updated docs

docs/code/pyaurorax_api_reference/pyaurorax/index.html

@@ -73,7 +73,7 @@ <h1 class="title">Package <code>pyaurorax</code></h1>
 &#34;&#34;&#34;
 
 # versioning info
-__version__ = &#34;1.0.0-rc1&#34;
+__version__ = &#34;1.0.0&#34;
 
 # documentation excludes
 __pdoc__ = {&#34;cli&#34;: False, &#34;pyaurorax&#34;: False}

docs/code/pyaurorax_api_reference/pyaurorax/tools/calibration/index.html

@@ -61,7 +61,7 @@ <h1 class="title">Module <code>pyaurorax.tools.calibration</code></h1>
 <h2 class="section-title" id="header-functions">Functions</h2>
 <dl>
 <dt id="pyaurorax.tools.calibration.rego"><code class="name flex">
-<span>def <span class="ident">rego</span></span>(<span>images: numpy.ndarray, cal_flatfield: Optional[pyucalgarysrs.data.classes.Calibration] = None, cal_rayleighs: Optional[pyucalgarysrs.data.classes.Calibration] = None, step_dark_frame_correction: bool = True, step_flatfield_correction: bool = True, step_rayleighs_conversion: bool = True, exposure_length_sec: float = 2.0) ‑> numpy.ndarray</span>
+<span>def <span class="ident">rego</span></span>(<span>images: numpy.ndarray, cal_flatfield: Optional[pyucalgarysrs.data.classes.Calibration] = None, cal_rayleighs: Optional[pyucalgarysrs.data.classes.Calibration] = None, step_dark_frame_correction: bool = True, step_flatfield_calibration: bool = True, step_rayleighs_calibration: bool = True, exposure_length_sec: float = 2.0) ‑> numpy.ndarray</span>
 </code></dt>
 <dd>
 <div class="desc"><p>Apply various calibration adjustments to a single or set of images raw images.</p>
@@ -74,13 +74,13 @@ <h2 id="args">Args</h2>
 the <code>step_flatfield_corection</code> is set to True.</dd>
 <dt><strong><code>cal_rayleighs</code></strong> :&ensp;<code><a title="pyaurorax.data.ucalgary.Calibration" href="../../data/ucalgary/index.html#pyaurorax.data.ucalgary.Calibration">Calibration</a></code></dt>
 <dd>Calibration object containing the Rayleighs data to utilize. This field is required if
-the <code>step_rayleighs_conversion</code> is set to True.</dd>
+the <code>step_rayleighs_calibration</code> is set to True.</dd>
 <dt><strong><code>step_dark_frame_correction</code></strong> :&ensp;<code>bool</code></dt>
 <dd>Perform the dark frame correction step. Defaults to <code>True</code>.</dd>
-<dt><strong><code>step_flatfield_correction</code></strong> :&ensp;<code>bool</code></dt>
+<dt><strong><code>step_flatfield_calibration</code></strong> :&ensp;<code>bool</code></dt>
 <dd>Perform the flatfield correction step. Defaults to <code>True</code>. Note that the <code>cal_flatfield</code> parameter
 must be supplied if this is True.</dd>
-<dt><strong><code>step_rayleighs_conversion</code></strong> :&ensp;<code>bool</code></dt>
+<dt><strong><code>step_rayleighs_calibration</code></strong> :&ensp;<code>bool</code></dt>
 <dd>Perform the Rayleighs conversion step. Defaults to <code>True.</code> Note that the <code>cal_rayleighs</code> parameter
 must be supplied if this is True.</dd>
 <dt><strong><code>exposure_length_sec</code></strong> :&ensp;<code>float</code></dt>
@@ -106,8 +106,8 @@ <h2 id="raises">Raises</h2>
     cal_flatfield: Optional[Calibration] = None,
     cal_rayleighs: Optional[Calibration] = None,
     step_dark_frame_correction: bool = True,
-    step_flatfield_correction: bool = True,
-    step_rayleighs_conversion: bool = True,
+    step_flatfield_calibration: bool = True,
+    step_rayleighs_calibration: bool = True,
     exposure_length_sec: float = 2.0,
 ) -&gt; np.ndarray:
     &#34;&#34;&#34;
@@ -121,13 +121,13 @@ <h2 id="raises">Raises</h2>
             the `step_flatfield_corection` is set to True.
         cal_rayleighs (pyaurorax.data.ucalgary.Calibration): 
             Calibration object containing the Rayleighs data to utilize. This field is required if 
-            the `step_rayleighs_conversion` is set to True.
+            the `step_rayleighs_calibration` is set to True.
         step_dark_frame_correction (bool): 
             Perform the dark frame correction step. Defaults to `True`.
-        step_flatfield_correction (bool): 
+        step_flatfield_calibration (bool): 
             Perform the flatfield correction step. Defaults to `True`. Note that the `cal_flatfield` parameter
             must be supplied if this is True.
-        step_rayleighs_conversion (bool): 
+        step_rayleighs_calibration (bool): 
             Perform the Rayleighs conversion step. Defaults to `True.` Note that the `cal_rayleighs` parameter
             must be supplied if this is True.
         exposure_length_sec (float): 
@@ -145,9 +145,9 @@ <h2 id="raises">Raises</h2>
         ValueError: issues encountered with supplied parameters.
     &#34;&#34;&#34;
     # verify that we have everything we need for each requested step
-    if (step_flatfield_correction is True and cal_flatfield is None):
+    if (step_flatfield_calibration is True and cal_flatfield is None):
         raise ValueError(&#34;The cal_flatfield parameter must be supplied to perform the flatfield correction step&#34;)
-    if (step_rayleighs_conversion is True and cal_rayleighs is None):
+    if (step_rayleighs_calibration is True and cal_rayleighs is None):
         raise ValueError(&#34;The cal_rayleighs parameter must be supplied to perform the rayleighs conversion step&#34;)
 
     # init
@@ -160,19 +160,19 @@ <h2 id="raises">Raises</h2>
         calibrated_images = perform_dark_frame_correction(images, 5)
 
     # apply the flatfield correction
-    if (step_flatfield_correction is True and cal_flatfield is not None):
-        calibrated_images = perform_flatfield_correction(calibrated_images, cal_flatfield)
+    if (step_flatfield_calibration is True and cal_flatfield is not None):
+        calibrated_images = perform_flatfield_calibration(calibrated_images, cal_flatfield)
 
     # apply the rayleighs conversion
-    if (step_rayleighs_conversion is True and cal_rayleighs is not None):
+    if (step_rayleighs_calibration is True and cal_rayleighs is not None):
         calibrated_images = perform_rayleighs_correction(calibrated_images, cal_rayleighs, exposure_length_sec)
 
     # return
     return calibrated_images</code></pre>
 </details>
 </dd>
 <dt id="pyaurorax.tools.calibration.trex_nir"><code class="name flex">
-<span>def <span class="ident">trex_nir</span></span>(<span>images: numpy.ndarray, cal_flatfield: Optional[pyucalgarysrs.data.classes.Calibration] = None, cal_rayleighs: Optional[pyucalgarysrs.data.classes.Calibration] = None, step_dark_frame_correction: bool = True, step_flatfield_correction: bool = True, step_rayleighs_conversion: bool = True, exposure_length_sec: float = 5.0) ‑> numpy.ndarray</span>
+<span>def <span class="ident">trex_nir</span></span>(<span>images: numpy.ndarray, cal_flatfield: Optional[pyucalgarysrs.data.classes.Calibration] = None, cal_rayleighs: Optional[pyucalgarysrs.data.classes.Calibration] = None, step_dark_frame_correction: bool = True, step_flatfield_calibration: bool = True, step_rayleighs_calibration: bool = True, exposure_length_sec: float = 5.0) ‑> numpy.ndarray</span>
 </code></dt>
 <dd>
 <div class="desc"><p>Apply various calibration adjustments to a single or set of images raw images.</p>
@@ -185,13 +185,13 @@ <h2 id="args">Args</h2>
 the <code>step_flatfield_corection</code> is set to True.</dd>
 <dt><strong><code>cal_rayleighs</code></strong> :&ensp;<code><a title="pyaurorax.data.ucalgary.Calibration" href="../../data/ucalgary/index.html#pyaurorax.data.ucalgary.Calibration">Calibration</a></code></dt>
 <dd>Calibration object containing the Rayleighs data to utilize. This field is required if
-the <code>step_rayleighs_conversion</code> is set to True.</dd>
+the <code>step_rayleighs_calibration</code> is set to True.</dd>
 <dt><strong><code>step_dark_frame_correction</code></strong> :&ensp;<code>bool</code></dt>
 <dd>Perform the dark frame correction step. Defaults to <code>True</code>.</dd>
-<dt><strong><code>step_flatfield_correction</code></strong> :&ensp;<code>bool</code></dt>
+<dt><strong><code>step_flatfield_calibration</code></strong> :&ensp;<code>bool</code></dt>
 <dd>Perform the flatfield correction step. Defaults to <code>True</code>. Note that the <code>cal_flatfield</code> parameter
 must be supplied if this is True.</dd>
-<dt><strong><code>step_rayleighs_conversion</code></strong> :&ensp;<code>bool</code></dt>
+<dt><strong><code>step_rayleighs_calibration</code></strong> :&ensp;<code>bool</code></dt>
 <dd>Perform the Rayleighs conversion step. Defaults to <code>True.</code> Note that the <code>cal_rayleighs</code> parameter
 must be supplied if this is True.</dd>
 <dt><strong><code>exposure_length_sec</code></strong> :&ensp;<code>float</code></dt>
@@ -217,8 +217,8 @@ <h2 id="raises">Raises</h2>
     cal_flatfield: Optional[Calibration] = None,
     cal_rayleighs: Optional[Calibration] = None,
     step_dark_frame_correction: bool = True,
-    step_flatfield_correction: bool = True,
-    step_rayleighs_conversion: bool = True,
+    step_flatfield_calibration: bool = True,
+    step_rayleighs_calibration: bool = True,
     exposure_length_sec: float = 5.0,
 ) -&gt; np.ndarray:
     &#34;&#34;&#34;
@@ -232,13 +232,13 @@ <h2 id="raises">Raises</h2>
             the `step_flatfield_corection` is set to True.
         cal_rayleighs (pyaurorax.data.ucalgary.Calibration): 
             Calibration object containing the Rayleighs data to utilize. This field is required if 
-            the `step_rayleighs_conversion` is set to True.
+            the `step_rayleighs_calibration` is set to True.
         step_dark_frame_correction (bool): 
             Perform the dark frame correction step. Defaults to `True`.
-        step_flatfield_correction (bool): 
+        step_flatfield_calibration (bool): 
             Perform the flatfield correction step. Defaults to `True`. Note that the `cal_flatfield` parameter
             must be supplied if this is True.
-        step_rayleighs_conversion (bool): 
+        step_rayleighs_calibration (bool): 
             Perform the Rayleighs conversion step. Defaults to `True.` Note that the `cal_rayleighs` parameter
             must be supplied if this is True.
         exposure_length_sec (float): 
@@ -256,9 +256,9 @@ <h2 id="raises">Raises</h2>
         ValueError: issues encountered with supplied parameters.
     &#34;&#34;&#34;
     # verify that we have everything we need for each requested step
-    if (step_flatfield_correction is True and cal_flatfield is None):
+    if (step_flatfield_calibration is True and cal_flatfield is None):
         raise ValueError(&#34;The cal_flatfield parameter must be supplied to perform the flatfield correction step&#34;)
-    if (step_rayleighs_conversion is True and cal_rayleighs is None):
+    if (step_rayleighs_calibration is True and cal_rayleighs is None):
         raise ValueError(&#34;The cal_rayleighs parameter must be supplied to perform the rayleighs conversion step&#34;)
 
     # init
@@ -271,11 +271,11 @@ <h2 id="raises">Raises</h2>
         calibrated_images = perform_dark_frame_correction(images, 5)
 
     # apply the flatfield correction
-    if (step_flatfield_correction is True and cal_flatfield is not None):
-        calibrated_images = perform_flatfield_correction(calibrated_images, cal_flatfield)
+    if (step_flatfield_calibration is True and cal_flatfield is not None):
+        calibrated_images = perform_flatfield_calibration(calibrated_images, cal_flatfield)
 
     # apply the rayleighs conversion
-    if (step_rayleighs_conversion is True and cal_rayleighs is not None):
+    if (step_rayleighs_calibration is True and cal_rayleighs is not None):
         calibrated_images = perform_rayleighs_correction(calibrated_images, cal_rayleighs, exposure_length_sec)
 
     # return

docs/code/pyaurorax_api_reference/pyaurorax/tools/classes/montage.html

@@ -66,11 +66,14 @@ <h1 class="title">Module <code>pyaurorax.tools.classes.montage</code></h1>
             Timestamps corresponding to each montage image.
     &#34;&#34;&#34;
 
-    def __init__(self, data: np.ndarray, timestamp: List[datetime.datetime]):
+    def __init__(self, data: np.ndarray, timestamp: List[datetime.datetime], n_channels: int):
         # public vars
         self.data = data
         self.timestamp = timestamp
 
+        # private vars
+        self.__n_channels = n_channels
+
     def __str__(self) -&gt; str:
         return self.__repr__()
 
@@ -160,12 +163,12 @@ <h1 class="title">Module <code>pyaurorax.tools.classes.montage</code></h1>
 
         # for each image
         for ax, i in zip(axs.flat, range(0, len(self.timestamp))):
-            if (len(self.data.shape) == 3):
+            if (self.__n_channels == 1):
                 # single channel
                 ax.imshow(self.data[:, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
-            elif (len(self.data.shape) == 4):
+            elif (self.__n_channels == 3):
                 # single channel
-                ax.imshow(self.data[:, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
+                ax.imshow(self.data[:, :, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
             else:
                 raise ValueError(&#34;Can only plot 3 or 4 dimensional data (series of single-channel or RGB mages), but found data of shape %s&#34; %
                                  (self.data.shape))
@@ -176,7 +179,7 @@ <h1 class="title">Module <code>pyaurorax.tools.classes.montage</code></h1>
             if (timestamps_display is True):
                 ax.text(
                     int(np.floor(self.data.shape[1] / 2.)),
-                    0.5,
+                    5,
                     self.timestamp[i].strftime(timestamps_format),
                     ha=&#34;center&#34;,
                     fontsize=timestamps_fontsize,
@@ -232,7 +235,7 @@ <h2 class="section-title" id="header-classes">Classes</h2>
 <dl>
 <dt id="pyaurorax.tools.classes.montage.Montage"><code class="flex name class">
 <span>class <span class="ident">Montage</span></span>
-<span>(</span><span>data: numpy.ndarray, timestamp: List[datetime.datetime])</span>
+<span>(</span><span>data: numpy.ndarray, timestamp: List[datetime.datetime], n_channels: int)</span>
 </code></dt>
 <dd>
 <div class="desc"><p>Class representation for a montage</p>
@@ -260,11 +263,14 @@ <h2 id="attributes">Attributes</h2>
             Timestamps corresponding to each montage image.
     &#34;&#34;&#34;
 
-    def __init__(self, data: np.ndarray, timestamp: List[datetime.datetime]):
+    def __init__(self, data: np.ndarray, timestamp: List[datetime.datetime], n_channels: int):
         # public vars
         self.data = data
         self.timestamp = timestamp
 
+        # private vars
+        self.__n_channels = n_channels
+
     def __str__(self) -&gt; str:
         return self.__repr__()
 
@@ -354,12 +360,12 @@ <h2 id="attributes">Attributes</h2>
 
         # for each image
         for ax, i in zip(axs.flat, range(0, len(self.timestamp))):
-            if (len(self.data.shape) == 3):
+            if (self.__n_channels == 1):
                 # single channel
                 ax.imshow(self.data[:, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
-            elif (len(self.data.shape) == 4):
+            elif (self.__n_channels == 3):
                 # single channel
-                ax.imshow(self.data[:, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
+                ax.imshow(self.data[:, :, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
             else:
                 raise ValueError(&#34;Can only plot 3 or 4 dimensional data (series of single-channel or RGB mages), but found data of shape %s&#34; %
                                  (self.data.shape))
@@ -370,7 +376,7 @@ <h2 id="attributes">Attributes</h2>
             if (timestamps_display is True):
                 ax.text(
                     int(np.floor(self.data.shape[1] / 2.)),
-                    0.5,
+                    5,
                     self.timestamp[i].strftime(timestamps_format),
                     ha=&#34;center&#34;,
                     fontsize=timestamps_fontsize,
@@ -550,12 +556,12 @@ <h2 id="raises">Raises</h2>
 
     # for each image
     for ax, i in zip(axs.flat, range(0, len(self.timestamp))):
-        if (len(self.data.shape) == 3):
+        if (self.__n_channels == 1):
             # single channel
             ax.imshow(self.data[:, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
-        elif (len(self.data.shape) == 4):
+        elif (self.__n_channels == 3):
             # single channel
-            ax.imshow(self.data[:, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
+            ax.imshow(self.data[:, :, :, i], cmap=cmap, origin=&#34;lower&#34;, interpolation=&#34;nearest&#34;)
         else:
             raise ValueError(&#34;Can only plot 3 or 4 dimensional data (series of single-channel or RGB mages), but found data of shape %s&#34; %
                              (self.data.shape))
@@ -566,7 +572,7 @@ <h2 id="raises">Raises</h2>
         if (timestamps_display is True):
             ax.text(
                 int(np.floor(self.data.shape[1] / 2.)),
-                0.5,
+                5,
                 self.timestamp[i].strftime(timestamps_format),
                 ha=&#34;center&#34;,
                 fontsize=timestamps_fontsize,