From fd80bc89069c285791039bb9bc3f6e769679d3b3 Mon Sep 17 00:00:00 2001
From: lkugler <lukas.kugler@gmail.com>
Date: Thu, 19 Jan 2023 14:39:47 +0100
Subject: [PATCH] improved layer calculation
---
dartwrf/obsseq.py | 31 ++++++++++++++++++++++++-------
1 file changed, 24 insertions(+), 7 deletions(-)
diff --git a/dartwrf/obsseq.py b/dartwrf/obsseq.py
index e3fa8ad..69a5f6e 100755
--- a/dartwrf/obsseq.py
+++ b/dartwrf/obsseq.py
@@ -136,6 +136,27 @@ class ObsRecord(pd.DataFrame):
# find indices of observations within pandas.DataFrame
return self.iloc[self.i_obs_grid[i, j, k].ravel()]
+ def determine_nlayers(self):
+ nlayers = 1 # first guess
+
+ if len(exp.observations) == 1:
+ # obscfg = exp.observations[0]
+ # if 'heights' in obscfg:
+ # nlayers = len(obscfg['heights'])
+
+ heights = [loc_xyz[2] for loc_xyz in self['loc3d']]
+ heights = sorted(heights)
+ h0 = heights[0]
+ for i, h in enumerate(heights):
+ if h != h0:
+ break
+ obs_per_layer = i # if it fails at 1, there is 1 obs per layer
+
+ nlayers = int(len(self)/obs_per_layer)
+ else:
+ warnings.warn('I can only guess the number of layers from this file.')
+ return nlayers
+
def superob(self, window_km):
"""Select subset, average, overwrite existing obs with average
@@ -191,14 +212,10 @@ class ObsRecord(pd.DataFrame):
print("window (#obs in x/y)=", win_obs)
# superob in case of multiple layers, only implemented for single obstype
- nlayers = 1
- if len(exp.observations) == 1:
- obscfg = exp.observations[0]
- if 'heights' in obscfg:
- nlayers = len(obscfg['heights'])
- self.nlayers = nlayers
+ nlayers = self.determine_nlayers()
- i_obs_grid = self.index.values # indices of observations (starting from 0)
+ # indices of observations (starting from 0)
+ i_obs_grid = self.index.values
# get the observation indices from obs_seq (list)
# onto a cartesian grid (ix, iy, iz)
--
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