Revert "temporarily remove pop"

This reverts commit 4341c1f.

tests/test_plot_pop.py

@@ -0,0 +1,297 @@
+from unittest import TestCase
+
+import pytest
+
+import ldcpy
+
+ds = ldcpy.open_datasets(
+    'pop',
+    ['SST'],
+    [
+        'data/pop/pop.SST.60days.nc',
+        'data/pop/zfp1.0.pop.SST.60days.nc',
+        'data/pop/zfp1e-1.pop.SST.60days.nc',
+        'data/pop/zfp1e-2.pop.SST.60days.nc',
+    ],
+    ['orig', 'recon', 'recon2', 'recon3'],
+)
+
+
+class TestPlotPop(TestCase):
+    """
+    Note: The tests in this class currentlytest the plot() function in ldcpy.plot for a variety of different
+    parameters on ocean (POP) data
+    """
+
+    def test_mean(self):
+        ldcpy.plot(ds, 'SST', sets=['orig', 'recon'], calc='mean', vert_plot=True, tex_format=False)
+        self.assertTrue(True)
+
+    def test_standardized_mean(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon2'],
+            calc='standardized_mean',
+            plot_type='time_series',
+            lat=90,
+            lon=0,
+            calc_type='diff',
+            vert_plot=True,
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_mean_compare(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon2', 'recon3'],
+            calc='mean',
+            plot_type='spatial',
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_lag1(self):
+        ldcpy.plot(
+            ds, 'SST', sets=['orig', 'recon'], calc='lag1', plot_type='spatial', tex_format=False
+        )
+        self.assertTrue(True)
+
+    def test_lag1_first_difference(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon2'],
+            calc='lag1_first_difference',
+            plot_type='spatial',
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_annual_harmonic(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='ann_harmonic_ratio',
+            calc_type='calc_of_diff',
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_pooled_variance_ratio(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon', 'recon2'],
+            scale='log',
+            calc='pooled_var_ratio',
+            calc_type='diff',
+            tex_format=False,
+        )
+
+    def test_std_dev_compare(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='std',
+            color='cmo.thermal',
+            plot_type='spatial',
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_mean_diff(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='mean',
+            calc_type='diff',
+            transform='log',
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_prob_negative_log_compare(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='prob_negative',
+            color='coolwarm',
+            transform='log',
+            plot_type='spatial',
+            tex_format=False,
+        )
+        self.assertTrue(True is True)
+
+    def test_odds_positive_grouped(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='odds_positive',
+            plot_type='time_series',
+            group_by='time.month',
+            calc_ssim=True,
+            vert_plot=True,
+        )
+        self.assertTrue(True)
+
+    def test_prob_neg_compare(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='prob_negative',
+            color='binary',
+            plot_type='spatial',
+            tex_format=False,
+        )
+        self.assertTrue(True is True)
+
+    def test_mean_abs_diff_time_series(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon', 'recon2'],
+            calc='mean_abs',
+            calc_type='diff',
+            plot_type='time_series',
+            tex_format=False,
+        )
+        self.assertTrue(True is True)
+
+    @pytest.mark.nonsequential
+    def test_mean_diff_time_series_subset(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['recon', 'orig'],
+            calc_type='diff',
+            calc='mean',
+            plot_type='time_series',
+            subset='first50',
+            lat=44.56,
+            lon=-123.26,
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_subset_lat_lon_ratio_time_series(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='mean',
+            calc_type='ratio',
+            group_by=None,
+            subset='first50',
+            lat=44.76,
+            lon=-93.75,
+            plot_type='time_series',
+            tex_format=False,
+        )
+        self.assertTrue(True is True)
+
+    def test_periodogram_grouped(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='mean',
+            calc_type='raw',
+            plot_type='periodogram',
+            group_by='time.dayofyear',
+            tex_format=False,
+        )
+        self.assertTrue(True is True)
+
+    def test_winter_histogram(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='mean',
+            calc_type='diff',
+            subset='winter',
+            plot_type='histogram',
+            group_by='time.dayofyear',
+            tex_format=False,
+        )
+        self.assertTrue(True is True)
+
+    def test_zscore_plot(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc_type='calc_of_diff',
+            calc='zscore',
+            tex_format=False,
+        )
+        self.assertTrue(True is True)
+
+    def test_ssim(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='mean',
+            plot_type='spatial',
+            calc_ssim=True,
+            tex_format=False,
+        )
+
+    def test_mae_max_day(self):
+        ldcpy.plot(ds, 'SST', sets=['orig'], calc='mae_day_max', tex_format=False)
+
+    def test_std_by_month(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='mean',
+            plot_type='time_series',
+            group_by='time.month',
+            calc_type='diff',
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    # Time series plot of first seven TS mean data points for ds orig dataset
+    def test_mean_start_end(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig'],
+            calc='mean',
+            start=0,
+            end=8,
+            plot_type='time_series',
+            tex_format=False,
+        )
+        self.assertTrue(True)
+
+    def test_mean_time_series(self):
+        ldcpy.plot(ds, 'SST', sets=['orig'], calc='mean', plot_type='time_series', tex_format=False)
+        self.assertTrue(True)
+
+    def test_periodogram(self):
+        ldcpy.plot(ds, 'SST', sets=['orig'], calc='mean', plot_type='periodogram', tex_format=False)
+        self.assertTrue(True)
+
+    def test_plot_multiple_time_series(self):
+        ldcpy.plot(
+            ds,
+            'SST',
+            sets=['orig', 'recon'],
+            calc='mean',
+            plot_type='time_series',
+            tex_format=False,
+        )
+        self.assertTrue(True)