Merges refactor_plot

CHANGELOG.md

@@ -7,6 +7,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 [Unreleased]
 ### Added
 - `load_data` can read site location and system information for generating clear sky irradiance from a json or yaml file.
+- New plotting module with a plot function which replaces the CapData.plot method. The new plot function creates a panel dashboard with expanded functionality. Internally, removes
+the plotting dependency on the CapData.trans_keys attribute.
 
 ### Changed
 - `load_data` now checks if any individual files were loaded when loading multiple files from a directory.

docs/examples/clear_sky.ipynb

@@ -60,7 +60,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "meas_nrel.plot(ncols=1, width=800, merge_grps=['irr'],  subset=['irr_comb'], use_abrev_name=False)"
+    "meas_nrel.plot(default_groups=['irr_comb'], combine={'irr_comb':'poa|ghi'})"
    ]
   },
   {
@@ -365,7 +365,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "meas_nrel_trck.plot(ncols=1, width=800, merge_grps=['irr'],  subset=['irr_comb'], use_abrev_name=False)"
+    "meas_nrel_trck.plot(default_groups=['irr_comb'], combine={'irr_comb':'poa|ghi'})"
    ]
   }
  ],
@@ -386,7 +386,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.11"
+   "version": "3.11.3"
   },
   "toc": {
    "base_numbering": 1,

docs/examples/complete_capacity_test.ipynb

@@ -196,9 +196,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The plot method creates a group of time series plots that are useful for visually inspecting the imported data.\n",
+    "The plot method creates a dashboard with a group of time series plots that are useful for visually inspecting the imported data.\n",
     "\n",
-    "`plot` uses the structure of the `column_group` attribute to create a layout of plots. A single plot is generated for each measurement type and each column with measurements of that type are plotted as a separate line on the plot. In this example there are two different weather stations, which each have pyranometers measuring plane of array and global horizontal irradiance. This arrangement of sensors results in two plots which each have two lines."
+    "`plot` uses the structure of the `column_groups` attribute to create a layout of plots. A single plot is generated for each measurement type and each column with measurements of that type are plotted as a separate line on the plot. In this example there are two different weather stations, which each have pyranometers measuring plane of array and global horizontal irradiance. This arrangement of sensors results in two plots which each have two lines.\n",
+    "\n",
+    "Note, the full functionality of the dashboard requires a live notebook. Try installing to run or using the launch binder button at the top of the page. "
    ]
   },
   {
@@ -207,7 +209,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "das.plot(width=900, height=250, ncols=1, use_abrev_name=False)"
+    "combine = {'inv_sum_mtr_pwr': ['mtr', 'inv.*agg'], 'irr_all':['irr_poa', 'irr_ghi'], 'temp_all':['temp_amb', 'temp_mod']}\n",
+    "default_groups = ['inv_sum_mtr_pwr', 'irr_all', 'temp_all']\n",
+    "das.plot(combine=combine, default_groups=default_groups)"
    ]
   },
   {
@@ -694,7 +698,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.11"
+   "version": "3.11.3"
   }
  },
  "nbformat": 4,

docs/examples/concise_capacity_test.ipynb

@@ -79,13 +79,22 @@
     "das.agg_sensors(agg_map={'real_pwr_inv':'sum', 'irr_poa':'mean', 'temp_amb':'mean', 'wind':'mean'})"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note, the full functionality of the dashboard requires a live notebook. Try installing to run or using the launch binder button at the top of the page. "
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "das.plot(marker='line', width=900, height=250, ncols=1, use_abrev_name=False)"
+    "combine = {'inv_sum_mtr_pwr': ['mtr', 'inv.*agg'], 'irr_all':['irr_poa', 'irr_ghi'], 'temp_all':['temp_amb', 'temp_mod']}\n",
+    "default_groups = ['inv_sum_mtr_pwr', 'irr_all', 'temp_all']\n",
+    "das.plot(combine=combine, default_groups=default_groups)"
    ]
   },
   {
@@ -158,6 +167,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "das.data.index.name = 'Timestamp' # bug to be addressed in v0.13.0\n",
     "das.timeseries_filters().opts(width=1200)"
    ]
   },
@@ -336,7 +346,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.11"
+   "version": "3.11.3"
   }
  },
  "nbformat": 4,

docs/source/captest.rst

@@ -44,6 +44,14 @@ captest.util module
    :undoc-members:
    :show-inheritance:
 
+captest.plotting module
+-------------------
+
+.. automodule:: captest.plotting
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 .. Module contents
 .. ---------------
 

docs/source/modules.rst

@@ -9,3 +9,4 @@ captest
    io
    prtest
    util
+   plotting

docs/user_guide/dataload.rst

@@ -90,6 +90,56 @@ Screenshot of the excel file loaded in the Concise Example Capacity Test showing
 
     The column names in the column groups template excel file are sorted alphabetically after reversing the names, so names with the same ending are grouped together. This is often a good starting point for grouping the columns, but it is not always correct, so review carefully!
 
+Dashboard
+---------
+
+The :py:meth:`~captest.capdata.CapData.plot` method of CapData objects will create a `Panel <https://panel.holoviz.org/>`_ dashboard that can be used to explore timeseries plots of the data.
+
+The dashboard contains three tabs: Groups, Layout, and Overlay.
+
+Groups Tab
+~~~~~~~~~~
+The first tab, Groups, presents a column of plots with a separate plot overlaying the measurements for each group of the :py:attr:`~captest.capdata.CapData.column_groups` attribute. The groups plotted are defined by the ``default_groups`` argument. This is the default tab when the dashboard is first opened.
+
+.. image:: ../_images/dboard_groups.png
+
+The ``default_groups`` argument can be used to specify which groups to plot by passing a list of regular expressions which are used to search the keys of the :py:attr:`~captest.capdata.CapData.column_groups` attribute. The default list of regular expressions attempts to create the following plots:
+
+* Metered power and sum of inverter power, group name is "inv_sum_mtr_pwr"
+* Inverter power output - group id must contain "real", "pwr", "inv"
+* Metered power output - group id must contain "real", "pwr", "mtr"
+* GHI irradiance
+* Modeled clear sky POA irradiance
+* Modeled clear sky GHI irradiance
+* Ambient temperature and BOM temperature - group name is "temp_amb_bom"
+
+The groups names ``inv_sum_mtr_pwr`` and ``temp_amb_bom`` are not keys from :py:attr:`~captest.capdata.CapData.column_groups`, but are created from the dictionary keys of the ``combine`` argument. These labels are for combinations of groups from the ``column_groups`` attribute. The ``combine`` argument can be used to create these combined groups by passing a dictionary of group names and regular expressions. The regular expressions are used to identify groups from :py:attr:`~captest.capdata.CapData.column_groups` and individual tags (columns) of :py:attr:`~captest.capdata.CapData.data` to combine into new groups. The dictionary keys are strings which will be used as the names of new groups. Values should be either a string or a list of two strings. If a string, the string is used as a regex to identify groups to combine. If a list, the first string is used to identify groups to combine and the second is used to identify individual tags (columns) to combine.
+
+See the :py:func:`~captest.plotting.parse_combine` and :py:func:`~captest.plotting.find_default_groups` functions for more details.
+
+The `Layout` and `Overlay` tabs provide the same functionality of combining and selecting groups to be plotted on the `Groups` tab through a GUI without needing to write regular expressions.
+
+Layout Tab
+~~~~~~~~~~
+The `Layout` tab allows creating a column of plots like the `Groups` tab by selecting groups from the list.
+
+.. image:: ../_images/dboard_layout.png
+
+The button labeled "Set plots to current layout" above the list of groups can be used to replace the figure shown on the `Groups` tab with the current figure on the `Layout` tab. This will save a ``plot_defaults.json`` file in the current working directory that will be used to set the default groups for the `Groups` tab when the :py:meth:`~captest.capdata.CapData.plot` method is called. You will need to rerun the ``plot`` method to see the new defaults.
+
+.. note::
+
+    The ``plots_defaults.json`` file will override the ``default_groups`` argument. If you want to use the ``default_groups`` argument, you will need to delete the ``plot_defaults.json`` file.
+
+
+Overlay Tab
+~~~~~~~~~~~
+The `Overlay` tab allows picking a group or any combination of individual tags to overlay on a single plot similar to the functionality of the ``combine`` argument.
+
+.. image:: ../_images/dboard_overlay.png
+
+The list of groups and tags can be filtered using regular expressions. The text box at the top left of the tab is used to provide a label for the current overlay, which can be added to the list on the `Layout` tab by clicking the `Update` button. 
+
 Identifying Regression Data
 ---------------------------
 To perform the regression pvcaptest uses `statsmodels <https://www.statsmodels.org/stable/index.html>`_, which in turn `relies on patsy <https://www.statsmodels.org/stable/examples/notebooks/generated/formulas.html>`_ to simplify specifying regression equations.

src/captest/__init__.py

@@ -4,6 +4,7 @@
     prtest,
     columngroups,
     io,
+    plotting,
 )
 
 from captest.io import (