_flag, y_err_flag =
assemble_data_scatter(x_data_name=x_data_name, y_data_name=y_data_name,
plot_data=plot_data)
+ elif graph_type == 'seq-series':
+ data, set_labels, x_err_flag, y_err_flag =
assemble_data_seq_series(x_data_name=x_data_name, y_data_name=y_data_name,
plot_data=plot_data, x_type=x_type, y_type=y_type)
elif graph_type == 'series-series':
data, set_labels, x_err_flag, y_err_flag =
assemble_data_series_series(x_data_name=x_data_name, y_data_name=y_data_name,
plot_data=plot_data, x_type=x_type, y_type=y_type)
else:
@@ -100,6 +102,132 @@
# Default to the assemble_data_seq_value() function, as the graphs are
currently not constructed differently.
return assemble_data_seq_value(x_data_name=x_data_name,
y_data_name=y_data_name, plot_data=plot_data)
+
+
+def assemble_data_seq_series(spin_id=None, x_data_name=None,
y_data_name=None, plot_data='value', x_type=None, y_type=None):
+ """Assemble the graph data for residue or spin sequence verses verses
list or dictionary data.
+
+ For such data, one graph will be produced. There will be one data set
in this graph per series.
+
+
+ @keyword spin_id: The spin ID string for restricting the graph to.
+ @type spin_id: str
+ @keyword x_data_name: The name of the X-data or variable to plot.
+ @type x_data_name: str
+ @keyword y_data_name: The name of the Y-data or variable to plot.
+ @type y_data_name: str
+ @keyword plot_data: The type of the plotted data, one of 'value',
'error', or 'sim'.
+ @type plot_data: str
+ @keyword x_type: The type of X-data to plot.
+ @type x_type: type object
+ @keyword y_type: The type of Y-data to plot.
+ @type y_type: type object
+ @return: The graph data, set labels, and flags for errors
in the X and Y dimensions.
+ @rtype: list of lists of lists of numbers, list of str,
bool, bool
+ """
+
+ # Initialise some data structures.
+ data = [[]]
+ set_labels = []
+ x_err_flag = False
+ y_err_flag = False
+
+ # The sequence and series axes.
+ if x_data_name in ['res_num', 'spin_num']:
+ seq_axis = 'x'
+ series_type = y_type
+ else:
+ seq_axis = 'y'
+ series_type = x_type
+
+ # Determine the number of sets.
+ for spin, mol_name, res_num, res_name, id in spin_loop(full_info=True,
selection=spin_id, return_id=True, skip_desel=True):
+ # Fetch the series data (ignore simulations).
+ if seq_axis == 'x':
+ val, err = fetch_1D_data(plot_data=plot_data,
data_name=y_data_name, spin=spin, res_num=res_num)
+ else:
+ val, err = fetch_1D_data(plot_data=plot_data,
data_name=x_data_name, spin=spin, res_num=res_num)
+
+ # The keys.
+ if series_type == dict:
+ keys = list(val.keys())
+
+ # Loop over the series data.
+ for j in range(len(val)):
+ # The index or key for the data.
+ if series_type == list:
+ elem = j
+ else:
+ elem = keys[j]
+
+ # Add the set info if new.
+ if elem not in set_labels:
+ data[0].append([])
+ set_labels.append(elem)
+
+ # Sort the set labels.
+ set_labels.sort()
+
+ # Number of data points per spin.
+ if plot_data == 'sim':
+ points = cdp.sim_number
+ else:
+ points = 1
+
+ # Loop over the spins.
+ spin_index = 0
+ for spin, mol_name, res_num, res_name, id in spin_loop(full_info=True,
selection=spin_id, return_id=True, skip_desel=True):
+ # Loop over the data points (for simulations).
+ for i in range(points):
+ # The X and Y data.
+ x_val, x_err = fetch_1D_data(plot_data=plot_data,
data_name=x_data_name, spin=spin, res_num=res_num, sim_num=i)
+ y_val, y_err = fetch_1D_data(plot_data=plot_data,
data_name=y_data_name, spin=spin, res_num=res_num, sim_num=i)
+
+ # Alias the data.
+ if seq_axis == 'x':
+ series_val = y_val
+ else:
+ series_val = x_val
+
+ # Go to the next spin if there is missing xy data.
+ if x_val == None or y_val == None:
+ continue
+
+ # The error flags.
+ if x_err != None:
+ x_err_flag = True
+ if y_err != None:
+ y_err_flag = True
+
+ # The keys.
+ if series_type == dict:
+ keys = list(series_val.keys())
+
+ # Loop over the series data.
+ for j in range(len(series_val)):
+ # The index or key for the data.
+ if series_type == list:
+ index = set_labels.index(j)
+ elem = index
+ else:
+ index = set_labels.index(keys[j])
+ elem = set_labels[set_labels.index(keys[j])]
+
+ # Append the data.
+ if seq_axis == 'x':
+ data[0][index].append([x_val, y_val[elem]])
+ else:
+ data[0][index].append([x_val[elem], y_val])
+ if x_err_flag:
+ data[0][index][-1].append(x_err[elem])
+ if y_err_flag:
+ data[0][index][-1].append(y_err[elem])
+
+ # Increment the spin index.
+ spin_index += 1
+
+ # Return the data.
+ return data, set_labels, x_err_flag, y_err_flag
def assemble_data_seq_value(spin_id=None, x_data_name=None,
y_data_name=None, plot_data='value'):
r19434 - /trunk/pipe_control/plotting.py