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adding module refs for pysaul utils

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This commit is contained in:
Andy Eschbacher 2016-03-31 09:35:10 -04:00
parent 314d1851db
commit c18baf26d8
1 changed files with 13 additions and 5 deletions
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18
src/py/crankshaft/crankshaft/space_time_dynamics/markov.py
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@ -6,7 +6,7 @@ Spatial dynamics measurements using Spatial Markov
import numpy as np import numpy as np
import pysal as ps import pysal as ps
import plpy import plpy
from crankshaft.clustering import get_query, get_weight import crankshaft.pysal_utils as pu
def spatial_markov_trend(subquery, time_cols, num_time_per_bin, def spatial_markov_trend(subquery, time_cols, num_time_per_bin,
permutations, geom_col, id_col, w_type, num_ngbrs): permutations, geom_col, id_col, w_type, num_ngbrs):
@ -43,7 +43,7 @@ def spatial_markov_trend(subquery, time_cols, num_time_per_bin,
"subquery": subquery, "subquery": subquery,
"num_ngbrs": num_ngbrs} "num_ngbrs": num_ngbrs}
query = get_query(w_type, qvals) query = pu.construct_neighbor_query(w_type, qvals)
try: try:
query_result = plpy.execute(query) query_result = plpy.execute(query)
@ -53,7 +53,7 @@ def spatial_markov_trend(subquery, time_cols, num_time_per_bin,
return zip([None], [None], [None], [None], [None]) return zip([None], [None], [None], [None], [None])
## build weight ## build weight
weights = get_weight(query_result, w_type) weights = pu.get_weight(query_result, w_type)
## prep time data ## prep time data
t_data = get_time_data(query_result, time_cols) t_data = get_time_data(query_result, time_cols)
@ -81,6 +81,14 @@ def spatial_markov_trend(subquery, time_cols, num_time_per_bin,
return zip(trend, trend_up, trend_down, volatility, weights.id_order) return zip(trend, trend_up, trend_down, volatility, weights.id_order)
def spatial_markov_predict(subquery, time_cols, num_time_per_bin,
permutations, geom_col, id_col, w_type, num_ngbrs):
"""
Filler for this future function
"""
return None
def get_time_data(markov_data, time_cols): def get_time_data(markov_data, time_cols):
""" """
Extract the time columns and bin appropriately Extract the time columns and bin appropriately
@ -98,13 +106,13 @@ def rebin_data(time_data, num_time_per_bin):
9 8 7 6 8.5 6.5 9 8 7 6 8.5 6.5
5 4 3 2 4.5 2.5 5 4 3 2 4.5 2.5
if m = 2 if m = 2, the 4 x 4 matrix is transformed to a 2 x 4 matrix.
This process effectively resamples the data at a longer time span n This process effectively resamples the data at a longer time span n
units longer than the input data. units longer than the input data.
For cases when there is a remainder (remainder(5/3) = 2), the remaining For cases when there is a remainder (remainder(5/3) = 2), the remaining
two columns are binned together as the last time period, while the two columns are binned together as the last time period, while the
first three are binned together. first three are binned together for the first period.
Input: Input:
@param time_data n x l ndarray: measurements of an attribute at @param time_data n x l ndarray: measurements of an attribute at