[run_selector] Select several outputs by time + doc
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+74
-18
@@ -1,5 +1,7 @@
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# -*- mode: python-mode; python-indent-offset: 4 -*-
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# coding: utf-8
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import os
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import glob
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from functools import partial
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@@ -39,18 +41,56 @@ class RunSelector:
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in_runs=None,
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in_nums="all",
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pp_params=default_params(),
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name_run="*",
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namelist_cond={},
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filter_name="*",
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filter_nml={},
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sort_run_by=None,
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time_min=None,
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time_max=None,
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time=None,
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):
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"""
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Select runs and outputs with several filter options.
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By default, all runs and outputs within path_in are considered
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Parameters
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---------
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1. Define the set of runs and outputs considered
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path_in : str, path to the folder of the runs
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2. Filter runs and outputs
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in_runs : str or list of str. The name runs to consider. Default: all.
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in_nums : int or list of int or str.
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The output numbers to consider.
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"last" select only the last output.
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"all" preselect all outputs (default)
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filter_name : str, filter runs by name. Default "*"
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filter_nml : tuple or list of tupple.
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Filter runs by namelist.
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tuples are in the following form:
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(nml_key, operator, nml_value)
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with nml_key a key from the namelist (eg. "cloud_params/dens0")
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operator within ("=", "!=", "<", ">", "in")
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and nml_value a string, float or int
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time_min : float, select output where time >= time_min (in code units)
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time_max : float, select output where time <= time_min (in code units)
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time : float or list of float. For each value, select the output closer to it.
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3. Sort the runs
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sort_run_by : str, a key from the namelist used to sort the runs (by ascending order)
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"""
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self.path_in = path_in
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self.pp_params = pp_params
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self.namelist = {}
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self.runs = self.get_runs(in_runs, name_run, namelist_cond, sort_run_by)
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self.runs = self.get_runs(in_runs, filter_name, filter_nml, sort_run_by)
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if len(self.runs) == 0:
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raise ValueError("No runs found")
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@@ -67,7 +107,9 @@ class RunSelector:
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in_nums[run] = nums_temp
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for i, run in enumerate(self.runs):
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self.nums[run] = self.get_nums(run, in_nums[run], time_min, time_max, time)
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self.nums[run] = self.get_nums(
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run, in_nums[run], time_min, time_max, time
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)
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def load_namelist(self, run):
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path_run = self.path_in + "/" + run
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@@ -77,11 +119,11 @@ class RunSelector:
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def get_nml_value(self, nml_key, run):
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return self.namelist[run][nml_key]
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def nml_select(self, runs, namelist_cond):
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if type(namelist_cond) == tuple:
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namelist_cond = [namelist_cond]
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def nml_select(self, runs, filter_nml):
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if type(filter_nml) == tuple:
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filter_nml = [filter_nml]
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for (nml_key, operator, operand) in namelist_cond:
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for (nml_key, operator, operand) in filter_nml:
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value = {}
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for run in runs:
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value[run] = self.get_nml_value(nml_key, run)
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@@ -97,7 +139,7 @@ class RunSelector:
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runs = list(filter(lambda r: value[r] in operand, runs))
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return runs
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def get_runs(self, in_runs=None, name_run="*", namelist_cond={}, sort_run_by=None):
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def get_runs(self, in_runs=None, filter_name="*", filter_nml={}, sort_run_by=None):
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def try_load_nml(run):
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try:
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self.namelist[run] = self.load_namelist(run)
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@@ -109,15 +151,17 @@ class RunSelector:
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runs = list(
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map(
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os.path.basename,
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list(filter(os.path.isdir, glob.glob(self.path_in + "/" + name_run))),
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list(
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filter(os.path.isdir, glob.glob(self.path_in + "/" + filter_name))
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),
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)
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)
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if not in_runs is None:
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if in_runs is not None:
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runs = list(filter(lambda n: n in runs, in_runs))
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runs = list(filter(try_load_nml, runs))
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# Select runs that match namelist conditions
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runs = self.nml_select(runs, namelist_cond)
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runs = self.nml_select(runs, filter_nml)
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# Sort by the value in the namelist of sort_run_by
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if not sort_run_by is None:
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@@ -190,14 +234,26 @@ class RunSelector:
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else:
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nums = list(filter(try_load_info, nums))
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if not time_min is None:
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if time_min is not None:
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nums = list(filter(lambda n: self.info[run][n]["time"] >= time_min, nums))
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if not time_max is None:
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if time_max is not None:
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nums = list(filter(lambda n: self.info[run][n]["time"] <= time_max, nums))
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if not time is None:
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times = np.asarray([[self.info[run][n]["time"], n] for n in nums])
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idx = (np.abs(times[:, 0] - time)).argmin()
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nums = [int(times[idx, 1])]
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if time is not None:
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filtered_nums = []
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if not isinstance(time, list):
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time = [time]
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# Get time for all already selected nums
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time_all = np.asarray([[self.info[run][n]["time"], n] for n in nums])
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# For all times provided by the user, select the output closer to it
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for t in time:
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# Index of this output in the time_all array
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idx = (np.abs(time_all[:, 0] - t)).argmin()
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num = int(time_all[idx, 1])
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# Only add each selected output once
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if num not in filtered_nums:
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filtered_nums.append(num)
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nums = filtered_nums
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return nums
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