diff --git a/README.md b/README.md
index 4066de4..0e12781 100644
--- a/README.md
+++ b/README.md
@@ -11,13 +11,15 @@ For full dashboard functionality, upload a CSV or XLS file with the following co
- `View`: View of the sample (eg., 'ventral' or 'dorsal' for butterflies).
- `Sex`: Sex of each sample.
- `hybrid_stat`: Hybrid status of each sample (eg., 'valid_subspecies', 'subspecies_synonym', or 'unknown').
-- `lat`*: Latitude at which image was taken or specimen was collected.
-- `lon`*: Longitude at which image was taken or specimen was collected.
+- `lat`*: Latitude at which image was taken or specimen was collected: number in [-90,90].
+- `lon`*: Longitude at which image was taken or specimen was collected: number in [-180,180]. `long` will also be accepted.
- `file_url`*: URL to access file.
***Note:**
-- `lat` and `lon` columns are not required to utilize the dashboard, but there will be no map view if they are not included.
+- Column names are **not** case-sensitive.
+- `lat` and `lon` columns are not required to utilize the dashboard, but there will be no map view if they are not included. Blank (or null) entries are recorded as `unknown`, and thus excluded from map view.
- `Image_filename` and `file_url` are not required, but there will be no sample images option if either one is not included.
+- `locality` may be provided, otherwise it will take on the value `lat|lon` or `unknown` if these are not provided.
## Running Dashboard
diff --git a/components/divs.py b/components/divs.py
index 80df309..e4e58e8 100644
--- a/components/divs.py
+++ b/components/divs.py
@@ -3,7 +3,7 @@
# Fixed styles and sorting options
H1_STYLE = {'textAlign': 'center', 'color': 'MidnightBlue'}
H4_STYLE = {'color': 'MidnightBlue', 'margin-bottom' : 10}
-HALF_DIV_STYLE = {'width': '48%', 'display': 'inline-block'}
+HALF_DIV_STYLE = {'height': '48%', 'width': '48%', 'display': 'inline-block'}
QUARTER_DIV_STYLE = {'width': '24%', 'display': 'inline-block'}
BUTTON_STYLE = {'color': 'MidnightBlue',
'background-color': 'BlanchedAlmond',
@@ -18,10 +18,14 @@
{'label': 'Subspecies', 'value': 'Subspecies'},
{'label':'View', 'value': 'View'},
{'label': 'Sex', 'value': 'Sex'},
- {'label': 'Hybrid Status', 'value':'hybrid_stat'},
- {'label': 'Locality', 'value': 'locality'}
+ {'label': 'Hybrid Status', 'value':'Hybrid_stat'},
+ {'label': 'Locality', 'value': 'Locality'}
]
DOCS_URL = "https://github.com/Imageomics/dashboard-prototype#how-it-works"
+DOCS_LINK = html.A("documentation",
+ href=DOCS_URL,
+ target='_blank',
+ style = ERROR_STYLE)
def get_hist_div(mapping):
'''
@@ -124,6 +128,12 @@ def get_map_div():
),
html.Div([
+ html.H4('''
+ Note: Manual zooming may be required to view all points; the map focuses on the centroid of the data.
+ ''',
+ id = 'x-variable', #label to avoid nonexistent callback variable
+ style = {'color': 'MidnightBlue', 'margin-left': 20, 'margin-right': 20}
+ )
],
id = 'sort-by', #label sort-by box to avoid non-existent label and generate box so button doesn't move between views
style = HALF_DIV_STYLE
@@ -192,8 +202,8 @@ def get_img_div(df, all_species, img_url):
style = QUARTER_DIV_STYLE
),
html.Div([
- dcc.Checklist(df.hybrid_stat.unique(),
- df.hybrid_stat.unique()[0:2],
+ dcc.Checklist(df.Hybrid_stat.unique(),
+ df.Hybrid_stat.unique()[0:2],
id = 'hybrid?')],
style = QUARTER_DIV_STYLE
),
@@ -267,7 +277,10 @@ def get_main_div(hist_div, img_div):
# Graphs - Distribution (histogram or map), then pie chart
html.Div([
- dcc.Graph(id = 'dist-plot')], style = HALF_DIV_STYLE),
+ dcc.Loading(id = 'dist-plot-loading',
+ type = "circle",
+ color = 'DarkMagenta',
+ children = dcc.Graph(id = 'dist-plot'))], style = HALF_DIV_STYLE),
html.Div([
dcc.Graph(id = 'pie-plot')], style = HALF_DIV_STYLE),
@@ -303,20 +316,24 @@ def get_error_div(error_dict):
html.H3("Source data does not have '" + feature + "' column. ",
style = ERROR_STYLE),
html.H4(["Please see the ",
- html.A("documentation",
- href=DOCS_URL,
- target='_blank',
- style = ERROR_STYLE),
+ DOCS_LINK,
" for list of required columns."],
style = ERROR_STYLE)
])
+ elif 'mapping' in error_dict.keys():
+ error_msg = error_dict['mapping']
+ error_div = html.Div([
+ html.H4("Latitude or longitude columns have non-numeric values: " + error_msg + ".",
+ style = ERROR_STYLE),
+ html.H4(["Please see the ",
+ DOCS_LINK,
+ "."],
+ style = ERROR_STYLE)
+ ])
elif 'type' in error_dict.keys():
error_div = html.Div([
html.H4(["The source file is not a valid CSV format, please see the ",
- html.A("documentation",
- href=DOCS_URL,
- target='_blank',
- style = ERROR_STYLE),
+ DOCS_LINK,
"."],
style = ERROR_STYLE)
])
diff --git a/components/graphs.py b/components/graphs.py
index a1def62..e54fef0 100644
--- a/components/graphs.py
+++ b/components/graphs.py
@@ -26,7 +26,14 @@ def make_hist_plot(df, x_var, color_by, sort_by):
color = color_by,
color_discrete_sequence = px.colors.qualitative.Bold).update_xaxes(categoryorder = sort_by)
- fig.update_layout(title = {'text': f'Distribution of {x_var} Colored by {color_by}'})
+ fig.update_layout(title = {'text': f'Distribution of {x_var} Colored by {color_by}'},
+ font = {'size': 16},
+ margin = {
+ 'l': 30,
+ 'r': 20,
+ 't': 35,
+ 'b': 20
+ })
return fig
@@ -46,22 +53,17 @@ def make_map(df, color_by):
df = df.copy()
# only use entries that have valid lat & lon for mapping
df = df.loc[df['lat-lon'].str.contains('unknown') == False]
- fig = px.scatter_geo(df,
- lat = df.lat,
- lon = df.lon,
- projection = "natural earth",
+ fig = px.scatter_mapbox(df,
+ lat = "Lat",
+ lon = "Lon",
+ #projection = "natural earth",
custom_data = ["Samples_at_locality", "Species_at_locality", "Subspecies_at_locality"],
- size = df.Samples_at_locality,
+ size = "Samples_at_locality",
color = color_by,
color_discrete_sequence = px.colors.qualitative.Bold,
- title = "Distribution of Samples")
-
- fig.update_geos(fitbounds = "locations",
- showcountries = True, countrycolor = "Grey",
- showrivers = True,
- showlakes = True,
- showland = True, landcolor = "wheat",
- showocean = True, oceancolor = "LightBlue")
+ title = "Distribution of Samples",
+ zoom = 1,
+ mapbox_style = "white-bg")
fig.update_traces(hovertemplate =
"Latitude: %{lat}
"+
@@ -71,6 +73,24 @@ def make_map(df, color_by):
"Subspecies at lat/lon: %{customdata[2]}
"
)
+ fig.update_layout(
+ font = {'size': 16},
+ margin = {
+ 'l': 20,
+ 'r': 20,
+ 't': 35,
+ 'b': 20
+ },
+ mapbox_layers = [{
+ "below": "traces",
+ "sourcetype": "raster",
+ "sourceattribution": "Esri, Maxar, Earthstar Geographics, and the GIS User Community",
+ "source": ["https://services.arcgisonline.com/arcgis/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}"]
+ # Usage and Licensing (ArcGIS World Imagery): https://services.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer
+ # Style: https://roblabs.com/xyz-raster-sources/styles/arcgis-world-imagery.json
+ }]
+ )
+
return fig
def make_pie_plot(df, var):
@@ -97,6 +117,13 @@ def make_pie_plot(df, var):
color_discrete_sequence = px.colors.qualitative.Bold)
pie_fig.update_traces(textposition = 'inside', textinfo = 'percent+label')
- pie_fig.update_layout(title = {'text': f'Percentage Breakdown of {var}'})
+ pie_fig.update_layout(title = {'text': f'Percentage Breakdown of {var}'},
+ font = {'size': 16},
+ margin = {
+ 'l': 20,
+ 'r': 20,
+ 't': 35,
+ 'b': 20
+ })
return pie_fig
diff --git a/components/query.py b/components/query.py
index dbf57b3..d4e4813 100644
--- a/components/query.py
+++ b/components/query.py
@@ -17,7 +17,7 @@ def get_data(df, mapping, features):
df - DataFrame of the data to visualize.
mapping - Boolean. True when lat/lon are given in dataset.
features - List of features (columns) included in the DataFrame. This is a subset of the suggested columns:
- 'Species', 'Subspecies', 'View', 'Sex', 'hybrid_stat', 'lat', 'lon', 'file_url', 'Image_filename'
+ 'Species', 'Subspecies', 'View', 'Sex', 'Hybrid_stat', 'Lat', 'Lon', 'File_url', 'Image_filename'
Returns:
--------
@@ -29,24 +29,24 @@ def get_data(df, mapping, features):
# Will likely choose to calculate and return this in later instance
cat_list = [{'label': 'Species', 'value': 'Species'},
{'label': 'Subspecies', 'value': 'Subspecies'},
- {'label':'View', 'value': 'View'},
+ {'label': 'View', 'value': 'View'},
{'label': 'Sex', 'value': 'Sex'},
- {'label': 'Hybrid Status', 'value':'hybrid_stat'},
- {'label': 'Locality', 'value': 'locality'}
+ {'label': 'Hybrid Status', 'value':'Hybrid_stat'},
+ {'label': 'Locality', 'value': 'Locality'}
]
df = df.copy()
df = df.fillna('unknown')
- features.append('locality')
+ features.append('Locality')
# If we don't have lat/lon, just return DataFrame with otherwise required features.
if not mapping:
- if 'locality' not in df.columns:
- df['locality'] = 'unknown'
+ if 'Locality' not in df.columns:
+ df['Locality'] = 'unknown'
return df[features], cat_list
# else lat and lon are in dataset, so process locality information
- df['lat-lon'] = df['lat'].astype(str) + '|' + df['lon'].astype(str)
+ df['lat-lon'] = df['Lat'].astype(str) + '|' + df['Lon'].astype(str)
df["Samples_at_locality"] = df['lat-lon'].map(df['lat-lon'].value_counts()) # will duplicate if multiple views of same sample
# Count and record number of species and subspecies at each lat-lon
@@ -56,8 +56,8 @@ def get_data(df, mapping, features):
df.loc[df['lat-lon'] == lat_lon, "Species_at_locality"] = ", ".join(species_list)
df.loc[df['lat-lon'] == lat_lon, "Subspecies_at_locality"] = ", ".join(subspecies_list)
- if 'locality' not in df.columns:
- df['locality'] = df['lat-lon'] # contains "unknown" if lat or lon null
+ if 'Locality' not in df.columns:
+ df['Locality'] = df['lat-lon'] # contains "unknown" if lat or lon null
new_features = ['lat-lon', "Samples_at_locality", "Species_at_locality", "Subspecies_at_locality"]
for feature in new_features:
@@ -157,12 +157,12 @@ def get_filenames(df, subspecies, view, sex, hybrid, num_images):
df_sub = df.loc[df.Subspecies.isin(subspecies)].copy()
df_sub = df_sub.loc[df_sub.View.isin(view)]
df_sub = df_sub.loc[df_sub.Sex.isin(sex)]
- df_sub = df_sub.loc[df_sub.hybrid_stat.isin(hybrid)]
+ df_sub = df_sub.loc[df_sub.Hybrid_stat.isin(hybrid)]
num_entries = len(df_sub)
# Filter out any entries that have missing filenames or URLs:
df_sub = df_sub.loc[df_sub.Image_filename != 'unknown']
- df_sub = df_sub.loc[df_sub.file_url != 'unknown']
+ df_sub = df_sub.loc[df_sub.File_url != 'unknown']
max_imgs = len(df_sub)
missing_vals = num_entries - max_imgs
if max_imgs > 0:
@@ -172,7 +172,7 @@ def get_filenames(df, subspecies, view, sex, hybrid, num_images):
num = min(num_images, max_imgs)
df_filtered = df_sub.sample(num)
filenames = df_filtered.Image_filename.astype('string').values
- filepaths = df_filtered.file_url.astype('string').values
+ filepaths = df_filtered.File_url.astype('string').values
#return list of filenames for min(user-selected, available) images randomly selected images from the filtered dataset
return list(filenames), list(filepaths)
# If there aren't any images to display, check if there are no such entries or just missing information.
diff --git a/dashboard.py b/dashboard.py
index 933a745..9871148 100644
--- a/dashboard.py
+++ b/dashboard.py
@@ -1,4 +1,5 @@
import pandas as pd
+import numpy as np
import base64
import io
import json
@@ -80,13 +81,21 @@ def parse_contents(contents, filename):
# If no image urls, disable sample image options
mapping = True
img_urls = True
- features = ['Species', 'Subspecies', 'View', 'Sex', 'hybrid_stat', 'lat', 'lon', 'file_url', 'Image_filename']
+ features = ['Species', 'Subspecies', 'View', 'Sex', 'Hybrid_stat', 'Lat', 'Lon', 'File_url', 'Image_filename']
included_features = []
+ df.columns = df.columns.str.capitalize()
for feature in features:
if feature not in list(df.columns):
- if feature == 'lat' or feature == 'lon':
- mapping = False
- elif feature == 'file_url':
+ if feature == 'Lat' or feature == 'Lon':
+ if feature == 'Lon':
+ if 'Long' not in list(df.columns):
+ mapping = False
+ else:
+ df = df.rename(columns = {"Long": "Lon"})
+ included_features.append('Lon')
+ else:
+ mapping = False
+ elif feature == 'File_url':
img_urls = False
elif feature == 'Image_filename':
# If 'Image_filename' missing, return missing column if 'file_url' is included.
@@ -97,6 +106,18 @@ def parse_contents(contents, filename):
else:
included_features.append(feature)
+ # Check for lat/lon bounds & type if columns exist
+ if mapping:
+ try:
+ # Check lat and lon within appropriate ranges (lat: [-90, 90], lon: [-180, 180])
+ valid_lat = df['Lat'].astype(float).between(-90, 90)
+ df.loc[~valid_lat, 'Lat'] = 'unknown'
+ valid_lon = df['Lon'].astype(float).between(-180, 180)
+ df.loc[~valid_lon, 'Lon'] = 'unknown'
+ except ValueError as e:
+ print(e)
+ return json.dumps({'error': {'mapping': str(e)}})
+
# get dataset-determined static data:
# the dataframe and categorical features - processed for map view if mapping is True
# all possible species, subspecies
diff --git a/dashboard_preview_hist.png b/dashboard_preview_hist.png
index e19f557..fbafb71 100644
Binary files a/dashboard_preview_hist.png and b/dashboard_preview_hist.png differ
diff --git a/dashboard_preview_map.png b/dashboard_preview_map.png
index e6d11fd..888aede 100644
Binary files a/dashboard_preview_map.png and b/dashboard_preview_map.png differ
diff --git a/test_data/HCGSD_test_latLonOOB.csv b/test_data/HCGSD_test_latLonOOB.csv
new file mode 100644
index 0000000..9cb0a65
--- /dev/null
+++ b/test_data/HCGSD_test_latLonOOB.csv
@@ -0,0 +1,11 @@
+NHM_Specimen,Image_filename,View,Species,Subspecies,Sex,addit_taxa_info,type_stat,hybrid_stat,in_reduced,locality,lat,lon,speciesdesig,file_url
+10429021,10429021_V_lowres.png,,erato,notabilis,,f._notabilis,,subspecies synonym,1,,-1.583333333,-77.75,e. notabilis,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428972,10428972_V_lowres.png,ventral,erato,petiverana,male,petiverana,,valid subspecies,1,Songolica (= Zongolica) MEX VC,18.66666667,-96.98333333,e. petiverana,
+10429172,,ventral,,petiverana,male,petiverana,,valid subspecies,1,San Ramon NIC ZE,92,-84.68333333,e. petiverana,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428595,10428595_D_lowres.png,dorsal,erato,phyllis,male,f._phyllis,,subspecies synonym,1,Resistencia ARG CH,-27.45,-58.98333333,e. phyllis,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
+10428140,10428140_V_lowres.png,ventral,,plesseni,male,plesseni,,valid subspecies,1,Banos ECD TU,-1.4,-740,m. plesseni,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428250,10428250_V_lowres.png,ventral,melpomene,,male,ab._rubra,,subspecies synonym,1,Caradoc (Hda) PER CU,-13.36666667,-70.95,m. schunkei,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10427979,,dorsal,melpomene,rosina_S,male,rosina_S,,valid subspecies,1,Turrialba CRI CA,9.883333333,-83.63333333,m. rosina,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
+10428803,10428803_D_lowres.png,dorsal,erato,guarica,female,guarica,,valid subspecies,1,Fusagasuga COL CN,4.35,-74.36666667,e. guarica,
+10428169,10428169_V_lowres.png,ventral,melpomene,plesseni,male,f._pura,ST,subspecies synonym,1,Canelos ECD PA,-1.583333333,730,m. plesseni,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428321,10428321_D_lowres.png,,melpomene,nanna,male,nanna,ST,valid subspecies,1,Espirito Santo BRA ES,-20.33333333,-40.28333333,m. nanna,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
\ No newline at end of file
diff --git a/test_data/HCGSD_test_latLong.csv b/test_data/HCGSD_test_latLong.csv
new file mode 100644
index 0000000..bf88cbc
--- /dev/null
+++ b/test_data/HCGSD_test_latLong.csv
@@ -0,0 +1,11 @@
+NHM_Specimen,Image_filename,View,Species,Subspecies,Sex,addit_taxa_info,type_stat,hybrid_stat,in_reduced,locality,lat,long,speciesdesig,file_url
+10429021,10429021_V_lowres.png,,erato,notabilis,,f._notabilis,,subspecies synonym,1,,-1.583333333,-77.75,e. notabilis,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428972,10428972_V_lowres.png,ventral,erato,petiverana,male,petiverana,,valid subspecies,1,Songolica (= Zongolica) MEX VC,18.66666667,-96.98333333,e. petiverana,
+10429172,,ventral,,petiverana,male,petiverana,,valid subspecies,1,San Ramon NIC ZE,89,-84.68333333,e. petiverana,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428595,10428595_D_lowres.png,dorsal,erato,phyllis,male,f._phyllis,,subspecies synonym,1,Resistencia ARG CH,-27.45,-58.98333333,e. phyllis,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
+10428140,10428140_V_lowres.png,ventral,,plesseni,male,plesseni,,valid subspecies,1,Banos ECD TU,-1.4,-74,m. plesseni,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428250,10428250_V_lowres.png,ventral,melpomene,,male,ab._rubra,,subspecies synonym,1,Caradoc (Hda) PER CU,-13.36666667,-70.95,m. schunkei,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10427979,,dorsal,melpomene,rosina_S,male,rosina_S,,valid subspecies,1,Turrialba CRI CA,9.883333333,-83.63333333,m. rosina,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
+10428803,10428803_D_lowres.png,dorsal,erato,guarica,female,guarica,,valid subspecies,1,Fusagasuga COL CN,4.35,-74.36666667,e. guarica,
+10428169,10428169_V_lowres.png,ventral,melpomene,plesseni,male,f._pura,ST,subspecies synonym,1,Canelos ECD PA,-1.583333333,73,m. plesseni,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428321,10428321_D_lowres.png,,melpomene,nanna,male,nanna,ST,valid subspecies,1,Espirito Santo BRA ES,-20.33333333,-40.28333333,m. nanna,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
\ No newline at end of file
diff --git a/test_data/HCGSD_test_nonnumeric.csv b/test_data/HCGSD_test_nonnumeric.csv
new file mode 100644
index 0000000..2cc8cc2
--- /dev/null
+++ b/test_data/HCGSD_test_nonnumeric.csv
@@ -0,0 +1,11 @@
+NHM_Specimen,Image_filename,View,Species,Subspecies,Sex,addit_taxa_info,type_stat,hybrid_stat,in_reduced,locality,lat,lon,speciesdesig,file_url
+10429021,10429021_V_lowres.png,,erato,notabilis,,f._notabilis,,subspecies synonym,1,,-1.583333333,-77.75,e. notabilis,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428972,10428972_V_lowres.png,ventral,erato,petiverana,male,petiverana,,valid subspecies,1,Songolica (= Zongolica) MEX VC,18.66666667,,e. petiverana,
+10429172,,ventral,,petiverana,male,petiverana,,valid subspecies,1,San Ramon NIC ZE,92,-84.68333333,e. petiverana,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428595,10428595_D_lowres.png,dorsal,erato,phyllis,male,f._phyllis,,subspecies synonym,1,Resistencia ARG CH,-27.45,-58.98333333,e. phyllis,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
+10428140,10428140_V_lowres.png,ventral,,plesseni,male,plesseni,,valid subspecies,1,Banos ECD TU,,Non numeric,m. plesseni,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428250,10428250_V_lowres.png,ventral,melpomene,,male,ab._rubra,,subspecies synonym,1,Caradoc (Hda) PER CU,-13.36666667,-70.95,m. schunkei,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10427979,,dorsal,melpomene,rosina_S,male,rosina_S,,valid subspecies,1,Turrialba CRI CA,Non numeric,-83.63333333,m. rosina,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
+10428803,10428803_D_lowres.png,dorsal,erato,guarica,female,guarica,,valid subspecies,1,Fusagasuga COL CN,4.35,-74.36666667,e. guarica,
+10428169,10428169_V_lowres.png,ventral,melpomene,plesseni,male,f._pura,ST,subspecies synonym,1,Canelos ECD PA,-1.583333333,,m. plesseni,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/ventral_images/
+10428321,10428321_D_lowres.png,,melpomene,nanna,male,nanna,ST,valid subspecies,1,Espirito Santo BRA ES,-20.33333333,-40.28333333,m. nanna,https://github.com/Imageomics/dashboard-prototype/raw/main/test_data/images/dorsal_images/
\ No newline at end of file
diff --git a/tests/components/test_divs.py b/tests/components/test_divs.py
index cf162a4..28341cc 100644
--- a/tests/components/test_divs.py
+++ b/tests/components/test_divs.py
@@ -29,7 +29,7 @@ def test_get_img_div():
'Subspecies': ['subspecies1', 'subspecies2', 'subspecies4'],
'View': ['ventral', 'ventral', 'dorsal'],
'Sex': ['male', 'female', 'female'],
- 'hybrid_stat': ['subspecies synonym', 'valid subspecies', 'subspecies synonym']
+ 'Hybrid_stat': ['subspecies synonym', 'valid subspecies', 'subspecies synonym']
}
df = pd.DataFrame(data = data)
diff --git a/tests/components/test_graphs.py b/tests/components/test_graphs.py
index 7f6cd88..1f2d4bf 100644
--- a/tests/components/test_graphs.py
+++ b/tests/components/test_graphs.py
@@ -4,7 +4,9 @@
# Define test data
df = pd.read_csv("test_data/HCGSD_full_testNA.csv")
-included_features = ['Species', 'Subspecies', 'View', 'Sex', 'hybrid_stat', 'lat', 'lon', 'file_url', 'Image_filename']
+# Update columns since not running through parse
+df.columns = df.columns.str.capitalize()
+included_features = ['Species', 'Subspecies', 'View', 'Sex', 'Hybrid_stat', 'Lat', 'Lon', 'File_url', 'Image_filename']
processed_df, cat_list = get_data(df, True, included_features)
def test_make_hist_plot():
@@ -25,7 +27,7 @@ def test_make_map():
# Map plot output
output = make_map(processed_df, "Species")
output_data = output['data', 0]
- assert output_data.type == "scattergeo"
+ assert output_data.type == "scattermapbox"
#test for uknowns in data and check it's proper type
assert 'unknown' not in output_data['customdata']
diff --git a/tests/components/test_query.py b/tests/components/test_query.py
index 9d8eb67..7be5180 100644
--- a/tests/components/test_query.py
+++ b/tests/components/test_query.py
@@ -23,23 +23,23 @@ def test_get_data(self):
data = {
'Species': ['melpomene', 'melpomene', 'erato', 'melpomene', 'erato', 'species3'],
'Subspecies': ['schunkei', 'nanna', 'erato', 'rosina_N', 'guarica', None],
- 'lat': [-13.43, 5.25, 5.25, 9.9, 5.25, 9.9],
- 'lon': [-70.38, -55.25, -55.25, -83.73, -55.25, -55.25]
+ 'Lat': [-13.43, 5.25, 5.25, 9.9, 5.25, 9.9],
+ 'Lon': [-70.38, -55.25, -55.25, -83.73, -55.25, -55.25]
}
cat_list = [{'label': 'Species', 'value': 'Species'},
{'label': 'Subspecies', 'value': 'Subspecies'},
{'label':'View', 'value': 'View'},
{'label': 'Sex', 'value': 'Sex'},
- {'label': 'Hybrid Status', 'value':'hybrid_stat'},
- {'label': 'Locality', 'value': 'locality'}]
- features = ['Species', 'Subspecies', 'lat', 'lon']
+ {'label': 'Hybrid Status', 'value':'Hybrid_stat'},
+ {'label': 'Locality', 'value': 'Locality'}]
+ features = ['Species', 'Subspecies', 'Lat', 'Lon']
locality = ['-13.43|-70.38', '5.25|-55.25', '5.25|-55.25', '9.9|-83.73','5.25|-55.25', '9.9|-55.25']
# Test with mapping = True (location data)
df = pd.DataFrame(data = data)
result_df, result_list = get_data(df, True, features)
self.assertEqual(result_df['lat-lon'].tolist(), locality)
- self.assertEqual(result_df['locality'].tolist(), locality)
+ self.assertEqual(result_df['Locality'].tolist(), locality)
self.assertEqual(result_df["Samples_at_locality"].tolist(), [1,3,3,1,3,1])
self.assertEqual(result_df["Species_at_locality"].tolist(), ['melpomene', 'melpomene, erato', 'melpomene, erato', 'melpomene', 'melpomene, erato', 'species3'])
self.assertEqual(result_df["Subspecies_at_locality"].tolist(), ['schunkei', 'nanna, erato, guarica', 'nanna, erato, guarica', 'rosina_N', 'nanna, erato, guarica', 'unknown'])
@@ -48,8 +48,7 @@ def test_get_data(self):
# Test with mapping = False (no location data)
df2 = pd.DataFrame(data = {key: data[key] for key in ['Species', 'Subspecies']})
result_df2, result2_list = get_data(df2, False, features[:2])
- #self.assertEqual('locality' not in result_df2.columns, True)
- self.assertEqual(result_df2['locality'].tolist(), ['unknown' for i in range(len(locality))])
+ self.assertEqual(result_df2['Locality'].tolist(), ['unknown' for i in range(len(locality))])
self.assertEqual(result_df2["Species"].tolist(), ['melpomene', 'melpomene', 'erato', 'melpomene', 'erato', 'species3'])
self.assertEqual(result_df2["Subspecies"].tolist(), ['schunkei', 'nanna', 'erato', 'rosina_N', 'guarica', 'unknown'])
self.assertEqual(result2_list, cat_list)
@@ -62,7 +61,7 @@ def test_get_filenames(self):
'Subspecies': ['schunkei', 'nanna', 'erato', 'rosina_N', 'guarica', 'subspecies6', 'subspecies6'],
'View': ['ventral', 'ventral', 'ventral', 'dorsal', 'dorsal', 'ventral', 'dorsal'],
'Sex': ['male', 'female', 'female', 'male', 'female', 'male', 'female'],
- 'hybrid_stat': ['subspecies synonym',
+ 'Hybrid_stat': ['subspecies synonym',
'valid subspecies',
'subspecies synonym',
'valid subspecies',
@@ -76,7 +75,7 @@ def test_get_filenames(self):
'10428804_D_lowres.png',
'unknown',
'10428723_V_lowres.png'],
- 'file_url': [BASE_URL_V,
+ 'File_url': [BASE_URL_V,
BASE_URL_V,
BASE_URL_V,
BASE_URL_D,
diff --git a/tests/test_app_callbacks.py b/tests/test_app_callbacks.py
index 0548729..bb7a44b 100644
--- a/tests/test_app_callbacks.py
+++ b/tests/test_app_callbacks.py
@@ -3,7 +3,7 @@
from dashboard import update_dist_view, update_dist_plot, update_pie_plot, set_subspecies_options, update_display
# Define test data
-data = {'processed_df': '{"columns":["Species","Subspecies","View","Sex","hybrid_stat","lat","lon","lat-lon","Samples_at_locality","Species_at_locality","Subspecies_at_locality"],"index":[0,1,2,3,4,5,6,7,8,9],"data":[["erato","notabilis","unknown","unknown","subspecies synonym",-1.583333333,-77.75,"-1.583333333|-77.75",1,"erato","notabilis"],["erato","petiverana","ventral","male","valid subspecies",18.66666667,-96.98333333,"18.66666667|-96.98333333",1,"erato","petiverana"],["unknown","petiverana","ventral","male","valid subspecies","unknown",-84.68333333,"unknown|-84.68333333",1,"unknown","petiverana"],["erato","phyllis","dorsal","male","subspecies synonym",-27.45,-58.98333333,"-27.45|-58.98333333",1,"erato","phyllis"],["unknown","plesseni","ventral","male","valid subspecies",-1.4,"unknown","-1.4|unknown",1,"unknown","plesseni"],["melpomene","unknown","ventral","male","subspecies synonym",-13.36666667,-70.95,"-13.36666667|-70.95",1,"melpomene","unknown"],["melpomene","rosina_S","dorsal","male","valid subspecies",9.883333333,-83.63333333,"9.883333333|-83.63333333",1,"melpomene","rosina_S"],["erato","guarica","dorsal","female","valid subspecies",4.35,-74.36666667,"4.35|-74.36666667",1,"erato","guarica"],["melpomene","plesseni","ventral","male","subspecies synonym",-1.583333333,"unknown","-1.583333333|unknown",1,"melpomene","plesseni"],["melpomene","nanna","unknown","male","valid subspecies",-20.33333333,-40.28333333,"-20.33333333|-40.28333333",1,"melpomene","nanna"]]}',
+data = {'processed_df': '{"columns":["Species","Subspecies","View","Sex","Hybrid_stat","Lat","Lon","lat-lon","Samples_at_locality","Species_at_locality","Subspecies_at_locality"],"index":[0,1,2,3,4,5,6,7,8,9],"data":[["erato","notabilis","unknown","unknown","subspecies synonym",-1.583333333,-77.75,"-1.583333333|-77.75",1,"erato","notabilis"],["erato","petiverana","ventral","male","valid subspecies",18.66666667,-96.98333333,"18.66666667|-96.98333333",1,"erato","petiverana"],["unknown","petiverana","ventral","male","valid subspecies","unknown",-84.68333333,"unknown|-84.68333333",1,"unknown","petiverana"],["erato","phyllis","dorsal","male","subspecies synonym",-27.45,-58.98333333,"-27.45|-58.98333333",1,"erato","phyllis"],["unknown","plesseni","ventral","male","valid subspecies",-1.4,"unknown","-1.4|unknown",1,"unknown","plesseni"],["melpomene","unknown","ventral","male","subspecies synonym",-13.36666667,-70.95,"-13.36666667|-70.95",1,"melpomene","unknown"],["melpomene","rosina_S","dorsal","male","valid subspecies",9.883333333,-83.63333333,"9.883333333|-83.63333333",1,"melpomene","rosina_S"],["erato","guarica","dorsal","female","valid subspecies",4.35,-74.36666667,"4.35|-74.36666667",1,"erato","guarica"],["melpomene","plesseni","ventral","male","subspecies synonym",-1.583333333,"unknown","-1.583333333|unknown",1,"melpomene","plesseni"],["melpomene","nanna","unknown","male","valid subspecies",-20.33333333,-40.28333333,"-20.33333333|-40.28333333",1,"melpomene","nanna"]]}',
'all_species': {'Erato': ['Any-Erato', 'notabilis', 'petiverana', 'phyllis', 'guarica'], 'Unknown': ['Any-Unknown', 'petiverana', 'plesseni'], 'Melpomene': ['Any-Melpomene', 'unknown', 'rosina_S', 'plesseni', 'nanna'], 'Any': ['Any', 'notabilis', 'petiverana', 'phyllis', 'plesseni', 'unknown', 'rosina_S', 'guarica', 'nanna']},
'mapping': True,
'images': True}
@@ -34,7 +34,7 @@ def test_update_dist_plot_call():
# Map plot output
output2 = update_dist_plot('Species', 'Subspecies', 'alpha', "Show Histogram", jsonified_data)
- assert output2['data', 0].type == "scattergeo"
+ assert output2['data', 0].type == "scattermapbox"
def test_update_pie_plot():
diff --git a/tests/test_filters.py b/tests/test_filters.py
index 772fb1f..778b2be 100644
--- a/tests/test_filters.py
+++ b/tests/test_filters.py
@@ -19,15 +19,16 @@ def generate_mock_upload(filepath):
contents = "".join([content_type, ",", content_string])
return contents
+ALL_COLUMNS = ['Species', 'Subspecies', 'View', 'Sex', 'Hybrid_stat', 'Lat', 'Lon',
+ 'File_url', 'Image_filename', 'Locality', 'lat-lon',
+ 'Samples_at_locality', 'Species_at_locality', 'Subspecies_at_locality']
# Define Test Cases
test_cases = [
{ # Check with full columns expected
"filepath": "test_data/HCGSD_full_testNA.csv",
"filename": "HCGSD_full_testNA.csv",
- "expected_columns": ['Species', 'Subspecies', 'View', 'Sex', 'hybrid_stat', 'lat', 'lon',
- 'file_url', 'Image_filename', 'locality', 'lat-lon',
- 'Samples_at_locality', 'Species_at_locality', 'Subspecies_at_locality'],
+ "expected_columns": ALL_COLUMNS,
"expected_mapping": True,
"expected_images": True
},
@@ -35,16 +36,16 @@ def generate_mock_upload(filepath):
"filepath": "test_data/HCGSD_test_no_mapping.csv",
"filename": "HCGSD_test_no_mapping.csv",
# 'lon' in data, 'lat' not, 'lon' maintained
- "expected_columns": ['Species', 'Subspecies', 'View', 'Sex', 'hybrid_stat', 'lon',
- 'locality'],
+ "expected_columns": ['Species', 'Subspecies', 'View', 'Sex', 'Hybrid_stat', 'Lon',
+ 'Locality'],
"expected_mapping": False,
"expected_images": False
},
{ # Check with missing image URL information
"filepath": "test_data/HCGSD_testNA.csv",
"filename": "HCGSD_testNA.csv",
- "expected_columns": ['Species', 'Subspecies', 'View', 'Sex', 'hybrid_stat', 'lat', 'lon',
- 'Image_filename', 'locality', 'lat-lon',
+ "expected_columns": ['Species', 'Subspecies', 'View', 'Sex', 'Hybrid_stat', 'Lat', 'Lon',
+ 'Image_filename', 'Locality', 'lat-lon',
'Samples_at_locality', 'Species_at_locality', 'Subspecies_at_locality'],
"expected_mapping": True,
"expected_images": False
@@ -52,11 +53,25 @@ def generate_mock_upload(filepath):
{ # Check with just missing mapping information
"filepath": "test_data/HCGSD_test_nolon.csv",
"filename": "HCGSD_test_nolon.csv",
- "expected_columns": ['Species', 'Subspecies', 'View', 'Sex', 'hybrid_stat', 'lat',
- 'file_url', 'Image_filename', 'locality'],
+ "expected_columns": ['Species', 'Subspecies', 'View', 'Sex', 'Hybrid_stat', 'Lat',
+ 'File_url', 'Image_filename', 'Locality'],
"expected_mapping": False,
"expected_images": True
},
+ { # Check with full columns expected, but lat/lon out of bounds (1 lat and 2 lon)
+ "filepath": "test_data/HCGSD_test_latLonOOB.csv",
+ "filename": "HCGSD_test_latLonOOB.csv",
+ "expected_columns": ALL_COLUMNS,
+ "expected_mapping": True,
+ "expected_images": True
+ },
+ { # Check with full columns expected, but 'long' instead of 'lon'
+ "filepath": "test_data/HCGSD_test_latLong.csv",
+ "filename": "HCGSD_test_latLong.csv",
+ "expected_columns": ALL_COLUMNS,
+ "expected_mapping": True,
+ "expected_images": True
+ },
]
def test_parse_contents():
@@ -70,3 +85,7 @@ def test_parse_contents():
assert list(dff.columns) == case['expected_columns']
assert output['mapping'] == case['expected_mapping']
assert output['images'] == case['expected_images']
+
+ if case['filename'] == "HCGSD_test_latLonOOB.csv":
+ assert len(dff.loc[dff.Lat == 'unknown']) == 1
+ assert len(dff.loc[dff.Lon == 'unknown']) == 2