fix(helper): Add function to find smallest dtype

* fix(helper): Add function to find smallest dtype

* fix(map): Add binary option in CLI command

* refactor(mtx): Use load matrix function

ladybug_comfort/cli/_helper.py

@@ -178,9 +178,100 @@ def thermal_map_csv(folder, temperature, condition, condition_intensity,
         _data_to_csv(condition_intensity, result_file_dict['condition_intensity'])
     else:
         with open(result_file_dict['temperature'], 'wb') as fp:
-            np.save(fp, temperature)
+            np.save(fp, set_smallest_dtype(np.array(temperature)))
         with open(result_file_dict['condition'], 'wb') as fp:
-            np.save(fp, np.array(condition))
+            np.save(fp, set_smallest_dtype(np.array(condition)))
         with open(result_file_dict['condition_intensity'], 'wb') as fp:
-            np.save(fp, np.array(condition_intensity))
+            np.save(fp, set_smallest_dtype(np.array(condition_intensity)))
     return result_file_dict
+
+
+def smallest_integer_dtype(array: np.ndarray):
+    """Return the smallest possible integer dtype.
+
+    Args:
+        array: NumPy array.
+    
+    Returns:
+        A NumPy integer dtype.
+    """
+    if np.all(array >= np.iinfo(np.int8).min) and \
+        np.all(array <= np.iinfo(np.int8).max):
+        return np.int8
+    elif np.all(array >= np.iinfo(np.int16).min) and \
+        np.all(array <= np.iinfo(np.int16).max):
+        return np.int16
+    elif np.all(array >= np.iinfo(np.int32).min) and \
+        np.all(array <= np.iinfo(np.int32).max):
+        return np.int32
+    elif np.all(array >= np.iinfo(np.int64).min) and \
+        np.all(array <= np.iinfo(np.int64).max):
+        return np.int64
+
+
+def smallest_float_dtype(array: np.ndarray, rtol: float = 1e-5, atol: float = 1e-5):
+    """Return the smallest possible float dtype.
+
+    The allclose function is used to check if a certain floating-point precision
+    can be used without losing accuracy.
+
+    Args:
+        array: NumPy array.
+        rtol: The relative tolerance parameter for `np.allclose`. The default
+            is 1e-5.
+        atol: The absolute tolerance parameter for `np.allclose`. The default
+            is 1e-5.
+    
+    Returns:
+        A NumPy floating dtype.
+    """
+    if np.all((array >= np.finfo(np.float16).min) & \
+                (array <= np.finfo(np.float16).max)):
+        if np.allclose(array, array.astype(np.float16), rtol=rtol, atol=atol):
+            return np.float16
+    if np.all((array >= np.finfo(np.float32).min) & \
+                (array <= np.finfo(np.float32).max)):
+        if np.allclose(array, array.astype(np.float32), rtol=rtol, atol=atol):
+            return np.float32
+    if np.all((array >= np.finfo(np.float64).min) & \
+                (array <= np.finfo(np.float64).max)):
+        if np.allclose(array, array.astype(np.float64), rtol=rtol, atol=atol):
+            return np.float64
+
+
+def smallest_dtype(array: np.ndarray, rtol: float = 1e-5, atol: float = 1e-5):
+    """Return the smallest possible dtype.
+
+    Args:
+        array: NumPy array.
+        rtol: The relative tolerance parameter for `np.allclose`. The default
+            is 1e-5. This is also used if the dtype of the array is np.floating.
+        atol: The absolute tolerance parameter for `np.allclose`. The default
+            is 1e-5. This is also used if the dtype of the array is np.floating.
+    
+    Returns:
+        A NumPy dtype.
+    """
+    if np.issubdtype(array.dtype, np.integer):
+        return smallest_integer_dtype(array)
+    elif np.issubdtype(array.dtype, np.floating):
+        return smallest_float_dtype(array, rtol=rtol, atol=atol)
+    else:
+        raise TypeError(f'Expected integer or floating dtype. Got {array.dtype}')
+
+
+def set_smallest_dtype(array: np.ndarray, rtol: float = 1e-5, atol: float = 1e-5):
+    """Return a NumPy array with the smallest possible dtype.
+    
+    Args:
+        array: NumPy array.
+        rtol: The relative tolerance parameter for `np.allclose`. The default
+            is 1e-5. This is also used if the dtype of the array is np.floating.
+        atol: The absolute tolerance parameter for `np.allclose`. The default
+            is 1e-5. This is also used if the dtype of the array is np.floating.
+    
+    Returns:
+        A new NumPy array with a smaller dtype.
+    """
+    dtype = smallest_dtype(array, rtol=rtol, atol=atol)
+    return array.astype(dtype)

ladybug_comfort/cli/map.py

@@ -34,7 +34,7 @@
 
 from ._helper import load_values, load_analysis_period_str, \
     load_pmv_par_str, load_adaptive_par_str, load_utci_par_str, \
-    load_solarcal_par_str, thermal_map_csv, _data_to_ill
+    load_solarcal_par_str, thermal_map_csv, _data_to_ill, set_smallest_dtype
 
 _logger = logging.getLogger(__name__)
 
@@ -590,7 +590,7 @@ def shortwave_mrt(
                 output_file.write('')
             else:
                 with open(output_file.name, 'wb') as fp:
-                    np.save(fp, d_mrt_temps)
+                    np.save(fp, set_smallest_dtype(np.array(d_mrt_temps)))
     except Exception as e:
         _logger.exception('Failed to run Shortwave MRT Delta map.\n{}'.format(e))
         sys.exit(1)
@@ -651,7 +651,7 @@ def longwave_mrt(result_sql, view_factors, modifiers, enclosure_info, epw_file,
                 output_file.write('\n')
         else:
             with open(output_file.name, 'wb') as fp:
-                np.save(fp, mrt_temps)
+                np.save(fp, set_smallest_dtype(np.array(mrt_temps)))
     except Exception as e:
         _logger.exception('Failed to run Longwave MRT map.\n{}'.format(e))
         sys.exit(1)
@@ -677,8 +677,12 @@ def longwave_mrt(result_sql, view_factors, modifiers, enclosure_info, epw_file,
 @click.option('--output-file', '-f', help='Optional file to output the CSV matrix '
               'of values. By default this will be printed out to stdout',
               type=click.File('w'), default='-', show_default=True)
-def air_temperature(result_sql, enclosure_info, epw_file,
-                    run_period, air_temperature, output_file):
+@click.option('--plain-text/--binary', ' /-b', help='Flag to note whether the '
+              'output should be formatted as a plain text CSV or whether it '
+              'should be formatted as a binary numpy array.',
+              default=True, show_default=True)
+def air_temperature(result_sql, enclosure_info, epw_file, run_period,
+                    air_temperature, output_file, plain_text):
     """Get CSV files with maps of air temperatures or humidity from EnergyPlus results.
 
     \b
@@ -701,9 +705,13 @@ def air_temperature(result_sql, enclosure_info, epw_file,
         air_data = air_map(enclosure_info, result_sql, epw_file, run_period, humidity)
 
         # write out the final results to CSV files
-        for air_d in air_data:
-            output_file.write(','.join(str(v) for v in air_d))
-            output_file.write('\n')
+        if plain_text:
+            for air_d in air_data:
+                output_file.write(','.join(str(v) for v in air_d))
+                output_file.write('\n')
+        else:
+            with open(output_file.name, 'wb') as fp:
+                np.save(fp, set_smallest_dtype(np.array(air_data)))
     except Exception as e:
         _logger.exception('Failed to run Air Temperature map.\n{}'.format(e))
         sys.exit(1)

ladybug_comfort/cli/mtx.py

@@ -4,14 +4,14 @@
 import logging
 import json
 import os
-import numpy as np
 
 from ladybug_comfort.pmv import predicted_mean_vote, predicted_mean_vote_no_set
 from ladybug_comfort.adaptive import adaptive_comfort_ashrae55, \
     adaptive_comfort_en15251, adaptive_comfort_conditioned_function, \
     cooling_effect_ashrae55, cooling_effect_en16798, cooling_effect_en15251
 from ladybug_comfort.utci import universal_thermal_climate_index
 
+from ..map._helper import load_matrix
 from ._helper import load_value_list, thermal_map_csv, csv_to_num_matrix, \
     load_pmv_par_str, load_adaptive_par_str, load_utci_par_str
 
@@ -360,29 +360,15 @@ def utci_mtx(
     """
     try:
         # load up the matrices of values
-        air_temp = np.genfromtxt(temperature_mtx, delimiter=',').tolist()
-        rel_h = np.genfromtxt(rel_humidity_mtx, delimiter=',').tolist()
+        air_temp = load_matrix(temperature_mtx).tolist()
+        rel_h = load_matrix(rel_humidity_mtx).tolist()
+
         if rad_temperature_mtx is not None:
-            with open(rad_temperature_mtx, 'rb') as inf:
-                first_char = inf.read(1)
-                second_char = inf.read(1)
-            is_text = True if first_char.isdigit() or second_char.isdigit() else False
-            if is_text:
-                rad_temp = np.genfromtxt(
-                    rad_temperature_mtx, delimiter=',', encoding='utf-8').tolist()
-            else:
-                rad_temp = np.load(rad_temperature_mtx).tolist()
+            rad_temp = load_matrix(rad_temperature_mtx).tolist()
         else:
             rad_temp = air_temp
         if rad_delta_mtx is not None and not os.path.getsize(rad_delta_mtx) == 0:
-            with open(rad_delta_mtx, 'rb') as inf:
-                first_char = inf.read(1)
-                second_char = inf.read(1)
-            is_text = True if first_char.isdigit() or second_char.isdigit() else False
-            if is_text:
-                d_rad_temp = np.genfromtxt(rad_delta_mtx, delimiter=',', encoding='utf-8')
-            else:
-                d_rad_temp = np.load(rad_delta_mtx).tolist()
+            d_rad_temp = load_matrix(rad_delta_mtx).tolist()
             rad_temp = tuple(tuple(t + dt for t, dt in zip(t_pt, dt_pt))
                              for t_pt, dt_pt in zip(rad_temp, d_rad_temp))
         mtx_len = len(air_temp[0])