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191
db/tables.py
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191
db/tables.py
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# $Id: tables.py,v 1.1 2011-10-06 19:14:47 wirawan Exp $
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#
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# wpylib.db.tables module
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# Created: 20100223
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# Wirawan Purwanto
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#
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"""Simple table accessors for sqlite database."""
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import sys
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import os
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import os.path
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import time
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try:
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import sqlite3
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except:
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# For Python < 2.5:
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import pysqlite2.dbapi2 as sqlite3
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# dtype map from python types to sqlite3 types:
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dtype_map = {
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str: 'TEXT',
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int: 'INTEGER',
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float: 'REAL',
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}
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#
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simple_row_type = None # returns tuple
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indexable_row_type = sqlite3.Row
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class simple_table(object):
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"""Simple table with no primary key."""
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dtypes_default = []
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def __init__(self, src_name, table_name, dtypes=None):
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self.src_name = src_name
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self.table_name = table_name
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if isinstance(src_name, str): # os.path.isfile(src_name):
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self.db = sqlite3.connect(src_name)
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self.dbc = self.db.cursor()
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elif isinstance(src_name, sqlite3.Connection):
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self.src_name = None
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self.db = src_name
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self.dbc = self.db.cursor()
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else:
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raise ValueError, "Invalid src_name data type"
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self.db.text_factory = str
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self.sql_params = {
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'table_name': table_name,
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}
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self.debug = 1
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create_sql = """\
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CREATE TABLE IF NOT EXISTS '%(table_name)s' (
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""" \
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+ ", ".join(["'%s' %s" % (dname, self.sqlite_dtype_map[dtyp])
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for (dname,dtyp) in self.dtypes_default + list(dtypes)
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]) \
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+ """
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);
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"""
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self.exec_sql(create_sql)
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self.db.commit()
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def exec_sql(self, stmt, params=None):
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sql_stmt = stmt % self.sql_params
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if params:
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if self.debug:
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print "--SQL::", sql_stmt.rstrip()
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print "--val::", params
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return self.dbc.execute(sql_stmt, params)
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else:
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if self.debug:
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print "--SQL::", sql_stmt.rstrip()
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return self.dbc.execute(sql_stmt)
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def add_fields(self, dtypes):
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"""Adds columns to the table."""
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for (dname, dtyp) in dtypes:
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self.exec_sql("ALTER TABLE '%(table_name)s' ADD COLUMN" \
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+ " '%s' %s;" % (dname, self.sqlite_dtype_map[dtyp])
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)
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self.db.commit()
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def register_file(self, filename, replace=False, extra_values=None):
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"""Register a file, note its mtime, and size, and digests its content."""
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filestats = get_file_stats(filename)
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fields = [
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('md5sum', filestats['md5sum']),
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('date', filestats['mdate']),
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('time', filestats['mtime']),
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('size', filestats['size']),
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] + [
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kwpair for kwpair in extra_values
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]
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dnames = [ dname for (dname,dval) in fields ]
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dvals = [ dval for (dname,dval) in fields ]
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if replace:
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# Test if we want to replace or to add.
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count = [
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x for x in self.exec_sql(
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"SELECT count(*) from '%(table_name)s' where filename = ?;",
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(filename,)
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)
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][0][0]
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if count == 0: replace = False
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if replace:
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# WARNING: This will replace all the occurences of the entry with
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# the same filename.
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# Replaceable insert is not intended for tables with duplicate entries
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# of the same filename.
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insert_sql = "UPDATE '%(table_name)s' SET " \
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+ ', '.join(["'%s' = ?" % d for d in dnames]) \
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+ " WHERE filename = ?;"
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vals = tuple(dvals + [filename])
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else:
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insert_sql = "INSERT INTO '%(table_name)s' (filename, " \
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+ ", ".join(["'%s'" % d for d in dnames]) \
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+ ") VALUES (?" + ',?'*(len(fields)) + ");"
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vals = tuple([filename] + dvals)
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self.exec_sql(insert_sql, vals)
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def flush(self):
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self.db.commit()
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def get_filenames(self):
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"""Reads all the file names in the table to memory."""
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return [
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rslt[0] for rslt in
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self.exec_sql("SELECT filename FROM '%(table_name)s' ORDER BY filename;")
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]
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def __getitem__(self, **criteria):
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# Criteria could be SQL stmt
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"""Reads all the entries matching in the `filename' field."""
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if filename.find("%") >= 0:
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sql_stmt = "SELECT * FROM '%(table_name)s' WHERE filename LIKE ?;"
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else:
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sql_stmt = "SELECT * FROM '%(table_name)s' WHERE filename = ?;"
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return [ rslt for rslt in self.exec_sql(sql_stmt, (filename,)) ]
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def __setitem__(self, filename, newdata):
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"""Updates the metadata on the filename. Any other field than the filename
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can be updated. The filename serves as a unique key here.
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The newdata can be a hash, like this:
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A_file_table[filename] = {'date': 20041201, 'time': 122144}
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or a list of tuples:
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A_file_table[filename] = [('date': 20041201), ('time': 122144)]
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"""
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if isinstance(newdata, dict) or "keys" in dir(newdata):
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dnames = newdata.keys()
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dvals = [ newdata[k] for k in dnames ]
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else:
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# Assuming an iterable with ('field', 'value') tuples.
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dnames = [ dname for (dname,dval) in newdata ]
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dvals = [ dval for (dname,dval) in newdata ]
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update_sql = "UPDATE '%(table_name)s' SET " \
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+ ', '.join(["'%s' = ?" % d for d in dnames]) \
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+ " WHERE filename = ?;"
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vals = tuple(dvals + [filename])
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self.exec_sql(update_sql, vals)
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def __contains__(self, filename):
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"""Counts the number of record entries matching in the `filename' field."""
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if filename.find("%") >= 0:
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sql_stmt = "SELECT count(*) FROM '%(table_name)s' WHERE filename LIKE ?;"
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else:
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sql_stmt = "SELECT count(*) FROM '%(table_name)s' WHERE filename = ?;"
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return [ rslt for rslt in self.exec_sql(sql_stmt, (filename,)) ][0][0]
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count = __contains__
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def fields(self):
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"""Returns the field names of the table of the latest query."""
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return [ z[0] for z in self.dbc.description ]
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def row_kind(self, kind=None):
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if kind:
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self.db.row_factory = kind
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# We will reload the cursor to account for the new factory
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self.dbc = self.db.cursor()
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return self.db.row_factory
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55
math/fft.py
55
math/fft.py
@@ -1,4 +1,4 @@
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# $Id: fft.py,v 1.1 2010-02-24 14:27:23 wirawan Exp $
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# $Id: fft.py,v 1.2 2011-10-06 19:14:48 wirawan Exp $
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#
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# wpylib.math.fft module
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# Created: 20100205
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@@ -37,7 +37,7 @@ The slice [gmin:gmax:gstep] will certainly result in an empty slice.
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To do this, we define two functions below.
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First, fft_grid_ranges1 generates the ranges for each dimension, then
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fft_grid_ranges itself generates all the combination of ranges (which cover
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all combinations of positive and ndgative frequency domains for all
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all combinations of positive and negative frequency domains for all
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dimensions.)
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For a (5x8) FFT grid, we will have
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@@ -70,6 +70,57 @@ fft_grid_ranges = lambda Gmin, Gmax, Gstep : \
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all_combinations(fft_grid_ranges1(Gmin, Gmax, Gstep))
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class fft_grid(object):
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"""A class describing a N-dimensional grid for plane wave
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(or real-space) basis.
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In this version, the grid is centered at (0,0,...) coordinate.
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To actually create a grid, use the new_dens() method.
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"""
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dtype = complex
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def __init__(self, Gsize=None, Gmin=None, Gmax=None, dtype=None):
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"""Creates a new grid descriptor.
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There are two possible methods, and you must choose either one for
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initialization:
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* Gsize = an N-dimensional array (list, tuple, ndarray) specifying
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the number of grid points in each dimension.
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or
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* Gmin, Gmax = a pair of N-dimensional arrays (list, tuple, ndarray)
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specifying the smallest (most negative) and largest (most positive)
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coordinates in each dimension.
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The grid size will be specified to fit this range.
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"""
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from numpy import maximum
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if Gsize != None:
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self.Gsize = numpy.array(Gsize, dtype=int)
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(self.Gmin, self.Gmax) = fft_grid_bounds(self.Gsize)
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elif Gmin != None and Gmax != None:
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self.Gmin = numpy.array(Gmin, dtype=int)
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self.Gmax = numpy.array(Gmax, dtype=int)
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# Figure out the minimum grid size to fit this data:
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Gsize_min = abs(self.Gmin) * 2
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Gsize_max = abs(self.Gmax) * 2 + (abs(self.Gmax) % 2)
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Gsize_def = self.Gmax - self.Gmin + 1
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self.Gsize = maximum(maximum(Gsize_min, Gsize_max), Gsize_def)
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else:
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raise ValueError, \
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"Either Gsize or (Gmin,Gmax) parameters have to be specified."
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if dtype != None:
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self.dtype = dtype
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self.ndim = len(self.Gsize)
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def new_dens(self, zero=False, dtype=None):
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"""Creates a new N-dimensional array (grid)."""
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if dtype == None: dtype = self.dtype
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if zero:
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return numpy.zeros(self.Gsize, dtype=dtype)
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else:
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return numpy.empty(self.Gsize, dtype=dtype)
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def check_index(self, G):
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"""Check if an index is valid according to Gmin, Gmax boundary."""
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return numpy.all(self.Gmin <= G) and numpy.all(G <= self.Gmax)
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def fft_r2g(dens):
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"""Do real-to-G space transformation.
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According to our covention, this transformation gets the 1/Vol prefactor."""
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@@ -1,4 +1,4 @@
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# $Id: __init__.py,v 1.1 2011-07-14 19:00:59 wirawan Exp $
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# $Id: __init__.py,v 1.2 2011-10-06 19:14:49 wirawan Exp $
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#
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# wpylib.math.linalg main module
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# Created: 20110714
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@@ -13,6 +13,12 @@ already provided by numpy.
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"""
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import numpy
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import numpy.linalg
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# My favorites:
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from numpy import dot, trace
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from numpy.linalg import det, inv
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def matmul(*Mats):
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"""Do successive matrix product. For example,
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13
math/stats/linear_regression.py
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13
math/stats/linear_regression.py
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# $Id: linear_regression.py,v 1.1 2011-10-06 19:14:50 wirawan Exp $
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#
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# Module wpylib.math.stats.linear_regression
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#
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# Created: 20110414
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# Wirawan Purwanto
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#
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# Transcribed from my cp.inc's stats1.cpp
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class linreg(object):
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"""Class linreg provides my standard recipe for linear regression.
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"""
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@@ -1,4 +1,4 @@
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# $Id: params_flat_test.py,v 1.2 2011-09-09 18:58:48 wirawan Exp $
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# $Id: params_flat_test.py,v 1.3 2011-10-06 19:14:51 wirawan Exp $
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# 20100930
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from wpylib.params import flat as params
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@@ -55,6 +55,10 @@ def test2b(**_opts_):
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print "new deltau = ", p.deltau
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def dump_objects():
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"""See what's in each dicts.
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"""
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pass
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if __name__ == "__main__":
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57
py/wrapper.py
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57
py/wrapper.py
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# $Id: wrapper.py,v 1.1 2011-10-06 19:15:05 wirawan Exp $
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#
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# wpylib.py.wrapper module
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# Created: 20110608
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# Wirawan Purwanto
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#
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# Wrapper base class.
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# Used for automatic wrapping of (especially) methods to
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# dispatch it to a host of object possibilities.
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#
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class wrapper_base(object):
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"""Wrapper or proxy object to provide uniform API to other routines,
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etc.
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This class allows dirty tricks such as injecting external functions
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to accomplish certain required tasks in object-oriented manner.
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If using external procedure, it must be callable with "self" as
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its first argument.
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Reserved attributes:
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* _obj_ = the wrapped object
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* _procnames_[:] = method names to wrap automatically.
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* _obj_path_[:] = list of objects (instances) from which to look
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for the methods.
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* _set_obj_path_() = object method to define what objects to be
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included in the object path (_obj_path_).
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"""
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def __init__(self, obj):
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"""Creates a wrapper."""
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self._obj_ = obj
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if hasattr(self, '_set_obj_path_'):
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self._set_obj_path_()
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else:
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self._obj_path_ = [ obj ]
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def _autoset_proc_(self, procname, extproc=None):
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from wpylib.py import make_unbound_method
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from wpylib.py.im_weakref import im_ref
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from weakref import ref
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procname_ = procname + '_'
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procname_proc = procname + '_proc'
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if hasattr(self, procname_proc):
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# In case the derived-class has the procedure, we will use
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# that.
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setattr(self, procname, im_ref(getattr(self, procname_proc)))
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else:
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for o in self._obj_path_:
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if hasattr(o, procname):
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setattr(self, procname, im_ref(getattr(o, procname)))
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return
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# May implement a global fallback hook here?
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pass
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