Adding baseline optimizers #46

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JonahHansen wants to merge 33 commits into fdannert:fov_taper from JonahHansen:fov_taper

lifesim/__init__.py

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+Diff line change
@@ Expand Up / @@ -13,4 +13,6 @@ @@
     from lifesim.optimize.optimizer import Optimizer
     from lifesim.optimize.ahgs import AhgsModule
-    from lifesim.gui.spectrum_gui import Gui
+    from lifesim.gui.spectrum_gui import Gui
+    from lifesim.analysis.yield_wrapper import ScienceYield

lifesim/analysis/yield_wrapper.py

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lifesim/analysis/yield_wrapper_notes.md

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@@ -0,0 +1,171 @@
+    # `ScienceYield` Wrapper
+    The purpose of the science yield wrapper is to collect all functions necessary to run a yield with LIFEsim.
+    While detection yields with single catalogs or instrument setups can be quickly run using
+    `instrument.snr()` and `opt.ahgs()`, this wrapper is aimed at
+    - yields for varying instrument setups (e.g. aperture size)
+    - yields including the characterization yield
+    Central tools to achieve this are
+    - a table of all synthetic planets, to which LIFEsim adds the `snr_1h` column. We call this _snr table_.
+    - the optimizer, which based on the `snr_1h` column creates an optimized observing sequence
+    ## Current State
+    So far, the ScienceYield wrapper has grown organically.
+    Here, we provide an overview of the current state.
+    ---
+    ## `ScienceYield`
+    ### Constructor
+    #### `__init__(self, ...)`
+    **Description:**
+    Sets up the working environment, mainly paths to file locations.
+    **Arguments:**
+    | Argument        | Type | Description                                  |
+    |-----------------|------|----------------------------------------------|
+    | `config_path`   | str  | Path to the config file in .yaml format      |
+    | `catalog_path`  | str  | Path to the input catalog                    |
+    | `output_path`   | str  | Location where the snr catalogs are saved    |
+    | `n_cpu`         | int  | Number of CPUs to be used in multiprocessing |
+    | `cat_from_ppop` | bool | True if input catalog is in .txt format      |
+    **Example:**
+    ```python
+    import lifesim
+    ywrap = lifesim.ScienceYield(config_path='/path/CONFIG_251104.yaml',
+                     catalog_path='/path/Bryson2021_hab2low.txt',
+                     output_path='/path/hab2low_500/',
+                     n_cpu=64)
+    ```
+    #### `_compute_snrs(self, ...)`
+    **Description:**
+    Calculates on individual SNR table for one setting of the instrument.
+    Saves a catalog with `snr_1h` and a config file called `output_filename_catalog.hdf5` and `output_filename.yaml` to `output_path`.
+    This function is mainly meant to be an internal helper function, it is usually not required to use it.
+    **Arguments:**
+    | Argument          | Type | Description                                                                     |
+    |-------------------|------|---------------------------------------------------------------------------------|
+    | `output_path`     | str  | Path to where this individual run is saved                                      |
+    | `output_filename` | str  | Filename of catalog and config table                                            |
+    | `run_maxsep`      | bool | If true, all planets will be placed in their maximum separation                 |
+    | `diameter`        | int  | Mirror diameter for this run. If set to None, diameter from config file is used |
+    **Files created:**
+    | Name / Location                           | Content and Purpose            |
+    |-------------------------------------------|--------------------------------|
+    | `output_path/output_filename_catalog.hdf5`| snr table for the single run   |
+    | `output_path/output_filename.yaml`        |config file for the single run |
+    **Example:**
+    (continued from above)
+    ```python
+    ywrap.compute_snrs(output_path='path/',
+                       output_filename='single_test',
+                       run_maxsep=False,
+                       diameter=None)
+    ```
+    #### `run_aperture_sweep_snr(self, ...)`
+    **Description:**
+    One of the key instrument parameters is the sensitivity.
+    For LIFE, we usually fix the photon-conversion-efficiency, and the aperture is varied.
+    This function creates snr tables for an array of mirror diameters.
+    **Arguments:**
+    | Argument           | Type             | Description                               |
+    |--------------------|------------------|-------------------------------------------|
+    | `mirror_diameters` | list/np.ndarray  | Array of all mirror sizes to be evaluated |
+    | `run_name`         | str              | Name of the run (for file creation)       |
+    **Files created:**
+    For every diameter in `mirror_diameters`, the following files will be created (here we take 2.5m as example)
+    | Name / Location                                                         | Content and Purpose                                                                     |
+    |-------------------------------------------------------------------------|-----------------------------------------------------------------------------------------|
+    | `self.output_path/run_name/diam_2_5/`                                   | new parent directory is created                                                         |
+    | `self.output_path/run_name/diam_2_5/sweep_diam_2_5.yaml`                | _config file_ for run with the actual planet position for the detection phase           |
+    | `self.output_path/run_name/diam_2_5/sweep_diam_2_5_catalog.hdf5`        | &uarr; and its _snr catalog_                                                            |
+    | `self.output_path/run_name/diam_2_5/sweep_diam_maxsep_2_5.yaml`         | _config file_ for run with the maximum planet separation for the characterization phase |
+    | `self.output_path/run_name/diam_2_5/sweep_diam_maxsep_2_5_catalog.hdf5` | &uarr; and its _snr catalog_                                                            |
+    **Example:**
+    (continued from above)
+    ```python
+    ywrap.run_aperture_sweep_snr(mirror_diameters=np.arange(2.0, 5.1, 0.25),
+                                 run_name='aperture_size_2_to_5')
+    ```
+    #### `run_optimizer_sweep(self, ...)`
+    **Description:**
+    Runs the optimizer on all snr tables in a given source folder.
+    **Arguments:**
+    | Argument      | Type | Description                                                           |
+    |---------------|------|-----------------------------------------------------------------------|
+    | `run_name`    | str  | Name of the run (for file creation)                                   |
+    | `source_name` | str  | Name of the folder in self.output_path that contains the _snr tables_ |
+    **Files created:**
+    | Name / Location                                                | Content and Purpose                                            |
+    |----------------------------------------------------------------|----------------------------------------------------------------|
+    | `self.output_path/run_name/`                                   | new parent directory is created, if it does not already exists |
+    | `self.output_path/run_name/subdir/`                            | New directory for every directory in the source folder         |
+    | `self.output_path/run_name/subdir/sweep_diam_2_5.yaml`         | _config file_ for run of optimizer                             |
+    | `self.output_path/run_name/subdir/sweep_diam_2_5_catalog.hdf5` | &uarr; and its _snr catalog_ with optimized sequence           |
+    **Example:**
+    (continued from above)
+    ```python
+    ywrap.run_optimizer_sweep(run_name='opt_aperture_size_2_to_5',
+                              source_name='aperture_size_2_to_5')
+    ```
+    ---
+    ## Helper Functions
+    #### `compute_yields_mp()`
+    **Description:**
+    Runs the optimizer on all snr tables in a given source folder.
+    **Arguments:**
+    | Argument          | Type     | Description                                                                   |
+    |-------------------|----------|-------------------------------------------------------------------------------|
+    | `output_filename` | str      | Name of output files                                                          |
+    | `output_path`     | str      | Path to which catalog and config file will be saved                           |
+    | `catalog_path`    | str      | Path to the input catalog file                                                |
+    | `config_path`     | str      | Path to the config file                                                       |
+    | `uni_sel`         | int/None | Number of universes to select from all universes. If `None`, all are selected |
+    | `return_yields`   | bool     | Set true to return experiment yield of this run                               |
+    **Files created:**
+    | Name / Location                           | Content and Purpose              |
+    |-------------------------------------------|----------------------------------|
+    | `output_path/output_filename_catalog.hdf5`| snr table for the single run     |
+    | `output_path/output_filename.yaml`        | config file for the single run   |
+    # What happens in the characterization ahgs

lifesim/core/core.py

            
                      Original file line number
                      Diff line number
                      Diff line change
                  
    @@ -6,7 +6,7 @@
  
    import os

    import yaml

    from numpy import ndarray, array

    from numpy import ndarray, array, float64, float32, int64, int32, int16

    import git

    from lifesim.core.data import Data

    @@ -442,6 +442,8 @@ def add_module(self,
  
            module.data = self.data

        def write_config(self):

            add_numpy_representers()

            module_dict = {key: str(type(module)) for (key, module) in self.modules.items()}

            # fetch version number and git commit hash if available

    @@ -475,7 +477,7 @@ def write_config(self):
  
        def build_from_config(self,

                              filename: str):

            with open(filename) as file:

                config_dict = yaml.load(file, Loader=yaml.FullLoader)

                config_dict = yaml.load(file, Loader=yaml.UnsafeLoader)

            self.data.options.array = convert_to_np(config_dict['array'])

            self.data.options.optimization = convert_to_np(config_dict['optimization'])

    @@ -520,3 +522,14 @@ def convert_to_np(inp: dict):
  
            else:

                out[k] = inp[k]

        return out

    def add_numpy_representers():

        def numpy_repr(dumper, data):

            return dumper.represent_data(data.item())

        # Add for various numpy types

        for dtype in [float64, float32, int64, int32, int16]:

            yaml.add_representer(dtype, numpy_repr)

        # Handle numpy arrays specifically

        yaml.add_representer(ndarray, lambda dumper, data: dumper.represent_list(data.tolist()))

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